- 📁 .claude-plugin/
- 📁 .cursor-plugin/
- 📁 .github/
- 📄 .DS_Store
- 📄 .gitignore
- 📄 .markdownlint-cli2.jsonc
Use when working with OpenTelemetry - configuring collectors, designing pipelines, instrumenting applications, implementing sampling strategies, managing cardinality, securing telemetry data, troubleshooting observability issues, writing OTTL transformations, making production observability architecture decisions, or setting up observability for AI coding agents (Claude Code, Codex, Gemini CLI, GitHub Copilot, and others)
- 📁 glab-alias/
- 📁 glab-api/
- 📁 glab-attestation/
- 📄 README.md
- 📄 SKILL.md
- 📄 VERSION
Comprehensive GitLab CLI (glab) command reference and workflows for all GitLab operations via terminal. Use when user mentions GitLab CLI, glab commands, GitLab automation, MR/issue management via CLI, CI/CD pipeline commands, repo operations, authentication setup, or any GitLab terminal operations. Routes to specialized sub-skills for auth, CI, MRs, issues, releases, repos, and 30+ other glab commands. Triggers on glab, GitLab CLI, GitLab commands, GitLab terminal, GitLab automation.
RESTful API design conventions including endpoint naming, HTTP methods, status codes, pagination, error handling, and versioning patterns. Use when designing APIs, creating endpoints, or reviewing API contracts.
Protocol for interacting with the OntoSkills MCP server to discover, evaluate, and compose skills from the compiled knowledge graph.
- 📁 scripts/
- 📄 _meta.json
- 📄 SKILL.md
General-purpose ClawProbe spend digest skill for OpenClaw. Use when the user needs a daily, weekly, or monthly cost digest, top spenders, token totals, daily breakdowns, or previous-period comparisons based on local OpenClaw and clawprobe data. This skill is guidance plus a runnable Node script: read this file, then use exec with node to generate the digest.
End-to-end integration tests for Grafana Lens agent tools against a live LGTM stack. Detects local code changes and runs targeted tests for affected tools.
Create a well-formed git commit from current changes using session history for rationale and summary; use when asked to commit, prepare a commit message, or finalize staged work. --- # Commit ## Goals - Produce a commit that reflects the actual code changes and the session context. - Follow common git conventions (type prefix, short subject, wrapped body). - Include both summary and rationale in the body. ## Inputs - Codex session history for intent and rationale. - `git status`, `git diff`, and `git diff --staged` for actual changes. - Repo-specific commit conventions if documented. ## Steps 1. Read session history to identify scope, intent, and rationale. 2. Inspect the working tree and staged changes (`git status`, `git diff`, `git diff --staged`). 3. Stage intended changes, including new files (`git add -A`) after confirming scope. 4. Sanity-check newly added files; if anything looks random or likely ignored (build artifacts, logs, temp files), flag it to the user before committing. 5. If staging is incomplete or includes unrelated files, fix the index or ask for confirmation. 6. Choose a conventional type and optional scope that match the change (e.g., `feat(scope): ...`, `fix(scope): ...`, `refactor(scope): ...`). 7. Write a subject line in imperative mood, <= 72 characters, no trailing period. 8. Write a body that includes: - Summary of key changes (what changed). - Rationale and trade-offs (why it changed). - Tests or validation run (or explicit note if not run). 9. Append a `Co-authored-by` trailer for Codex using `Codex <[email protected]>` unless the user explicitly requests a different identity. 10. Wrap body lines at 72 characters. 11. Create the commit message with a here-doc or temp file and use `git commit -F <file>` so newlines are literal (avoid `-m` with `\n`). 12. Commit only when the message matches the staged changes: if the staged diff includes unrelated files or the message describes work that isn't staged, fix the index or revise the message
Knowledge and guardrails for the mise + fnox + infisical secrets toolchain, covering secret injection, secret providers, and env var hygiene.
Build REST and RPC APIs in Frappe including whitelisted methods, authentication, and permission handling. Use when creating custom endpoints, integrating with external systems, or exposing business logic via API.
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 ```
Add a new agent (tool) support to agent-command-sync following the registry pattern
- 📁 agents/
- 📁 references/
- 📁 scripts/
- 📄 .gitignore
- 📄 AGENTS.md
- 📄 CHANGELOG.md
Deterministic workflow to find and export full podcast transcripts as cleaned TXT files from YouTube URLs, episode webpages (including Xiaoyuzhou), Apple Podcasts title search, X/Twitter links, direct audio URLs, or plain episode titles. Use when users ask for 逐字稿/文字版/transcript/txt and want minimal trial-and-error.
