Interactive debugging mode that generates hypotheses, instruments code with runtime logs, and iteratively fixes bugs with human-in-the-loop verification. Only for hard-to-diagnose bugs; in those cases, remind the user that debug-mode is available, and never proactively activate this skill.
Universal legal document processor with PII anonymization. Anonymize → Work → Deanonymize. Modes: MEMO (legal analysis), REDLINE (tracked changes in contract), SUMMARY (brief overview), COMPARISON (diff two docs), BULK (up to 5 files). Supports .docx and .pdf input. Trigger for: contract review, risk analysis, compliance check, GDPR review, clause analysis, tracked changes, redline, 'anonymize', 'pii shield'. If user uploads contract/NDA/DSAR/HR doc — USE THIS SKILL. If user says 'skip pii' or 'don't anonymize' — skip anonymization and work directly.
自動標註尺寸：使用 Ray-Casting 或 BoundingBox 方法，在平面視圖中自動建立房間、走廊、MEP 設備的尺寸標註。觸發條件：使用者提到標註、尺寸、dimension、annotation、淨寬、淨高、measurement、自動標註、批次標註。工具：create_dimension_by_ray、create_dimension_by_bounding_box、get_room_info。
When the user wants to track follower growth, understand what drives new followers, or analyze audience development. Also use when the user mentions 'follower growth,' 'followers,' 'audience growth,' 'gaining followers,' 'losing followers,' 'who follows me,' or 'grow my audience.' Uses BlackTwist follower data when available. For post-level metrics, see performance-analyzer-sms. For content patterns, see content-pattern-analyzer-sms.
(colcon/ament), edits launch files (.launch.py), configures QoS or DDS, writes URDF/xacro,
Email inboxes for AI agents - create addresses, send and receive email, manage threads
State-machine driven iterative planning and execution for complex coding tasks.
Reference for how an agent's memory, filesystem, and runtime are organized. Part 1 explains the memory system — the durability hierarchy from conversation to shared library, plus auxiliary layers (soul, token ledger, time veil) and the network-topology layer that lives across stores. Part 2 is the filesystem reference — where manifests, system prompts, history, mailboxes, heartbeats, logs, signal files, and config live, with exact field-level schemas. Part 3 is the runtime anatomy — turn loop, state machine, signal consumption lifecycle, molt mechanics, and mail atomicity. Read Part 1 to understand how knowledge flows between layers; Part 2 when debugging or inspecting on-disk state; Part 3 when reasoning about *how an agent runs*.
Maximum-fidelity Python source reconstruction from Nuitka `.nbc` / `NBC/2` files produced by `nuitka_decompiler.py`. Use when the user pastes or references a `.nbc` file, an `AI_READY_NBC` bundle, sections such as `@MOD`, `@CONSTS`, `@RAW_CHUNK`, `@OPS`, `@ASM`, `@FORENSICS`, `module_code_*`, `mod_consts[N]`, or asks to rebuild Python source from a Nuitka C-compiled module. The goal is evidence-backed reconstruction, not guaranteed perfect 1:1 recovery; uncertain spans must be marked.
Convene a panel of CLI-based AI agents (Codex, Gemini) to deliberate on a question. Each agent answers independently, then you synthesize the council's verdict as chairman. Use for architecture decisions, code review, debugging hypotheses, or any question where diverse perspectives add value.
Summarizes B2B account health by analyzing usage patterns, engagement trends, risk signals, and expansion opportunities. Use for customer success reviews, renewal preparation, QBRs, or account prioritization.
Auto-discover all skills with evals in RConsortium/pharma-skills, benchmark each with vs. without skill using matched isolated sessions, and post scored results to the linked GitHub issue. Use whenever someone says "run benchmarks", "compare skill performance", "eval the skills", or wants to measure whether a skill improves output quality.
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:
