claude-code-skills

47 marketing skills across 8 pods: Content, SEO & AEO, CRO, Channels, Growth, Intelligence, Sales enablement, and X/Twitter growth. 62 Python tools, 89 reference docs.

46 skills

37 advanced engineering skills: agent designer, agent workflow designer, RAG architect, database designer + schema designer + SQL assistant, migration architect, observability designer, dependency auditor, changelog generator (semantic version bumper + hotfix/rollback), API design reviewer, API test suite builder, CI/CD pipeline builder, MCP server builder, skill security auditor, skill tester, performance profiler, focused-fix, browser-automation, full-page-screenshot, git-worktree-manager, monorepo-navigator, codebase-onboarding, interview-system-designer, runbook-generator, spec-driven-workflow, secrets-vault-manager, env-secrets-manager, pr-review-expert, self-eval, tc-tracker, feature-flags-architect, kubernetes-operator, chaos-engineering, ship-gate (pre-production 8-category audit), slo-architect (error-budget + multi-window burn-rate alerts per Google SRE Workbook), and tech-debt-tracker. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.

43 skills

Founder-mode executive team plugin: 13 cs-* C-suite agents (CFO, CMO, CRO, CPO, COO, CHRO, CISO, Chief of Staff, General Counsel, Chief Data Officer, Chief AI Officer, Chief Customer Officer, VP of Engineering) with distinct cognitive voices, plus 21 /cs:* slash commands — forcing-question office hours (CFO/CMO/CPO/CRO/CTO/CISO/GC/CDO/CAIO/CCO/VPE reviews), strategic sprint pipeline (brief → boardroom → decide → execute → post-mortem), and meta routing (/cs:founder-mode auto-router, /cs:onboard, /cs:cross-eval multi-model consensus, /cs:freeze cooldown lock). Wraps the 33 c-level skills with cognitive gearing, persona voice, and artifact-driven handoffs. The business-domain answer to YC Garry Tan's gstack.

22 skills · 13 agents

33 C-level advisory skills (install the separate companion c-level-agents plugin for the persona layer): virtual board of directors (CEO, CTO, COO, CPO, CMO, CFO, CRO, CISO, CHRO) plus General Counsel, CDO, CAIO, CCO, and VP of Engineering (DORA delivery throughput analyzer, engineering hiring funnel calculator with conversion + pipeline gap, eng team structure designer with squad/tribe + manager-trigger), executive mentor, founder coach, orchestration (Chief of Staff, board meetings, decision logger), strategic capabilities (board deck builder, scenario war room, competitive intel, M&A playbook), culture frameworks. The 13 cs-* persona agents + 21 /cs:* slash commands (founder-mode router, office-hours intake, multi-role boardroom, strategic sprint pipeline, cross-model consensus, cooldown freeze) ship in the companion c-level-agents plugin.

34 skills

32 engineering skills: architecture, frontend, backend, fullstack, QA, DevOps, security, AI/ML, data engineering, Playwright (9 sub-skills), self-improving agent, Stripe integration, TDD guide, tech stack evaluator, Google Workspace CLI, a11y audit (WCAG 2.2), Azure cloud architect, GCP cloud architect, security pen testing, Snowflake development, adversarial-reviewer, ai-security, cloud-security, incident-response, red-team, threat-detection. v2.8.1 audits senior-fullstack / senior-frontend / senior-backend against karpathy-coder + Matt Pocock — each ships a 7-question forcing-question library, 4 customization profiles (JSON), deterministic decision engine, composition map into POWERFUL specialists, plus cs-fullstack-engineer / cs-frontend-engineer / cs-backend-engineer orchestrator agents (context: fork) + /cs:fullstack-review, /cs:frontend-review, /cs:backend-review, /cs:engineer-grill slash commands.

34 skills

Build, launch, grade, and schedule Claude Managed Agents (CMA) in your own Anthropic account — a plugin re-implementation of Anthropic's launch-your-agent reference skill (Apache-2.0; independent, not a fork). Every session starts with a goal (./my-agent/goal.json, opt-in SessionStart hook, driven by /cs:goal); loop_compiler.py compiles it into a bounded grade->iterate loop (max_iterations 1..20), a recurring cron scheduled-deployment loop, or a single-pass interview->stage->launch workflow. 6 skills: orchestrator (context: fork goal router) + interview + stage-launch + grade-iterate + run-without-you + wrap-up. 18 stdlib-only deterministic scaffolders (no network/API calls; live launches emitted as BYOK curl that never prints the key), 4 agents, 8 commands, hooks, 5 references, 4 assets. Validators enforce CMA limits. Distinct from engineering/agent-harness (generic domain loop) and write-a-skill (authors Claude Code skills, not CMAs).

6 skills · 8 commands · 4 agents · hooks

Per-deal-and-packaging Commercial domain. v2.8.0 ships 8 skills: orchestrator + pricing-strategist (model picker + Van Westendorp WTP + packaging) + deal-desk (deal scorer + discount approval routing + redline) + partnerships-architect (5-tier classifier + joint GTM + revshare modeler) + channel-economics (cost-to-serve + ROI + mix optimizer) + commercial-policy (data-backed discount matrix + exception flow + linter) + rfp-responder (Shipley structured RFP/RFI/RFQ + win-theme + winrate predictor, context: fork) + commercial-forecaster (4Q-weighted bookings + cohort NRR/GRR + funnel-confidence with mandatory assumption disclosure). Hard rules: pricing outputs model+range (never a single number), deal outputs route to named human approver (never auto-approve), forecast outputs surface conversion assumption, RFP never invents claims for GAP requirements. 21 stdlib Python tools, 28+ reference docs. Distinct from business-growth (sales execution), c-level-advisor/cro-advisor (strategic), finance (close+report).

