course-lecture-notes

Skills and tools that improve themselves from use: observations, evidence-gated reflection passes, evals, versions and a session-start digest

1 skill · hooks

Design GUIs people actually use: tool and mod panels, settings pages, inspection viewers, dashboards and interactive explainers, at the right density (everything needed on screen or one click away, rarer flows behind more steps, more detail on request). Layered disclosure rule, settings and explainer patterns, surface limits, a build-lint-shoot-look loop with screenshots at several widths in light and dark, and a profile for audience and taste. Use when building or reworking any GUI, panel, page, viewer or interactive demo, or when one feels too complex or too thin.

1 skill

Delegate self-contained steps to helper agents on other subscriptions (Kiro, Antigravity/agy, GitHub Copilot, Codex, another Claude Code account) through Herdr's herdr-core (hc): pick a helper by tier, launch it with a brief, act as its approval judge, collect its report, review it, clean up. Use when the person asks to offload or delegate work, when Claude's limits are tight, or when a router plan marks a step for herdr. Needs hc on PATH.

1 skill

Literature research and claim verification for any research question: frame the question and the decision it serves, search several sources in parallel (PubMed, Semantic Scholar, arXiv, OpenAlex, the web, DEVONthink when on the owner's Mac) with a reproducible search log and citation chasing, record every finding in an evidence ledger (value, units, species, preparation, source, page, verbatim quote, evidence type) before any prose, have fresh checkers re-read each cited passage, then synthesise the answer with conflicts and costed gaps. Use for parameter lookups, mechanism or state-of-the-field reviews, novelty or prior-art checks, verifying a claim or citation, and finding methods; not for writing the final paper (use research-writing).

1 skill

Run many local simulation or analysis jobs in parallel under a private-memory budget: measure each job's whole process tree (macOS footprint, Linux PSS; never RSS), admit jobs by estimates taken from measured peaks, stop and requeue the newest job above a kill line, chain dependent jobs, survive restarts and the launching agent's exit, and change budget, priorities or estimates while it runs. Use when a batch of local runs (sweeps, calibrations, simulations) must fit a machine's memory, when parallel runs need a memory estimate, or when a previous queue over- or under-used memory.

1 skill

Portable model routing as a skill for agents without the model-router mod (Copilot, Kiro, Codex, Cursor, claude.ai): plan steps by tier, get approval, run each on the cheapest model that does it well

1 skill

AGENTS.md as project instructions, by one option. Under claude-md-or-agents-md a project with no instruction files of its own gets its AGENTS.md files instead: a prompt.context hook asks $.fs.ancestors for every AGENTS.md and .claude/AGENTS.md from the filesystem root down to the working directory and hands them to the engine as project instruction files, which it renders, announces and withholds from agents exactly as it does CLAUDE.md, skipping any file the engine already loaded by import or link; a tool.call hook on Read attaches the ones under the project root as the engine attaches a nested CLAUDE.md. Under claude-md-and-agents-md every AGENTS.md is loaded beside CLAUDE.md. Under managed-only the project's and the person's instruction files are dropped and the organization's managed ones kept. Under claude-md the engine's walk stands alone. claude-md-or-agents-md is the default.

Real-time graph intelligence — personalized PageRank, streaming delta updates, witness-signed reasoning, and federation-distributable vectors

1 skill

Personalized AWS guidance built on patterns from 350,000+ startups. Get architecture, cost, and security recommendations matched to your stage, from day-one account setup to production-ready infrastructure. Migrate to AWS from Azure, GCP, or Heroku with resource discovery, cost estimates, and generated Terraform. Move OpenAI, Azure OpenAI, and Gemini code to Amazon Bedrock, and plan and prototype AI agents on AgentCore and other AWS runtimes. Includes AWS Activate credits eligibility, 60+ exclusive startup offers, and multi-account, multi-region support. Built by AWS Startup Solutions Architects.

13 skills · 1 command · 7 agents · 1 MCP server

Turn Common Room into your GTM copilot. Research accounts and contacts, prep for calls with attendee profiles and talking points, and draft personalized outreach across email, LinkedIn, and phone.

6 skills · 2 commands · 1 MCP server

Personal knowledge brain for your coding agent — hybrid search, synthesis, and durable cross-session memory, plus a curated brain-first skill set.

80 skills · 1 MCP server · hooks

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