pi-skill-tool

Install

Requires the pi coding agent — install it first: npm install -g @earendil-works/pi-coding-agent.

pi install npm:@arhen/pi-core-skill-tool

Pi extension that implements opencode2-style skills: the skill catalog is stripped from the system prompt and exposed through a single lazy skill tool.

Why

Pi injects the full <available_skills> catalog (name + description for every skill) into the system prompt — ~7.2K tokens every session, whether you use skills or not. opencode2 instead packs the catalog into one tool's description and loads skill bodies only when the agent calls the tool.

This extension does the same for pi.

How it works

1. before_agent_start → reads the skill catalog from event.systemPromptOptions.skills (pi's own discovery — project, user, settings, CLI, and npm package skills) and strips the built-in <available_skills>...</available_skills> block from the system prompt
2. Registers one lazy skill tool; its description carries a compact catalog (name + truncated description, 100 chars/skill)
3. Agent matches a task → calls skill("name") → the tool reads that skill's SKILL.md body on demand and returns it → agent follows instructions

No filesystem discovery: the catalog comes entirely from pi via systemPromptOptions on before_agent_start, so it always matches what pi itself loads — no re-scanning, no divergence. SKILL.md bodies are read lazily only when the tool is called, saving ~4.5K tokens/session.

Full comparison matrix

Measured on a fresh session (deepseek-v4-flash, no user message beyond "hi").

┌───────────────────────┬─────────┬──────────────────────────────────┬───────────────────┐
│ Config                │ Context │ Agent invokes skills?            │ User /skill:name? │
├───────────────────────┼─────────┼──────────────────────────────────┼───────────────────┤
│ Baseline (nothing)    │ 26,480  │ ✅ (reads SKILL.md from catalog) │ ✅                │
├───────────────────────┼─────────┼──────────────────────────────────┼───────────────────┤
│ Ext ON (strip + tool) │ 22,021  │ ✅ (calls skill tool)            │ ✅                │
├───────────────────────┼─────────┼──────────────────────────────────┼───────────────────┤
│ Ext OFF + flag ON     │ 18,660  │ ❌ dead — invisible              │ ✅ only           │
└───────────────────────┴─────────┴──────────────────────────────────┴───────────────────┘

Row by row

Baseline (nothing) — stock pi, no extension, no flags.

• Context: 26,480 tokens every session.
• The full catalog (all 69 skills, name + description + file path ≈ 28.9K chars) is embedded in the system prompt.
• The agent sees every skill listed and can read any SKILL.md it wants — skills are fully agent-invocable.
• Cost: the catalog is paid upfront whether or not any skill is ever used.

Ext ON (strip + tool) — this extension installed, default mode.

• Context: 22,021 tokens (-4,459 vs baseline).
• The catalog is removed from the system prompt and instead lives inside the description of one skill tool (truncated to 100 chars/skill ≈ 11.7K chars).
• The agent still auto-invokes skills — it matches a task against the tool's catalog, calls skill("name"), and receives the full SKILL.md content. No user input.
• /skill:name still works (pi's command system is independent of the prompt catalog).

Ext OFF + flag ON — extension removed, disable-model-invocation: true added to every SKILL.md frontmatter.

• Context: 18,660 tokens — the cheapest, but at a hard cost.
• The flag hides skills from the system prompt entirely, so the agent cannot see or load them.
• Only the user can trigger a skill by typing /skill:name.
• Verified: asked about a private skill, the agent could not load it and improvised by reading unrelated source files instead.

The tradeoff in one line

The 3.4K tokens between Ext ON and Ext OFF+flag is the price of agent-side skill invocation. Ext OFF+flag saves the most but makes skills user-only — the agent's ability to use skills is gone. Ext ON keeps skills fully agent-invocable for a fraction of the baseline cost.

Our case — measured on this machine

Reference environment (the numbers above come from it):

• Model: deepseek/deepseek-v4-flash (deepseek tokenizer)
• Skills loaded: 69 (23 lark-*, 8 caveman-family, 6 npm-shipped: pi-lens ×4, pi-subagents, mcp-scripting, plus design/security/vercel/next misc)
• Tool count: 25 baseline → 26 with the extension (the extra one is skill)

Context composition at baseline (26,480 total):

Component	Tokens	Share
25 tool definitions (schemas + descriptions)	~16K	60%
System prompt text (instructions, guidelines)	~10.5K	40%
— of which: skill catalog (<available_skills>)	~7.2K	27%

Context excluding skills ≈ 19.3K — that's pi's floor with this tool set (dominated by pi-subagents ~9.5K + pi-lens ~4.5K tool schemas).

What the extension changes:

	Baseline	Ext ON	Δ
Skill catalog in system prompt	28.9K chars	stripped (0)	-28.9K
Catalog in skill tool description	—	11.7K chars	+11.7K
Net catalog cost	7.2K tok	2.9K tok	-4.3K
Total fresh context	26,480	22,021	-4,459

Pros

• Saves ~4.5K tokens/session (measured) — 17% of fresh context, every session, no behavior change
• Agent keeps full skill autonomy — same invocation flow as baseline, no user input required
• Lazy by design — skill bodies load only when the tool is called, exactly like opencode2
• Zero config — discovers the same skill locations pi uses, dedupes symlinks
• Reversible — uninstall to go back to baseline; no skill files are modified
• Kill switch — PI_SKILL_TOOL=0 disables the tool (strip-only, ~19K) for emergency savings

Cons

• Truncated descriptions (100 chars) — the agent matches on keywords rather than full text. Skill bodies are complete when loaded; only the catalog summary is shortened
• Catalog still costs ~2.9K — the tool description must carry skill names for the agent to discover them. Removing it entirely (Ext OFF+flag) is cheaper but kills agent invocation

License

MIT