8 skills · 9 commands · 1 agent

Compliance OS — meta-orchestrator for multi-framework compliance programs spanning 9 frameworks (ISO 27001, ISO 13485, ISO 42001, ISO 14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR). Framework selector, cross-framework control mapper, audit simulator, and consolidated evidence-pool generator (stdlib Python), plus 3 cs-* compliance agents and 3 /cs:* readiness commands.

9 skills · 8 agents

13 bundled product skills with 22 Python tools: product-skills fork-orchestrator with continuous-discovery loop (deterministic 16-lane router, Torres cadence tracker, OST linter, /cs:product + /cs:grill-product + /cs:product-loop), product manager toolkit (RICE, PRDs), product strategist, UX researcher, UI design system, competitive teardown, landing page generator, SaaS scaffolder, product analytics, experiment designer, product discovery, roadmap communicator, spec-to-repo. Companion standalone plugins: agile-product-owner, code-to-prd, apple-hig-expert, research-summarizer.

13 skills · 3 commands · 1 agent

14 regulatory affairs & quality management skills for HealthTech/MedTech: ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, GDPR/DSGVO, ISO 27001 ISMS, CAPA management, risk management, clinical evaluation, SOC 2 compliance.

17 skills

Internal BizOps domain. v2.8.0 ships 7 skills: orchestrator + process-mapper (BPMN/bottleneck/cycle-time, Lean+TOC) + vendor-management (scorecard+SLA+3rd-party risk, NIST SP 800-161/ISO 27036) + capacity-planner (Erlang-C queueing math for ops teams, NOT engineering) + internal-comms (ADKAR+Kotter 8-step, NOT marketing) + knowledge-ops (SOP+runbook+KB hygiene with 5W2H, context: fork) + procurement-optimizer (UNSPSC spend categorization + supplier consolidation). Orchestrator uses context: fork to route inquiries via Matt Pocock grill discipline (one question per turn, recommended answer, canon-cited challenge). Every SKILL.md ships a Forcing-question library section. 18 stdlib Python tools, 24+ reference docs. Distinct from business-growth (external sales) and c-level-advisor (strategic).

7 skills · 8 commands · 1 agent

Organic LinkedIn presence, end to end, with LinkedIn's own rules enforced in code. Orchestrator (context: fork) gates every request against User Agreement §8.2 — refusing automation, scraping, engagement pods, bulk DMs, fake identity and fabricated proof, each with a compliant substitute — then routes to profile / strategy / content / engagement / analytics. Headline and whole-profile scoring with fixes ranked by points per hour; positioning brief with a mandatory exclusion list; cadence priced against real hours with a 90-minute floor; newsletter eligibility + six-month sustainability gate; post linter blocking on engagement bait and screen-reader-hostile Unicode pseudo-bold; repurposing with a reuse ledger; capped commenting roster and template-refusing outreach; analytics that test patterns against a seeded permutation null and refuse to conclude below 10 posts. 17 stdlib tools, 15 references with per-claim confidence levels. No credentials, no API calls, nothing auto-sent. Answers discussion #934.

6 skills · 8 commands · 2 agents

9 project management skills with 15 Python tools: pm-skills fork-orchestrator with agentic delivery loop (deterministic 8-lane router, Jira MCP snapshot bridge to Kanban flow metrics + Monte Carlo forecasts, delegation-governance gate, /cs:pm + /cs:grill-pm + /cs:pm-loop), senior PM, scrum master, Jira expert, Confluence expert, Atlassian admin, template creator, meeting analyzer, team communications. Bundled Atlassian Remote MCP.

9 skills · 3 commands · 1 agent · 1 MCP server

Production-grade Playwright testing toolkit. 9 skills, 3 agents, 55 templates, plus optional (manually enabled) TestRail/BrowserStack integrations. Generate tests, fix flaky failures, migrate from Cypress/Selenium.

10 skills · 3 agents · hooks

Convert long markdown files into world-class single-file interactive HTML — DOMAIN COMPLETE at v2.10.3 (5 skills). v2.10.3 adds md-slides, the slide-deck converter (arrow/Space/PgDn/Home/End/P navigation, presenter mode with clock + speaker notes + next-slide preview, URL-hash deep linking, @media print page-per-slide for browser-native PDF export; vanilla JS only; Prism.js opt-in via --syntax). Joins md-review (v2.10.2 code-review converter: 2-col diff, severity-tagged margin annotations, WCAG-1.4.1 badges, named reviewer footer), md-document (v2.10.1 long-form: sticky TOC, scrollspy, search, code-copy, Prism autoloader), markdown-html-orchestrator (v2.10.0 context: fork; deterministic doc-type classifier), and design-system (v2.10.0 onboarding wizard; WCAG-AA 12-token palette). 15 stdlib-only Python tools, 15 references, 4 template assets. Inspired by Thariq Shihipar's Claude Code HTML output essay.

5 skills · 6 commands · 1 agent

Enterprise / cross-functional Research Operations domain — the managed counterpart to the academic research/ domain. v2.9.0 ships 5 skills: orchestrator (context: fork), clinical-research (protocol synopsis, endpoint selection, sample-size/power for means/proportions/survival, phase-gate feasibility), research-finance (R&D budgeting with F&A split, burn/runway, capitalize-vs-expense routing, portfolio ROI), market-research (TAM/SAM/SOM top-down and bottoms-up, survey sampling with FPC, Kotler segmentation), and product-research (goal-matched study design, method-based saturation, insight synthesis flagging single-source anecdotes). Hard rules: outputs are estimates routed to a named clinical or finance owner, market sizes show method + assumptions, product insights require recurrence across independent participants. 24 stdlib Python tools, 12 reference docs. Distinct from ra-qm-team, finance, research/grants, product-team, and marketing-skill.

