Automates the user's real Chrome browser via the Browser MCP Chrome extension. Uses the user's logged-in sessions and real browser fingerprint to avoid bot detection. Use when the user needs to browse websites, fill forms, scrape data, or test web pages using their actual browser profile.
Interact with data.gouv.fr APIs — Main API (datasets, orgs, users, resources, reuses, discussions), Metrics API (usage/stats by model), Tabular API (query CSV rows by resource ID). Use when working with data.gouv.fr data, catalog, or platform features.
Minimize token waste in all bash, file, and data processing operations. ALWAYS apply these principles whenever executing commands, reading files, or processing output. This skill governs how an LLM agent interacts with the system — it applies to every task involving tool use, file reading, data processing, or shell commands. TRIGGER on any computer use whatsoever. --- # Token-Efficient Computer Use Every character of stdout returned from a tool call gets tokenized and billed. A single careless `cat` on a 2000-line JSON file costs as much as a thoughtful conversation turn. The goal isn't to memorize specific commands — it's to internalize a simple cost model: **each byte of tool output is money and context window spent**, and each tool call has fixed round-trip overhead on top of that. Two questions should precede every tool call: 1. **Can I avoid this call entirely?** If the information is already in context from a previous read or from the user, use it. 2. **If I must call, how do I minimize the bytes returned?** Filter, project, truncate, or count at the source rather than dumping raw output.
[UDS] 分析 AC 與測試的追蹤關係及覆蓋率
Fetches ALL open issues from any GitHub repository using pagination and generates a comprehensive analysis including category breakdown, age distribution, stale issues (30+ days), top discussed issues, prioritization, and detailed recommendations for triage. Handles large repositories (5000+ issues) efficiently.
This skill should be used when interacting with the beankeeper accounting system via the `bk` CLI. Use when the user asks to "record a transaction", "post an entry", "check a balance", "generate a report", "create a company", "set up accounts", "import bank statements", "set a budget", "compare budget vs actual", "reconcile entries", "verify the ledger", "export data", "attach a receipt", or any financial bookkeeping task. Also use when piping structured JSON output from `bk` into other tools or agents. --- # Beankeeper (`bk`) -- Double-Entry Accounting CLI Beankeeper is a double-entry accounting system operated entirely through the `bk` command-line interface. It stores data in a local SQLite database (optionally encrypted via SQLCipher). All output supports three formats: human-readable tables, machine-readable JSON, and CSV. ## Core Concepts - **Double-entry**: Every transaction has balanced debits and credits. Total debits always equal total credits. - **Companies**: Multi-tenant -- each company has its own chart of accounts and ledger. Specified via `--company SLUG` or `BEANKEEPER_COMPANY` env var. - **Accounts**: Five types: `asset`, `liability`, `equity`, `revenue`, `expense`. Each has a code (e.g. `1000`) and a normal balance direction (debit or credit). - **Amounts**: Always specified in **major units** (dollars, not cents) on the CLI. Stored internally as minor units (cents). Example: `2500` means $2,500.00. - **Append-only ledger**: Transactions cannot be edited or deleted after posting. Corrections are made via reversing entries. - **Idempotency**: Use `--reference KEY` with `--on-conflict skip` for safe retry of duplicate posts. For detailed accounting concepts and account types, see [`references/accounting.md`](references/accounting.md). ## Agent Integration **Always use `--json` for programmatic access.** Every JSON response uses a uniform envelope: ```json { "ok": true, "meta": { "command": "...", "company": "...", "timestamp": "..." }, "data": { ...
Triage static analysis findings, assess merit, and accept noise or irrelevant items
AI-first security auditor for Solidity smart contracts. 4-phase pipeline (recon → detection → state analysis → verification) with 101 heuristics, 15 detection modules, and 8 kill gates. Tested at 100% precision across 50 blind shadow audits.
Administer an Omni Analytics instance — manage connections, users, groups, user attributes, permissions, schedules, and schema refreshes via the Omni CLI. Use this skill whenever someone wants to manage users or groups, set up permissions on a dashboard or folder, configure user attributes, create or modify schedules, manage database connections, refresh a schema, set up access controls, provision users, or any variant of "add a user", "give access to", "set up permissions", "who has access", "configure connection", "refresh the schema", or "schedule a delivery".
Show details of a single Claude Code project by ID. Use when the user wants to inspect a specific project's metadata, cost, or directory.
Use the OfferPilot skill pack for resume optimization, China-first JD fit diagnosis, targeted resumes, and cover letters in Claude Code style repository agents. Use when the user wants structured job-application outputs or JD fit analysis from local resume and job-description files.
How to use the Soda CLI for data quality management — authentication, datasources, datasets, contracts, monitors, results, secrets, permissions, and CI/CD integration. Use when working with Soda, data quality, or the sodacli command.
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
