oh-my-pi/.omp/skills/tool-prompt-optimization/SKILL.md

---

name: tool-prompt-optimization description: Optimize the description prompts an AI agent reads to learn its built-in tools (the .md files under prompts/tools/). Two halves: (1) measure how much of a prompt is already inferable from the tool's JSON parameter schema + name, to prune redundancy with evidence; (2) house authoring rules for what belongs in a tool prompt vs what stays in code. Use when auditing, trimming, writing, or reviewing tool prompts, deciding what schema field descriptions already cover, or testing schema-vs-prompt overlap before deleting prompt lines.

Tool Prompt Optimization

Prompt/schema overlap: content reconstructible from (name, JSON schema, blank outline) is a prune candidate, never an automatic delete. Probe this overlap for evidence, not vibes: predict the prompt body from those inputs. Reliably recovered lines: candidates; no-model recovery: load-bearing — keep.

Run probe

scripts/probe.ts: @oh-my-pi/pi-ai completeSimple; production-matching model/auth/provider behavior.

bun .omp/skills/tool-prompt-optimization/scripts/probe.ts \
  --schema <file|json> --template <file|text> --name <tool_name>

• Required: --schema, --template — file path or inline value.
• No --model: panel fireworks/kimi-k2.7-code, anthropic/claude-opus-4-8, openai/gpt-5.5 × --samples (default 3); requires FIREWORKS_API_KEY / ANTHROPIC_API_KEY / OPENAI_API_KEY.
• --model p/id,p/id: override panel. Tune: --samples N, --max-tokens, --json.
• Programmatic: import { probe } from "./scripts/probe.ts" → { prompt, results: [{ model, samples: [{ text, stopReason, usage, error }] }] }.

Builtin shortcut — preferred for this repo

scripts/probe-builtin.ts instantiates the live tool; gets exact toolWireSchema, tool.description, and derived outline:

bun .omp/skills/tool-prompt-optimization/scripts/probe-builtin.ts --tool <name> [--no-summary] [--show]

• --show: resolved schema, derived outline, real prompt; exits without API calls. Inspect before spending tokens.
• --no-summary: direct summary-line-blank ablation.
• --samples / --model / --max-tokens / --json: panel passthrough. Output ends with real prompt for in-place diff.
• Factory-map bypasses settings allowlist: gated irc, github, … resolve. Construction availability gate (e.g. missing gh CLI) → manual inputs.

Inputs

Schema: wire schema the model sees, never hand-sketch. Arktype:

import { arkToWireSchema } from "@oh-my-pi/pi-ai"; // or toolWireSchema(tool)
JSON.stringify(arkToWireSchema(toolSchema), null, 2);

Include required, additionalProperties: false; omission makes usage appear looser than reality.

Template: actual .md structure with bodies blanked — one-line summary, then each section tag containing ....

Structural code search via native ast-grep AST matching.

<instruction>
...
</instruction>

<output>
...
</output>

<critical>
...
</critical>

Interpret

Bucket each real-prompt line:

• Prune candidate: stable across samples and models; schema restatement — parameter names/types, required, field-description value examples, stated clamp ranges.
• Keep: no model recovers it — defaults/direction (gitignore default true); routing/escalation (NEVER shell out to find/fd → use this tool; broad exploration → Task subagent); exact output shape (mtime sort, grouping, artifact:// truncation); worked anti-patterns; type-invisible constraints (AST metavariable grammar, C++ trailing ;).

One sample: noise. Stable cross-sample/model overlap is only a candidate; history must clear it. MUST NOT delete on inferability alone.

Caveats — before every deletion

• MUST git blame each cut line; read its commit/issue. Many lines are incident scar tissue: hallucinated flag, shell-out, repo-root scan, fabricated anchor. Keep scar tissue. History distinguishes schema restatement from incident prevention. Inferability necessary, NEVER sufficient.
• Memorization ≠ inference: public repos, including this one, may be training data. Repo-specific prediction absent from schema — exact tool names, internal URI schemes, Task subagent — is recitation; discount it.
• Outline leaks: summary and section names hint. For schema-alone inference, second pass: no summary, generic section tags. Content surviving only the summary is summary-inferable, not schema-inferable.

Verdict

Predictions usually recover schema-covered parameter mechanics/generic usage, not defaults, output shape, routing, anti-patterns, domain grammar. Prune the former only after per-line git blame; keep the latter. Self-documenting flag tools (find) prune heavily; DSL/capability tools (read, ast_grep) barely.

Tool Prompt Authoring

Tool prompts are not API docs: teach when to choose a tool, input shape, and agent-owned failures. Engine internals, recovery heuristics, fallback chains, performance tuning: code.

Surface, not machinery

Agents choose from prose, not source: tell WHEN/WHY, NEVER internal HOW.

• read.md: every covered source — file/dir/archive/sqlite/PDF/URL — prevents cat/curl/tar; omit chunker, binary sniffer, cache layer.
• lsp.md: "You MUST use lsp whenever a language server is available — safer than text-based alternatives." Omit LSP wire protocol, server lifecycle, capability negotiation.
• ast_edit: metavariable syntax/workflow: "Loosest existence check: pat: 'executeBash' with narrow paths"; omit AST engine, query compilation, tree-sitter grammar selection.
• hashline.md (this repo): patch grammar — anchors, ops, payloads, ranges — and successful edit shapes. Hide tryRecoverHashlineWithCache, fuzz factor, bigram tables, findUniqueSuffixMatch, untilAborted, formatGroupedFiles; agent sees only "the tool resolved your typo" or "the anchor was stale, re-read".

If a detail cannot change agent behavior, it does NOT belong. Each sentence MUST shift an agent decision.

Good prompt anatomy

1. One-line purpose: agent-vocabulary problem; not "wraps libfoo with X", but "compact, line-anchored edit format".
2. Input grammar/surface: operators, parameters, selectors; concrete emitted syntax.
3. Worked examples: 3–8 common shapes. Example IS explanation; do not narrate twice.
4. Agent-owned failure shapes: input-fixable stale anchors, missing payload prefix, fabricated hash; omit silently recovered failures.
5. Anti-patterns: real-failure WRONG/RIGHT pairs for retry-causing mistakes, never imagined ones.
6. <critical> recap: 3–6 load-bearing lines for agents skipping body.

Exclude

• Implementation file/function names, module layout.
• Recovery, retry, normalization, caching, fuzz matching.
• Performance characteristics such as "this is O(n)", unless strategy-changing.
• Telemetry, logging, debug flags, unsettable env vars.
• Version history, deprecated parameters, "previously this worked differently".
• Cross-tool plumbing such as "this calls read under the hood", unless coordination required.