5 skills · 6 commands · 1 agent

Multi-agent collaboration — spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any task that benefits from diverse solutions. 7 slash commands (/hub:hub-init, /hub:spawn, /hub:hub-status, /hub:eval, /hub:merge, /hub:board, /hub:run), agent templates, DAG-based orchestration, LLM judge mode, message board coordination.

8 skills · 1 agent

A second brain for Claude Code + Obsidian inspired by Karpathy's LLM Wiki gist. Turn any LLM CLI into a disciplined wiki maintainer: incrementally ingest sources into a persistent, interlinked markdown vault; update entity/concept/source pages; flag contradictions; maintain index and append-only log. Knowledge compounds instead of being re-derived by RAG on every query. Ships 3 sub-agents (wiki-ingestor, wiki-librarian, wiki-linter), 5 slash commands (/wiki-init, /wiki-ingest, /wiki-query, /wiki-lint, /wiki-log), 8 Python tools (stdlib only: init_vault, ingest_source, update_index, append_log, wiki_search BM25, lint_wiki, graph_analyzer, export_marp), 8 reference docs, full vault templates (CLAUDE.md, AGENTS.md, cursorrules, 5 page templates), and a worked example vault. Cross-tool compatible with Claude Code, Codex CLI, Cursor, Antigravity, OpenCode, and Gemini CLI.

1 skill · 5 commands · 3 agents

Curate auto-memory, promote learnings to CLAUDE.md and rules, extract patterns into skills. Ships 5 slash commands (/si:memory-review, /si:promote, /si:extract, /si:memory-status, /si:remember) and 2 sub-agents (memory-analyst, skill-extractor).

6 skills · 2 agents · hooks

Autonomous experiment loop — optimize any file by a measurable metric. 5 slash commands (/ar:setup, /ar:run, /ar:loop, /ar:ar-status, /ar:ar-resume), 8 built-in evaluators, configurable loop intervals (10min to monthly).

6 skills · 1 agent

Adversarial thinking partner for founders and executives. Stress-tests plans, prepares for board meetings, navigates hard calls, runs postmortems. 5 sub-skills with slash commands.

6 skills · 1 agent

Email-workflow skill pair: inbox-setup builds your taxonomy/KB; inbox-triage classifies + drafts (drafts-only, never auto-send). KB-file contract between them. Path-B from megaprompts 06+07.

2 skills · 2 commands · 2 agents

5 business & growth skills: customer success manager, sales engineer, revenue operations, contract & proposal writer.

5 skills

Study companion for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org. Twenty chapter files, a glossary, patterns and a cheatsheet index the whole book, and a delta reference dates it against 2026 practice with per-claim confidence levels: double descent qualifying the U-curve, AdamW splitting weight decay from L2, transformers displacing Chapter 10's recurrence, diffusion growing out of Chapter 18's score matching. Four stdlib tools make it executable — a prerequisite-closed reading-path planner that refuses goals the book does not cover, a training diagnostic running Chapter 11's rules in priority order so a NaN is never reported as overfitting, a capacity planner that ranks 'shrink the model' last when overparameterized, and a parameter/FLOP/activation-memory calculator that refuses a stack whose shapes do not connect. A companion, not a compilation: the book is copyrighted, so nothing here reproduces its text.

1 skill · 3 commands · 1 agent

Compact the current conversation into a handoff document for another agent to pick up. Configurable save location, redaction enforcement, SessionStart auto-load + SessionEnd reminder, self-check fidelity script, --refresh flag, mtime-guarded cleanup. Inspired by Matt Pocock's handoff (MIT).

1 skill · 2 commands · 1 agent · hooks

A four-tier memory ladder for Claude Code where promotion is earned by recurrence, not asserted by confidence. L0 raw transcripts are never injected; L1 candidate atoms are gitignored and recalled on lexical relevance per prompt; L2 project context loads each session start; L3 stable persona is always loaded. L1 to L2 needs three distinct sessions spanning two distinct calendar days (a stated claim needs two; a verified claim is the only single-observation path); L2 to L3 needs two projects and thirty days. Two gates refuse rather than guess: a claim altered by the redaction pass never promotes on evidence alone, and a contradicted claim freezes until a human resolves it. Three hooks run the loop unattended and every one fails open. Nothing reaches a committed CLAUDE.md without an explicit human adopt. Ships 5 stdlib scripts, 3 hooks, a cs-memory-curator agent, /cs:memory, a JSON schema, and a 69-check validator. Concept from TencentCloud/TencentDB-Agent-Memory (MIT); no upstream code included.

1 skill · 1 command · 1 agent · hooks

Marc Andreessen-mode decision and productivity skill. Market-first operator that pressure-tests ventures/ideas/features/bets (market > team > product; product/market fit is the only milestone; bias to build) and runs the 3x5-card + Anti-Todo routine. Fixed anti-sycophancy operating prompt: counterargument first, no disclaimers, explicit confidence levels, no capitulation. Issues hard verdicts backed by deterministic stdlib tools.

