- 📁 scripts/
- 📄 README.md
- 📄 SKILL.md
codex-session-reader
读取 Codex 的单个 session/thread;当已知 thread id 且需要查看或摘要会话内容时使用。
读取 Codex 的单个 session/thread;当已知 thread id 且需要查看或摘要会话内容时使用。
Your next session starts cold. No memory of what you built, what broke, what you decided. Every signal you write is a gift to that future session. The richer the signal, the less time re-learning.
Project-specific PR-review rules for the Condukt Elixir codebase. Focuses on command execution, cwd scoping, session restore precedence, session store safety, Mimic placement, and the repo's no-typespec convention.
Analyze llmist CLI session logs to debug failures, understand agent behavior, and diagnose issues. Use this skill whenever the user mentions session logs, asks about a recent llmist run, wants to know why an agent session failed or behaved unexpectedly, references a session by name (like "witty-raven"), asks about errors in llmist, or wants to understand what happened in a past CLI invocation. Also trigger when the user says things like "what went wrong", "check the logs", "last session", "most recent run", or "debug the agent".
Analyze higher-level patterns in Claude Code usage. Outputs (a) graphic monthly/weekly digest with metaphors — aquarium of biomes (🐋🦈🐬🐟🦐🦠), archetypes (⚙️🔬🌐🛠📝🔍🏗💬), rhythm, stack palette, DORA radar (CFR + lead time + pushes), friction (compacts/pivots/subagents); (b) per-session parquet bundles for further analysis (biome, archetype, rhythm, growth, milestones, idle gaps, subagent pyramids, compact patterns, parallelism, burst classes, topics). Use when the user asks about weekly/monthly reports, session biomes, productivity profiles, "what kind of work was done", when a session became a whale, DORA metrics, or wants drill-down view of a specific session.
Wait for CI to settle across all repos in a Polygraph session, then report results and investigate failures. USE WHEN user says "await polygraph", "wait for polygraph ci", "polygraph ci status", "check polygraph ci", "watch polygraph session", "monitor polygraph".
Debug Bright Data Scraping Browser sessions using the Browser Sessions API. Use this skill when the user encounters a Bright Data browser session error, puppeteer stack trace, failed scraper run, or asks about session bandwidth, duration, captchas, or connection issues. Also use when a Bright Data scraper produces unexpected results such as empty data, 0 items found, missing products, or fewer results than expected — session data can reveal whether the issue is network/proxy-side (blocks, captchas, redirects, timeouts) or client-side (selectors, extraction logic). Triggers on phrases like 'why did my session fail', 'debug my bright data session', 'check my scraping browser sessions', 'how much bandwidth did my scraper use', 'got 0 results', 'found 0', 'scraper returned empty', 'scraper not working', 'script didn't work', or when a Bright Data error code or brd.superproxy.io stack trace appears in the conversation. Requires BRIGHTDATA_API_KEY environment variable.
Session start context priming -- loads relevant memories from Pensyve at the beginning of a session to provide continuity across sessions. Use when switching projects or needing historical context.
Claude Code Manager — manage accounts, sessions, environments, and optimize token usage. Use when the user mentions switching Claude accounts, cleaning up sessions, environment snapshots, disk usage, token optimization, Claude Code health check, orphaned sessions, orphaned processes, tmp files, MCP audit, project bindings, session search, token usage history, account reorder, profiles, isolated, concurrent sessions, watch, rate limit, auto-switch, dashboard, session archive, setup wizard, recover, usage dashboard, usage compare, claudeignore, permission rules, statusline, status bar, or says "ccm", "doctor", "clean cache", "clean tmp", "session list", "session search", "env snapshot", "bind", "unbind", "reorder", "usage history", "init", "permissions audit", "statusline", "ccm watch", "ccm profiles", "ccm setup", "ccm recover".
Use when starting work on code with non-obvious constraints or history, debugging, making architectural decisions, working with external services, when the user references something from a past session, or after completing analyses, hitting unexpected results, or resolving issues worth capturing for future sessions. --- <subagent-stop> If dispatched as a subagent to execute a specific task, skip this. </subagent-stop> Kilroy is the project's knowledge base — notes from past agent sessions, teammates, and humans. It persists across sessions, machines, and the project. It is NOT local auto-memory. **If Kilroy tools are failing or returning auth errors, re-run the install script from the project's web dashboard.** ## Project Routing Check `.kilroy/config.toml` for the project mapping. If it exists and has a `project` field, pass that value as the `project` parameter on every Kilroy tool call.
Self-improving skills toolkit that watches real agent sessions, detects missed triggers, grades execution quality, and evolves skill descriptions to match how users actually talk. Use when grading sessions, generating evals, evolving skill descriptions or routing tables, checking skill health, viewing the dashboard, ingesting sessions from other platforms, or running autonomous improvement loops. Make sure to use this skill whenever the user mentions skill improvement, skill performance, skill triggers, skill evolution, skill health, undertriggering, overtriggering, session grading, or wants to know how their skills are doing — even if they don't say "selftune" explicitly.
Local observability for coding-agent sessions. Use when reviewing what an agent did, debugging failed sessions, checking token/cost spend, comparing approaches across sessions, or investigating daily agent activity. --- # AgentLens — Agent Session Observability Inspect sessions before guessing what went wrong. One local surface for traces from Cursor, Claude Code, Codex, Gemini, Pi, and OpenCode. ## When to Use - Session failed or produced unexpected results - Reviewing what tools agent called and in what order - Checking token usage and cost - Comparing two approaches to same task - Daily/weekly activity review across all agents - Debugging why session stalled or looped ## Quick Reference ### CLI ```bash agentlens summary # overview of all indexed sessions agentlens sessions list --limit 20 # recent sessions agentlens session latest --show-tools # last session with tool calls agentlens sessions events latest --follow # live-stream events from latest ``` ### Browser UI ```bash agentlens --browser # opens http://127.0.0.1:8787 ```
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: