fs-investment-banking

FEDERATED - the claims inside are not verified by this repo. 501 engineering-grade trading skills - point-in-time backtest schemas, universe look-ahead, alt-data availability lag, ML against transaction costs, adjusted-vs-unadjusted prices, backtest determinism and audit trails, broker idempotency and failover, exchange FIX specs (ASX, B3, Bursa, BIST, Cboe), regulatory gates and a key-scope audit skill. Its README claims 458 of 501 cite a primary source; it is clearly LLM-generated at scale and the depth is unverified. Upstream splits these into per-domain plugins, but its root manifest exposes all 501 at once - roughly 25x the discovery budget, which is yours to spend since it installs disabled. No credentials in the skills; nothing executes. Installs disabled.

200 skills

FEDERATED - the claims inside are not verified by this repo. FTShare's official one-endpoint-per-skill data catalogue for the Chinese market: A/HK/US quotes and K-lines, 可转债 including SZSE declaration snapshots, ETF PCF and IOPV, 龙虎榜, block trades, margin balances, executive holdings, the ChinaBond yield curve, the CPI/PPI/PMI/LPR/M2/credit macro series and news-sentiment factors. FTSHARE_API_KEY in the environment (a free tier exists per the launch article); read-only. Be deliberate: 215 sub-skills is roughly 10x the ~20-skill discovery budget, so treat it as a catalogue to enable for a session, not a standing install - it arrives disabled and the budget is yours to spend. Installs disabled.

200 skills

FEDERATED - the claims inside are not verified by this repo. The deepest IFRS/GAAP pack in this sweep that also validates cleanly: IFRS 9 expected credit loss, IFRS 16 leases, IAS 12 deferred tax, revenue recognition, consolidation, SOX, forensic accounting, insurance reserving, WACC, LBO, treasury and Basel banking compliance, with an eval harness in the repo. Outside this library's quant core and overlapping the banking-regulatory entry on Basel and IFRS 9. Optional Stripe/Plaid connectors; nothing executes. Installs disabled.

48 skills · 52 commands

FEDERATED - the claims inside are not verified by this repo. HKUDS' 33k-star trading agent, taken for its skill tree alone - the richest algorithm content this sweep found: the Kakushadze 101, GTJA 191 and Qlib 158 alpha zoos, factor IC/IR research, execution models (square-root impact, VWAP/TWAP), microstructure (VPIN, Kyle's lambda, Amihud), SABR and local-vol options, convertible bonds, credit, Brinson attribution, GARCH/ADF and a Pine/vnpy exporter. The skills are coupled to the app's data router and Python toolkit, so test them standalone before trusting them; data keys go in a .env, and live orders are reachable only through a separate gated connector with a kill switch, not from these skills. 90 skills is about 4.5x the discovery budget. Installs disabled.

91 skills

FEDERATED - the claims inside are not verified by this repo. The closest structural peer to fin-libraries found in the wild - 82 one-library skills in Chinese - and the only pack anywhere in this sweep with actuarial and structured-credit content: MlFinLab information bars and fractional differencing, arch/GARCH, alphalens, bt/backtrader/nautilus/qlib/LEAN, QuantLib and FinancePy day counts and schedules, XVA (CVA/DVA/FVA, SIMM), chainladder loss reserving, IFRS 9 ECL, credit scorecards and transition matrices, ABS waterfalls, Smith-Wilson EIOPA curves. Depth is unverified and the author has one star; the easytrader and nautilus skills document live-broker paths but nothing executes by default. 82 skills is roughly 4x the discovery budget. Installs disabled.

82 skills

FEDERATED - the claims inside are not verified by this repo. The maintained superset of geeksfino-finskills, 107 skills across China, Hong Kong and US directories: A+H premium, block deals, 龙虎榜, pledge risk, goodwill, 解禁 unlocks, margin risk, factor crowding, event studies, valuation regimes, and HK southbound, currency and liquidity monitors. Free data sources; nothing executes. Two caveats - it has been idle since February 2026, and 107 skills is roughly 5x the discovery budget, which is yours to spend since it installs disabled. Installs disabled.

79 skills

Agent runtimes — local WASM-sandboxed agents (rvagent) + Anthropic Claude Managed Agents (cloud); one interface, local-vs-cloud backends

5 skills · 2 commands · 9 agents

Apollo GraphQL agent skills for Claude Code — Apollo Client, Server, Federation, Connectors, Router, Rover CLI, iOS, Kotlin, and the Apollo MCP server. Covers schema design, query optimization, and GraphQL best practices.

14 skills · 1 MCP server · LSP

Independent auditing for AI agents, open source. Claude discovers your setup, confirms the cost, and audits your agent against the one question other tools skip: is it doing the job it's supposed to do, given your business rules and org structure? Test any model (Anthropic, OpenAI, Gemini, Azure, Bedrock, …) graded by self, one independent judge, or a cross-vendor panel; each provider is billed to its own account via a key in your settings, never the command line. Results render as an interactive artifact (with a static-report fallback).

1 skill · hooks

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

Bundle of 12 LinkedIn marketing skills for Claude Code and Codex with verified 2026 hook formulas, comment + reply templates that earn author replies, a unified humanizer (rewrite + `--mode audit` pre-publish check, plus bundled emoji-detector, detector-spread tester, rule-explainer sub-tools), profile rewriter, content planner, employee advocacy playbook, thread monitor (warm-reply window author-reply tracking), and engager analytics (likers + commenters ICP segmentation), interviewer (Story Bank of receipts, turning points and positions).

13 skills

Strategic foresight intelligence using IFTF methodology. Two prediction modes: Soft Predict Future (Claude-native skill, instant, claude.ai + Claude Code) and Hard Predict Future (deterministic 12-step pipeline, Python-computed — Claude Code only). Both output four independent futures (Probable/Plausible/Possible/Preferable) with per-stakeholder conditional analysis. Try: Will India become the global AI leader? Will OpenAI or Anthropic win?

2 skills