1 skill · 2 commands · 1 agent

Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent skills: a master SKILL.md with core frameworks and a topic index, on-demand chapter files, a glossary, a patterns file, and a decision cheatsheet. Ships 4 stdlib-only tools (multi-format extractor with invisible-Unicode sanitization, four-family generated-skill validator covering frontmatter/safety/budget/index, pre- and post-flight token budget estimator with a worth-converting verdict, and a plugin emitter that wraps a compiled skill as an installable claude-skills package behind a rights gate), 5 references citing 7-8 sources each, a cs-book-to-skill agent, and /cs:book-to-skill + /cs:book-to-plugin commands. Derived from virgiliojr94/book-to-skill (MIT).

1 skill · 2 commands · 1 agent

Deep Work day planner. Classifies tasks deep vs shallow with a shallow-work budget verdict (plus the recent-graduate forcing question), builds a time-blocked schedule (deep blocks of 90+ minutes first, shallow batched, buffers, refuses more than 4 hours of deep demand), and logs focus sessions against a weekly deep-hours target with streaks. Fills the time/attention-management gap from audit/productivity-2026-07.

1 skill · 2 commands · 1 agent

3 finance skills: financial analyst (ratio analysis, DCF valuation, budgeting, forecasting), SaaS metrics coach (ARR, MRR, churn, CAC, LTV, NRR, Quick Ratio, projections), and business investment advisor. 7 Python automation tools.

4 skills

Meeting discipline. Cost-gates every meeting before it exists (MEET / ASYNC / NOT-READY verdicts with real dollar cost incl. optional refocus overhead), builds timeboxed agendas that refuse topics without a desired outcome (decision topics first), and extracts owned action items from raw notes with ORPHAN / NO-DUE flags. Fills the meeting-hygiene gap from audit/productivity-2026-07.

1 skill · 2 commands · 1 agent

Engineer an agent's forgetting, not just its remembering. Four deterministic stdlib scripts implement the four lenses of agent memory: a cost profiler that splits construction from query spend and reports cost per correct answer (construction energy exceeds total query energy across 300 queries in the Stanford characterization); an architecture picker that scores the four paradigm families — long-context, flat RAG, structure-augmented RAG, agentic — disqualifies on hard constraints, names the cost the winning choice makes you pay, and refuses to pick when the top two tie; a density auditor that classifies every record in a memory directory or JSONL export as FACT / SKILL / LOG / PROSE, finds near-duplicates, and flags stale wording; and a forgetting-policy linter that fails any design with no forgetting rule. Ships cs-memory-engineer agent, /cs:memory-engineering and /cs:forgetting-audit commands, 4 references, and a seven-question forcing worksheet.

1 skill · 2 commands · 1 agent

Turn any domain folder of skills into a bounded agentic loop: a manifest builder inventories a domain's skills/tools/checks, a goal compiler turns a goal into a verifiable task plan (refusing vague goals with forcing questions), and a JSON-backed loop controller drives execute->verify->close with retry caps, controller-run verification (no verification theater), human escalation on exhausted budgets, and a close gate that refuses while any task is unverified or unwaived. Ships 3 stdlib Python tools, 18 committed per-domain harness manifests + JSON schema, 3 references citing the 2024-2026 agent-harness canon (Anthropic long-running harnesses, verifier's law, SWE-agent, Ralph loop, Cognition), harness-runner agent + /cs:harness command. Use when an agent or subagent should pick up a goal, define its tasks, complete and verify them, and close the loop.

1 skill · 1 command · 1 agent

Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of versionable .md files with a frontmatter type, links forming a graph, and reserved index.md/log.md, readable by humans and agents alike. Guides the founder through a 12-phase interview (foundation, strategy, market, financial, sales, marketing, product, operations, tech, people, legal, governance), one phase at a time, and generates conformant markdown concepts. 3 stdlib tools: scaffold_bundle (bundle scaffold), okf_linter (validates type/reserved files/links), index_generator (regenerates the index.md files). Standalone-installable; also bundled in c-level-skills. In English.

1 skill · 1 command · 1 agent

Brain-dump-to-action workspace skill. Routes vague captures into discoverable actions via classify→cluster→connect→clarify intake. Path-B from megaprompt 05.

1 skill · 1 command · 1 agent

Ultra-compressed communication mode. Cuts token usage 20-50% (75% upper bound) by dropping filler, articles, pleasantries, and hedging while keeping full technical accuracy. Derived from Matt Pocock's MIT-licensed caveman with: (1) 3 stdlib Python tools (deterministic compressor, token-savings estimator with $/Mtok cost extrapolation, lint that detects banned vocab with code-block + exception-zone whitelisting), (2) 3 references citing 7-8 sources (compression principles, when caveman backfires, companion tooling), (3) cs-caveman-mode persona agent + /cs:caveman slash command. Matt's persistence rules + auto-clarity exception preserved verbatim per MIT.

1 skill · 1 command · 1 agent

Personal Claude power-user coach. Delivers a personalized, ranked cheat-code glossary on first activation, then surfaces at most one tip per turn when it would genuinely improve the next attempt. Ships cheat-codes glossary, coaching-rules decision tree, three stdlib Python tools, cs-claude-coach agent, and /cs:claude-coach command.

1 skill · 1 command · 1 agent

Disciplined multi-source meta-research for high-stakes questions — the heavyweight alternative to the fast research router. 9-phase pipeline (reframe into falsifiable hypotheses, plan, capability discovery, parallel sub-agent fan-out, score & triangulate, synthesize + adversarial pass, verify, refresh targets). Triangulates every thesis against >=3 independent differently-typed sources; per-source files with verbatim quotes; never fabricates a citation. Auditable, reusable folder + delta-update refresh protocol. Contributed via PR #851.

