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Found 13,634 Skills
Explain and write effective instructions for the `/goal` feature — the persistent self-checking agent loop (plan → act → test → review → iterate), available in agents like Codex, Claude Code, and Hermes Agent. Use when the user mentions `/goal`, "goal loop", "Ralph loop", wants to kick off a long-running autonomous agent run, asks how to write a goal prompt, or wants a one-paragraph goal instruction drafted.
Enter a friendly OpenSEO coach mode that explains workflows, recommends next steps, and helps users use agents, web search, scraping, and MCP data effectively.
Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.
Version and manage your agent's prompts with LangWatch Prompts CLI. Use for both onboarding (set up prompt versioning for an entire codebase) and targeted operations (version a specific prompt, create a new prompt version). Supports Python and TypeScript.
Vertical / parallel implementation planning skill. Creates DAG-structured plan directories where each step is an independent, QA-able vertical slice that sub-agents can pick up and implement in parallel. Use whenever the user wants a plan that fans out (multiple independent features), invokes /v-plan, or asks for a "parallel plan", "DAG plan", "vertical plan", or "plan that can be parallelized" — even if they don't say those exact words. Prefer the linear `planning` skill for strictly sequential work.
Restore and read workflow state after a context break — re-inject workflow phase, task progress, and behavioral guidance into the current session, reconcile state against git reality, and verify whether a workflow exists. Use when the user says 'resume', 'rehydrate', 'where were we', or runs /rehydrate, or when the agent has drifted after context compaction. Do NOT use for saving or mutating state (that is /checkpoint).
Author, audit, and improve Grafana SKILL.md files against Anthropic's published Agent Skills guidance and the four-dimension rubric the grafana/skills CI gate uses (conciseness, actionability, workflow clarity, progressive disclosure). Applies the canonical SKILL.md structure (YAML frontmatter + body + references/ + scripts/ + assets/), the "pushy description" trigger pattern, the three-level progressive-disclosure model, and the validate-fix-rerun feedback loop. Use when creating a new skill in this repo, when reviewing a skill PR, when a skill's Tessl review score is below 75 (the merge gate), when a skill's description isn't getting picked up by agents, when restructuring a long SKILL.md into a bundle, or when the user asks how to write, improve, optimize, audit, or fix a skill - even if they don't say "skill" explicitly (e.g. "this isn't triggering", "Tessl scored this 72", "split this doc").
Audit how agent context (CLAUDE.md / AGENTS.md / rules / skills) lines up with the code across a set of repositories and generate a self-contained HTML report — a short list of specific "things to check" (context behind the code, thin coverage for the codebase, oversized files, no per-area context), plus per-repo raw metrics and a folder tree comparing folder LOC to context coverage. Use when the user wants to audit context coverage across repos, "which repos are missing CLAUDE.md", "where is our agent context thin or stale", "context coverage across my org / projects folder", or "/context-coverage". Works on a local folder of clones or a whole GitHub org via the gh CLI.
Agent-callable Microsoft SharePoint tools — find sites and document libraries, browse, search, upload, move and share files, manage lists and list items, and author site pages. Use when the user mentions SharePoint or wants to work with SharePoint sites, files, folders, lists, or pages, even if they don't name SharePoint explicitly.
Security-test a REST, GraphQL, or gRPC API with Strix — autonomous agents that enumerate endpoints from an OpenAPI/GraphQL schema (or by crawling), then actually exploit the API-specific vulnerability classes in the OWASP API Security Top 10 (2023) — broken object-level authorization (BOLA/IDOR), broken object property level authorization (excessive data exposure and mass assignment), broken function-level authorization, unrestricted resource consumption, SSRF, injection, and auth/token flaws. Every finding comes with a working proof-of-concept request. Use when the user asks to pentest, security-test, audit, or find vulnerabilities in an API, endpoint, or backend service.
Build tools that agents can use effectively, including architectural reduction patterns
General-purpose agent for researching complex questions and executing multi-step tasks. Versatile problem-solver that combines research capabilities, analytical thinking, and systematic task execution. Use for complex research projects, multi-step workflows, cross-domain analysis, and tasks requiring multiple tools and approaches.