skill-authoring
Create SKILL.md files that teach the agent new domains. Use when authoring a new pi skill with frontmatter, body structure, and references.
What this skill does
# Pi Skills Skills are Markdown files (`SKILL.md`) that teach the agent how to do something it doesn't know by default. Each skill covers one or more use cases within a single domain — e.g., "NixOS configuration management" with sub-areas for system updates, home manager, and package search. The agent loads the full file when the user's request matches the trigger description. ## File Layout ``` my-skill/ ├── SKILL.md # Frontmatter + workflow instructions (keep under 120 lines) ├── references/ # Deep docs loaded on demand (API specs, advanced patterns) └── scripts/ # Helper scripts the agent runs directly ``` Assets go in `assets/` for templates and files the agent uses in outputs. Scripts in `scripts/` are deterministic code — not rewritten each invocation. ## Frontmatter Every skill requires `name`, `description`, and `keywords`. Additional fields depend on the skill type. ### Required Fields ```yaml --- name: my-skill-name # kebab-case, matches directory name (max 64 chars) description: "Does X. Use when Y." keywords: ["keyword1", "keyword2", "keyword3"] --- ``` - `name`: lowercase letters, numbers, hyphens only. No leading/trailing hyphens. - `description`: quoted string. First sentence starts with a verb. Second starts with "Use when". - `keywords`: array of single lowercase words used for scoring. Each word match scores 1.0 — you need at least 2 matches (score >= 2.0) for injection. Pick words users actually type. Avoid sharing keywords with other skills. ### Optional Fields by Type **Tool skills** (in `tools/` directory, name = tool name): ```yaml related: [other-skill] # co-inject related skills ``` **Knowledge skills** (domain knowledge): ```yaml topic: State-Space Search # required — display heading in injected block token_cost: 120 # estimated token budget (default: 150) requires_tools: [read, find] # tools needed before this skill fires ``` **Protocol skills** (behavioral rules): ```yaml topic: Conventional Commits # required — display heading in injected block ``` ## Body Structure (under 120 lines) ```markdown # Skill Name One-line summary of the domain this skill covers. ## Workflow / Commands Step-by-step examples or command reference with inline code snippets. ## Details Common variations, edge cases, or tricky parts specific to this domain. ## Constraints / Best Practices Rules, gotchas, and things the agent must do (or not do). See [deep reference](references/DEEP.md) for API specs and advanced usage. ``` - **Workflow/Commands**: numbered steps with concrete inline examples — command, code snippet, or config. - **Details**: short context for variations on the main use cases. - Link to `references/` for anything deep. One level of linking only. ## Examples from Existing Skills **Good — focused domain, multiple use cases:** ```yaml # nh: one domain (Nix operations), three sub-domains (system updates, home manager, package search) description: "Switches NixOS/Home Manager configurations, cleans old generations, and performs system maintenance. Use when running os/home switch, pruning the Nix store, or managing system generations." ``` **Good — single use case within a domain:** ```yaml # transcribe-audio: one domain (audio transcription), one primary use case description: "Transcribes audio files to text using whisper-cpp. Use when converting speech to text, transcribing podcasts, lectures, or meetings." ``` ## Validation Checklist - [ ] `name` is kebab-case and matches the directory name exactly - [ ] `description` is a quoted string with verb-first sentence + "Use when..." clause - [ ] `keywords` are single lowercase words, at least 3 per skill - [ ] `topic` present for knowledge and protocol skills - [ ] `related` lists logically connected skills for co-injection - [ ] Body is under 120 lines (move excess to `references/`) - [ ] At least one concrete inline example per key concept - [ ] No duplicated content between SKILL.md and references - [ ] All file links resolve to existing paths - [ ] Keywords don't collide with other skills ## Common Mistakes - Description uses `>` chevron instead of `"quoted"` — convert to quoted string - Missing "Use when..." clause — add trigger conditions - Duplicate content between SKILL.md and references — keep detail only in references - Long explanations of concepts the agent already knows — delete them - Extra files the agent never reads (README, changelog) — remove them
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.