1 skill · 1 command · 1 agent

Decision-grade entity research. Due-diligence/background-check/competitor-prep with tier-weighted verdict + citation tracker. Research-pack convention. Path-B from megaprompt 02.

1 skill · 1 command · 1 agent

NIH grant-funding intelligence skill. RePORTER/NOSI/study-section navigation, R01/R21/K-award strategy. Research-pack convention. Path-B from megaprompt 11.

1 skill · 1 command · 1 agent

Relentless plan-and-design interrogator. Walks the decision tree one branch at a time, asking forcing questions sequentially with recommended answers. Explores codebase before asking. Derived from Matt Pocock's MIT-licensed grill-me with: (1) 3 stdlib Python tools (decision-tree extractor across 6 branch kinds, question generator with dependency-aware ordering, JSON-backed session tracker for multi-day grills), (2) 3 references citing 7-8 sources (6 forcing-question patterns, when to stop grilling, companion tooling), (3) cs-grill-master persona agent + /cs:grill-me slash command. Matt's relentless one-at-a-time interview discipline preserved verbatim per MIT.

1 skill · 1 command · 1 agent

Docs-anchored grilling session — interrogates a plan against the project's existing language (CONTEXT.md) and recorded decisions (docs/adr/), updating those files inline as terminology and decisions crystallise. Derived from Matt Pocock's MIT-licensed grill-with-docs with stdlib validators (CONTEXT.md linter, ADR scanner, glossary-code consistency), reference docs, cs-grill-with-docs agent, and /cs:grill-with-docs command.

1 skill · 1 command · 1 agent

Conversation-handoff document generator. Compacts the current session into a markdown handoff for a fresh agent — references existing artifacts (PRDs, plans, ADRs, issues, commits) by path/URL instead of duplicating them. Derived from Matt Pocock's MIT-licensed handoff with: (1) 3 stdlib Python tools (template generator tailored to 5 next-session emphases, artifact deduplicator across 5 categories of duplication, skill recommender matching content to 14 skills in this repo), (2) 4 references citing 7-8 sources (handoff structure, deduplication discipline, next-session skill matching, companion tooling), (3) cs-handoff-author persona agent + /cs:handoff slash command. Matt's no-duplication discipline + mktemp convention preserved verbatim per MIT.

1 skill · 1 command · 1 agent

Human-verification gate for an agent loop: builds a single-file review page (the page itself makes no network request; a reviewed HTML artifact's own https: assets still load), collects batched feedback as structured batch.v1 data instead of chat prose, and refuses to close while a BLOCKER is open, the reviewer is unnamed, or nobody has reviewed. Non-blocking, headless-guarded, round-capped. Stdlib-only.

1 skill · 1 command · 1 agent

Active coding discipline enforcer based on Karpathy's 4 principles: surface assumptions, simplify, make surgical changes, define verifiable goals. Ships 4 Python tools (complexity_checker, diff_surgeon, assumption_linter, goal_verifier), a review agent, /karpathy-check command, and pre-commit hook. All stdlib-only.

1 skill · 1 command · 1 agent

Single-file HTML landing-page generator with 4 design styles, brand palette validation, GSAP animation patterns, kebab-slug URL hygiene. Path-B from megaprompt 04.

1 skill · 1 command · 1 agent

Academic literature orientation skill. PICO/SPIDER frameworks, systematic review structure, 8-section DOCX guide. Research-pack convention. Path-B from megaprompt 09.

1 skill · 1 command · 1 agent

Google NotebookLM browser-automation skill. 4 actions (read/extract, add-source, Studio outputs, create notebook). Screenshot-first + find-before-click + fire-and-notify async discipline. Path-B from megaprompt 03.

1 skill · 1 command · 1 agent

Patent prior-art + IP landscape skill. FTO/novelty/family-resolver via 3-pass Jaccard heuristic. Research-pack convention. Path-B from megaprompt 12.

1 skill · 1 command · 1 agent

Multi-source recency research. Reddit/HN/X/web sentiment + trending. Research-pack convention (1 q/sec, three-count tracking). Path-B from megaprompt 01.

1 skill · 1 command · 1 agent

Light-prompt reflection skill. Single forcing question + structured journal capture. Path-B sibling of capture from megaprompt 08.

1 skill · 1 command · 1 agent

Research orchestrator (hybrid router + fallback). Deterministic SIGNALS classification routes to 6 specialists (pulse/litreview/grants/dossier/patent/syllabus) at >=2 signals, else runs own 8-step plan-decompose-search-synthesize-cite fallback. Routing transparency mandatory. Path-B from megaprompt 13.

1 skill · 1 command · 1 agent

Pressure-test a business idea before you build it. Convenes a 5-angle adversarial panel — The Critic (what kills this?), The Champion (the 10x upside?), The Analyst (does the logic hold?), The Investigator (what does the market say?), The Customer (would I actually pay?) — fired in parallel as independent reviewers, then a Judge synthesizes one GO / RESHAPE / KILL verdict with explicit confidence and the cheapest 48-hour test to de-risk it. Never averages the scores: a weighted synthesizer with demand/fatal-flaw/logic veto gates produces the call, backed by deterministic stdlib tools.

1 skill · 1 command · 1 agent

Grade an agent setup from real conversation history — a rebuild of warpdotdev/common-skills' skill-doctor (MIT). Harvests recent local Claude Code and Codex sessions scoped to one repo, condenses and secret-redacts transcripts (12-pattern redactor, chmod-0600 artifacts, nothing uploaded), has the agent judge each transcript against two verbatim-preserved rubrics (efficiency, code quality — labels only), then runs a deterministic aggregation gate that derives every number from the label tables, refuses scores for unsampled sessions and suggestions that cite no scored session, and renders one self-contained zero-JS HTML report (dark-mode, print-to-PDF). Proposed skill edits stay staged as diffs until an explicit per-skill yes; zero suggestions is a valid, reportable success. Ships cs-skill-doctor agent, /cs:skill-doctor command, 3 stdlib tools, 3 references citing 7 sources each.

