Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/myths-labs/musenpx agentmods add skills/myths-labs/muse/semantic-searchWrote 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/skills/myths-labs/muse/semantic-search)<a href="https://agentmods.dev/skills/myths-labs/muse/semantic-search"><img src="https://agentmods.dev/badge/skills/myths-labs/muse/semantic-search/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/myths-labs/muse/semantic-search"><img src="https://agentmods.dev/badge/skills/myths-labs/muse/semantic-search.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00032 | $0.00495 |
| Opus 5.5 | $0.00013 | $0.00198 |
| Sonnet 5.5 | $0.00006 | $0.00099 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
semantic-search 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 1mo ago.
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.
What it actually says
Semantic Search
Search across your entire MUSE project context using TF-IDF ranking.
When to Use
- User asks "where did we discuss X?"
- User wants to find a past decision or lesson
- User needs to locate a specific skill
- Context recovery when resuming work
Usage
# Search everything
./scripts/search.sh "auth jwt oauth"
# Search only memory files
./scripts/search.sh "database migration" --scope memory
# Search only role files
./scripts/search.sh "dashboard" --scope roles --top 3
# Search only skills
./scripts/search.sh "testing" --scope skills --top 10
How It Works
- Tokenization: Query is split into lowercase terms
- TF (Term Frequency): For each file, count occurrences of each query term, normalized by file length
- IDF (Inverse Document Frequency): Terms that appear in fewer files get higher weight
- Score: TF × IDF summed across all query terms
- Ranking: Files sorted by score, top N shown with best-matching line as context snippet
Scopes
| Scope | Files Indexed |
|---|---|
all (default) |
memory/ + .muse/ + MEMORIES.md + skills/ |
memory |
memory/*.md + MEMORIES.md |
roles |
.muse/*.md |
skills |
skills//SKILL.md + .agent/skills//SKILL.md |
Integration
When resuming a conversation, you can use search to quickly find relevant context:
# Before /resume — find what was done last week
./scripts/search.sh "migration deploy" --scope memory --top 3
Limitations
- Pure TF-IDF, no semantic understanding (no embeddings/vectors)
- Exact term matching only (no synonyms)
- Best for keyword-based queries with specific terms
- For semantic search, consider integrating with mem0 or memsearch
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.
- 1mo ago First seen · 68 lines · 32 tokens per session scan A f3bf315c81e4
semantic-search is a skill published in the GitHub repository myths-labs/muse (36 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 495 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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