Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/danielvm-git/bigpowers/search-skillsgit clone --depth 1 https://github.com/danielvm-git/bigpowersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/danielvm-git/bigpowers/search-skills)<a href="https://agentmods.dev/rules/danielvm-git/bigpowers/search-skills"><img src="https://agentmods.dev/badge/rules/danielvm-git/bigpowers/search-skills.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00037 | $0.00798 |
| Opus 5 | $0.00018 | $0.00399 |
| Sonnet 5 | $0.00007 | $0.00160 |
| Haiku 4.5 | $0.00004 | $0.00080 |
Grade A, and why
search-skills scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
story: e09s01
story: e21s01
Search Skills
HARD GATE — Search results must be ranked by relevance. Do NOT return all matches without prioritization. Use skill metadata (phase, purpose, frequency) to rank.
HARD GATE — Do NOT use external embedding APIs or AI-based semantic search. This is a lexical-only index (ADR: zero external dependency).
Lexical search only — no embedding service (ADR: zero external dependency). The index is a flat markdown file (specs/SKILL-SEARCH-INDEX_LATEST.md) built from every SKILL.md's YAML frontmatter — name, description, and key phrases. No vector DB, no API calls, no network dependency.
When to use
- You're unsure which skill to invoke for a user's request
- At the start of
research-firstto find pre-existing skills that might solve the problem - When a user asks "is there a skill for X?"
- Before calling a skill by name, to confirm it's the right one
Pre-flight
- Does
specs/SKILL-SEARCH-INDEX_LATEST.mdexist? If not, runbash scripts/build-skill-index.sh. - Is the index fresh? Check its timestamp — if > 24 hours old or after any SKILL.md change, regenerate.
Process
-
Refresh index if stale — Run
bash scripts/build-skill-index.shifspecs/SKILL-SEARCH-INDEX_LATEST.mddoesn't exist or was modified before the last SKILL.md change. -
Search the index — Use ripgrep on the lexical index:
rg -i "<keywords>" specs/SKILL-SEARCH-INDEX_LATEST.mdThe index contains each skill's name, description, phase, and key use-case phrases, so natural language queries work well even without embeddings.
-
Rank results — Read the top 3 matches. Evaluate by:
- Exactness — Does the description literally match the user's intent?
- Phase fit — Is the skill designed for the current lifecycle phase?
- Trigger phrases — Does the skill's "Use when" section match the situation?
-
Recommend one skill — Select the single best-matching skill. Provide:
- The skill name
- Why it's the best match (citing the description or trigger phrase)
- What it produces (artifact, dialogue, or state change)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 73 lines · 37 tokens per session scan A d4f7e7613766
search-skills is a cursor rule published in the GitHub repository danielvm-git/bigpowers (163 stars, last pushed 2d ago), licensed MIT. It adds 37 tokens to every session and 798 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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