1 skill · 1 command · 1 agent

Nightly offline self-evolution for this repo's Claude agent: harvests past Claude Code sessions (read-only), mines recurring tasks, replays them offline on your own API budget, and consolidates learnings into validated CLAUDE.md memory and SKILL.md skills behind a held-out gate, staged for review (never auto-applied). Verbatim vendor of microsoft/SkillOpt's stdlib-only skillopt_sleep engine + Claude Code plugin surface (MIT).

1 skill · 1 command · hooks

Knowledge base compiled from OpenAI's Spinning Up in Deep RL (MIT, Joshua Achiam) by engineering/book-to-skill. A resident core carries the RL optimization problem, the model-free taxonomy, the policy-gradient template with its five valid weights, the safe-step family (VPG to TRPO to PPO) and the overestimation family (DDPG to TD3 and SAC); 20 on-demand chapters cover key concepts and MDPs, the algorithm taxonomy and model bias, the policy gradient derivation with the log-derivative trick and EGLP lemma, Achiam's researcher essay, the key-papers topic map, the exercises including the silent DDPG broadcasting bug, the benchmark parity disclosure, one chapter per algorithm, and the logger/MPI/ExperimentGrid utilities. Ships a glossary, a patterns file with 16 techniques, a decision cheatsheet with thresholds, a cs-spinning-up-deep-rl agent and /cs:spinning-up-deep-rl. Structured study notes, not a reproduction of the source.

1 skill · 1 command · 1 agent

Course supplementary-reading skill. Topic-grouper + bundled Node.js DOCX generator for syllabus-anchored reading lists. Research-pack convention. Path-B from megaprompt 10.

1 skill · 1 command · 1 agent

A universal scraping skill with intelligent routing, token budget tracking, and quota awareness. Supports Firecrawl (BYOK, free-tier compatible) and local Python extraction via requests/BeautifulSoup/pandas.

1 skill · 1 command · 1 agent

GTD weekly-review loop. Scans the workspace for open loops (unchecked boxes, TODO/FIXME, stale files), walks the three-phase GET CLEAR / GET CURRENT / GET CREATIVE checklist with a refusal gate (review is never COMPLETE while a mandatory GET CURRENT step is missing), and audits commitments for stalled / no-next-action / someday candidates with a 0-100 health score. Fills the periodic-review gap from audit/productivity-2026-07.

1 skill · 1 command · 1 agent

Workflow-builder skill: design and write deterministic multi-agent workflow scripts (.js files in .claude/workflows/) for Claude Code's Workflow tool (CLAUDE_CODE_WORKFLOWS=1, /workflows). Every session opens with an intake question set; when the user is vague, a stdlib recommendation engine infers and proposes a topology with rationale instead of stalling. Ships 3 stdlib Python tools (intake recommendation engine, .js validator enforcing pure-literal-meta / no-non-determinism / guarded-loop / parallel-thunk rules, topology scaffolder), 3 references citing 7-8 authoritative sources each (API surface, orchestration patterns, decision + intake guide), templates + a runnable example, cs-workflow-architect persona agent + /cs:workflow-build slash command. Use when building, scaffolding, or running a custom Claude Code workflow or orchestrating sub-agents (fan-out, pipeline, loop, judge-panel).

1 skill · 1 command · 1 agent

Skill-author skill: create new agent skills with proper structure, progressive disclosure, and bundled resources. Derived from Matt Pocock's MIT-licensed write-a-skill with: (1) 3 stdlib Python validation tools (description validator, structure validator, review-checklist runner — all enforcing Matt's 6-item checklist), (2) 4 references citing 7-8 authoritative sources each (progressive disclosure principles, description design patterns, quality gates, companion tooling), (3) cs-skill-author persona agent + /cs:write-a-skill slash command. Matt's voice and 3-phase workflow (Gather → Draft → Review) preserved verbatim per MIT.

1 skill · 1 command · 1 agent

Convert a rambling description of a desired outcome into one polished, autonomous /goal prompt ready to paste into a fresh session. Extracts deliverable/quantity/stakes/tools/destination, asks at most one question batch, verifies every named resource against the live environment, writes a 150-350 word prose prompt with the seven-part anatomy, and self-checks six binary criteria before delivering. The output is a single copy-paste prompt, never the build itself.

1 skill · 1 command

PreToolUse security reminder hook for Claude Code. Catches 12 common security anti-patterns in Edit/Write/MultiEdit operations BEFORE they happen — command injection (exec, os.system, subprocess shell=True), XSS (innerHTML, dangerouslySetInnerHTML, document.write), SQL injection (f-string queries, .format), unsafe deserialization (pickle, yaml.unsafe_load), code injection (eval, new Function), and GitHub Actions workflow injection. Session-state caching prevents duplicate warnings; 30-day auto-cleanup. Disable per-session with ENABLE_SECURITY_REMINDER=0. Ported from David Dworken at Anthropic.

1 skill · hooks

WCAG 2.2 accessibility audit and fix for React, Next.js, Vue, Angular, Svelte, and HTML. Static scanner detecting 20+ violation types, contrast checker with suggest mode, framework-specific fix patterns, /a11y-audit slash command.

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Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO (which optimizes for search rankings), AEO optimizes for citation in LLM-generated responses. 3 stdlib Python tools (aeo_audit, aeo_optimizer, citation_tracker), 3 references citing 8 sources each, industry-aware thresholds for 8 industries (saas/healthcare/finance/legal/ecommerce/b2b/media/education). Ported from alirezarezvani/aeo-box.

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Agile product ownership for backlog management and sprint execution. INVEST-compliant user story generation, acceptance criteria patterns (Given/When/Then, rule-based, checklist), epic breakdown with 5 split techniques, sprint planning with velocity-based capacity math, and weighted backlog prioritization. Includes user_story_generator Python tool and 2 reference guides.

1 skill

Master Apple's Human Interface Guidelines (HIG) with focus on 2026 Liquid Glass aesthetics. Design and audit iOS, macOS, and visionOS apps for full compliance and premium feel. Includes hig_checker Python tool for tap targets and contrast.

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Self-Mirror consciousness loop for human-like AI responses. Adds inner dialogue (Self → Mirror → Conscious Response) to make AI output feel authentic, not robotic. Zero dependencies — pure prompt technique.

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Business investment analysis and capital allocation advisor. Evaluates equipment, real estate, new-business, hiring, and technology investments with ROI, IRR, NPV, payback period, build-vs-buy, lease-vs-buy, and vendor evaluation frameworks for allocating limited budget.

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End-to-end chaos engineering discipline: design experiments with hypothesis + steady-state metric + blast radius + abort criteria, calculate risk score against error budget, and generate blameless postmortems. 3 stdlib Python tools (experiment_designer, blast_radius_calculator, experiment_postmortem), 4 references on chaos principles + experiment design + 7-attack taxonomy + tooling landscape (Chaos Toolkit/Mesh/Litmus/Gremlin/AWS FIS/DIY), templates, and /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (chaos targets).

1 skill

Chief AI Officer advisory for startups: model build-vs-buy calculator (API vs fine-tune vs build with 3-year TCO across 6 paths + breakeven that balances economics with practical feasibility), AI risk classifier (EU AI Act tier with 7 Article citations + US state patchwork: NYC LL 144, CO AI Act, IL HB 53, CA SB 1001, IL BIPA + industry overlays for FDA AI/ML, CFPB Circular 2023-03, NYDFS Reg 23, NAIC, ECOA, Fed SR 11-7), AI cost economics (API vs self-hosted breakeven with 2026 pricing across A100/H100, utilization reality, hidden costs). 4 in-depth references each citing 5+ authoritative sources. Standalone-installable; also bundled in c-level-skills. Strategic only — does not duplicate engineering AI/ML skills.

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Chief Customer Officer advisory: retention decomposition analyzer (honest GRR vs NRR; 7-category churn taxonomy with preventable% scoring), customer segmentation designer (4-tier framework, ICP fit scoring across 7 weighted signals, kill list + upgrade candidates), CS coverage calculator (pooled vs named CSM ratio math + 12-month hiring plan with quarterly sequencing). 4 in-depth references each citing 5+ authoritative sources. Standalone-installable; also bundled in c-level-skills. Strategic only — does not duplicate business-growth tactical CS skills.

1 skill

Chief Data Officer advisory for startups: AI training data audit (origin × class × use-case matrix with GDPR Art. 6 + EU AI Act citations), data product strategy picker (warehouse vs lakehouse vs mesh + 6-layer build-vs-buy + 12-month sequencing), data asset valuator (strategic value 0-10 + M&A multiplier with carve-out penalties + 3 ranked productization paths). 4 references answering one decision each: training rights, data product strategy, customer-data-as-asset, data team org evolution. Standalone-installable; also bundled in c-level-skills. Strategic only — does not duplicate engineering data skills.

1 skill

Reverse-engineer any codebase into a complete PRD. Frontend (React, Vue, Angular, Next.js), backend (NestJS, Django, Express, FastAPI), and fullstack. 2 Python scripts (codebase_analyzer, prd_scaffolder), 2 reference guides, /code-to-prd slash command.

1 skill

Create CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. 10 developer personas, all CodeTour step types, SMIG description formula.

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Assisted retrospective: after a session, calibrates what Claude contributed vs what the developer drove. LLM-assessed 4-frame analysis with explicit rubric, zero dependencies.

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EU AI Act (Regulation (EU) 2024/1689) operational compliance specialist: AI system risk classifier (Articles 5/6/50 + Annex III), conformity assessment planner (Article 43 + Annex IV checklist), and obligation tracker (provider/deployer/importer/distributor + GPAI Articles 51-55). Article-level references and cross-framework mapping to ISO 42001, NIST AI RMF, GDPR. Stdlib-only.

1 skill

ISO/IEC 42001:2023 AI Management System (AIMS) specialist: AIMS gap analyzer (Clauses 4-10 coverage + remediation priority), AI risk register builder (Annex A 38 controls per ISO 23894), and AIMS audit scheduler (Clause 9.2 cadence + auditor independence). Cross-framework mapping to EU AI Act, NIST AI RMF, ISO 23894. Stdlib-only.

1 skill

Audit datasets for completeness, consistency, accuracy, and validity. 3 stdlib-only Python tools: data profiler with DQS scoring, missing value analyzer with MCAR/MAR/MNAR classification, and multi-method outlier detector.

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Evidence-first reading of supplied documents. Five modes (quick/deep/map/feynman/book), claim-reason-evidence decomposition, confidence labels, evidence ledger, knowledge maps, Feynman teach-back.

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Create polished demo videos from screenshots and scene descriptions. Orchestrates playwright, ffmpeg, and edge-tts with story structure, scene design system, and narration guidance.

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Docker and container development — Dockerfile optimization, docker-compose orchestration, multi-stage builds, security hardening, and CI/CD container pipelines.

1 skill

End-to-end feature-flag discipline: classify, ship, ramp, retire. Detects stale flags as debt, generates phased rollout plans (ring/linear/log/cohort), and audits every flag for a documented kill switch. 3 stdlib Python tools, 4 references on flag taxonomy + provider trade-offs (LaunchDarkly/GrowthBook/Statsig/Unleash/Flipt/DIY) + rollout strategies + lifecycle. /flag-cleanup slash command. Cross-tool compatible.

1 skill

General Counsel advisory for startups: contract risk scanner (12 founder-killer patterns: auto-renew traps, uncapped indemnity, vague IP, MFN pricing, missing DPA, one-sided venue, broad non-solicit, perpetual license-back, etc.) and term sheet analyzer (0-100 founder-friendliness across 12 dimensions). 3 in-depth references: contracts playbook (7 startup contract types), IP + regulatory landscape mapping (HIPAA, GDPR, FDA, fintech, EU AI Act, SOC 2 → ISO sequencing), term sheet decoder (full glossary + founder-friendly defaults). Standalone-installable; also bundled in c-level-skills. Stdlib-only. NOT a substitute for licensed counsel.

1 skill

Google Workspace administration via the gws CLI. Install, authenticate, and automate Gmail, Drive, Sheets, Calendar, Docs, Chat, and Tasks. 5 Python tools, 3 reference guides, 43 built-in recipes, 10 persona bundles.

1 skill

Helm chart development — chart scaffolding, values design, template patterns, dependency management, and Kubernetes deployment strategies.

1 skill

End-to-end Kubernetes Operator discipline: CRD design, reconcile-loop patterns, and OperatorHub Capability Levels. Ships CRD validator, reconcile-loop linter, and capability auditor (3 stdlib Python tools), 4 references on the operator pattern + CRD design + reconcile patterns + framework comparison (controller-runtime/kubebuilder/operator-sdk/metacontroller/KOPF), CRD + Go controller skeletons, and /operator-audit slash command. NOT a generic k8s skill — specifically the Operator pattern.

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Cut LLM API spend via model routing, prompt caching, prompt compression, and per-feature cost observability. Use when AI costs are too high, choosing between models, or launching an AI feature without cost architecture. NOT for RAG design or prompt quality (separate skills).

1 skill

Manage prompts in production at scale: prompt versioning, A/B testing, prompt registries, regression prevention, and eval pipelines for production AI features. NOT for writing individual prompts, RAG design, or cost reduction (separate skills).

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Structured research summarization — summarize academic papers, market research, user interviews, and competitive analysis into actionable insights.

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End-to-end SLO/SLI/error-budget discipline per Google SRE Workbook. Ships SLO designer (refuses to render without required fields), error-budget calculator with multi-window burn-rate alert thresholds (PromQL-shaped), and SLO reviewer that catches the 7 common bugs. 4 references on principles + SLI design + error budget math + composition with feature-flags-architect/chaos-engineering/kubernetes-operator. Asset templates for SLO YAML and error budget policy. /slo-design slash command. NOT a generic observability skill.

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Snowflake SQL, data pipelines (Dynamic Tables, Streams+Tasks), Cortex AI functions, Snowpark Python, and dbt integration. Includes query helper script, reference guides, and troubleshooting.

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Hypothesis testing, A/B experiment analysis, sample size calculation, and confidence intervals. 3 stdlib-only Python tools: Z-test/t-test/chi-square with effect sizes, sample size calculator with power tradeoffs, and Wilson score confidence intervals.

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CEFR-leveled Swedish-learning mentor: two-question placement probe, listening-first learning paths, vetted YouTube/podcast catalog (SFI, Radio Sweden pa latt svenska, Klartext), never-invent-a-URL rule.

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Terraform infrastructure-as-code — module design patterns, state management, provider configuration, CI/CD integration, and multi-environment strategies.

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Video content strategy: video scripts, YouTube channel optimization and SEO, short-form video pipelines (Reels, TikTok, Shorts), and repurposing long-form content into video. NOT for written blog content or caption-only social posts (separate skills).

1 skill

VP of Engineering advisory: delivery throughput analyzer (DORA 4 metrics + cycle-time bottleneck identification with typical fixes per stage), engineering hiring funnel calculator (7-stage conversion + pipeline gap + weakest-stage fixes from sourcing to offer-accept), engineering team structure designer (squad/tribe model + manager-trigger + director-trigger + span-of-control). 4 in-depth references citing DORA / Spotify / Conway / Google SRE / Larson / Fournier. Standalone-installable; also bundled in c-level-skills. NOT a CTO skill — VPE owns how the team ships; CTO owns what to build.

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YouTube transcripts, video search, channel browsing, playlist extraction, and upload monitoring via TranscriptAPI. BYOK — 100 free credits. OSS fallbacks: youtube-transcript-api / yt-dlp.

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A disciplined coding pipeline that grounds code in verified structure before a line is written: Discuss -> Map -> Decompose -> Execute -> Verify, with a lazy-senior-dev YAGNI ladder that deletes unnecessary code first. No invented APIs, no assumed imports, no placeholder code. Opt-in for high-stakes, complex, or multi-file work; not for trivial edits. Synthesizes four MIT/open-source projects (Ralph atomic loop, GSD Core context engineering, Graphify KNOWN/INFERRED/UNKNOWN mapping, Ponytail lazy-senior hierarchy). Contributed via PR #854.

1 skill