Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/ahmedibrahim085/claude-multi-agent-research-system-skill/semantic-search)<a href="https://agentmods.dev/skills/ahmedibrahim085/claude-multi-agent-research-system-skill/semantic-search"><img src="https://agentmods.dev/badge/skills/ahmedibrahim085/claude-multi-agent-research-system-skill/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/ahmedibrahim085/claude-multi-agent-research-system-skill/semantic-search"><img src="https://agentmods.dev/badge/skills/ahmedibrahim085/claude-multi-agent-research-system-skill/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 | $0.00068 | $0.07381 |
| Opus 5 | $0.00034 | $0.03691 |
| Sonnet 5 | $0.00014 | $0.01476 |
| Haiku 4.5 | $0.00007 | $0.00738 |
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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 817 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Semantic Search Skill
Orchestrator for Semantic Code Intelligence via Agent Delegation
This skill orchestrates two specialized agents for semantic search operations. It provides bash scripts that import Python modules from the claude-context-local library (NOT an MCP server - no server process runs, just Python imports via PYTHONPATH). Unlike traditional text-based search (Grep) or pattern matching (Glob), semantic search understands the meaning of content, finding functionally similar text even when using different wording, variable names, or patterns.
The skill uses the library's venv Python interpreter to import merkle, chunking, and embedding modules, enabling semantic search, indexing, and similarity finding across any text content (code, docs, markdown, configs).
🎬 Orchestration Instructions
When this skill is active, you MUST spawn the appropriate agent via Task tool.
This skill uses a 2-agent architecture for token optimization:
- semantic-search-reader: Handles READ operations (search, find-similar, list-projects)
- semantic-search-indexer: Handles WRITE operations (index, incremental-reindex, status)
Decision Logic: Which Agent to Spawn?
| User Request Contains | Operation Type | Agent to Spawn |
|---|---|---|
| "find X", "search for Y", "where is Z" | search | semantic-search-reader |
| "find similar to...", "similar chunks" | find-similar | semantic-search-reader |
| "what projects", "list indexed", "show projects" | list-projects | semantic-search-reader |
| "index this", "create index", "full reindex" | index | semantic-search-indexer |
| "incremental reindex", "auto reindex", "update index" | incremental-reindex | semantic-search-indexer |
| "check index", "index status", "is it indexed" | status | semantic-search-indexer |
Agent Spawn Examples
Example 1: Search Operation (semantic-search-reader)
Task(
subagent_type="semantic-search-reader",
description="Search project semantically",
prompt="""You are the semantic-search-reader agent.
Operation: search
Query: "user authentication logic"
K: 10
Project: /path/to/project
Execute the search operation using scripts/search and return interpreted results with explanations."""
)
What ships with it
56 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .gitignore 163 B
- CURRENT-STATE-BEFORE-CORRECT-POC.md 7.7 KB
- docs/END-TO-END-HONEST-REVIEW-ALL-PHASES.md 25 KB
- docs/FIXES-COMPLETION-REPORT.md 14 KB
- docs/HONEST-REVIEW-PHASE1-AND-2.md 16 KB
- docs/model-caching-optimization.md 13 KB
- docs/phase-2-completion-report.md 8.2 KB
- docs/phase-3-completion-report.md 22 KB
- docs/phase-3-honest-review.md 15 KB
- docs/phase-3-second-honest-review.md 17 KB
- docs/ULTRA-DEEP-CODE-LEVEL-HONEST-REVIEW.md 27 KB
- MCP-INCREMENTAL-ANALYSIS.md 7.8 KB
- README.md 9.3 KB
- references/api-stability.md 3.5 KB
- references/effective-queries.md 15 KB
- references/performance-tuning.md 14 KB
- references/troubleshooting.md 18 KB
- scripts/check-prerequisites 17 KB
- scripts/find-similar 3.2 KB
- scripts/get-prerequisites-status 3.5 KB
- scripts/incremental_reindex.py 66 KB runs code
- scripts/incremental-reindex 998 B
- scripts/index.mcp-native.DEPRECATED 5.5 KB
- scripts/list-projects 429 B
- scripts/measure_cache_performance.py 7.9 KB runs code
- scripts/measure_incremental_performance.py 6.5 KB runs code
- scripts/search 3.2 KB
- scripts/set-prerequisites-ready 5.0 KB
- scripts/status 1.1 KB
- scripts/verify-setup 5.9 KB
- tests/analyze_timing_breakdowns.py 5.7 KB runs code
- tests/measure_model_caching_impact.py 7.5 KB runs code
- tests/measure_phase2_performance.py 7.1 KB runs code
- tests/measure_phase3_validation.py 11 KB runs code
- tests/profile_bottlenecks.py 10 KB runs code
- tests/test_cache_integration.py 14 KB runs code
- tests/test_cross_session_persistence.py 9.0 KB runs code
- tests/test_end_to_end_cache.py 13 KB runs code
- tests/test_end_to_end_validation.py 12 KB runs code
- tests/test_faiss_segfault.py 6.3 KB runs code
- tests/test_find_similar.py 2.6 KB runs code
- tests/test_hash_determinism.py 4.7 KB runs code
- tests/test_incremental_cache.py 29 KB runs code
- tests/test_incremental_operations.py 24 KB runs code
- tests/test_incremental_real_poc.py 23 KB runs code
- tests/test_incremental_reindex_simple.py 9.1 KB runs code
- tests/test_incremental_simple.py 3.1 KB runs code
- tests/test_incremental_verified.py 8.1 KB runs code
- tests/test_incremental_with_real_components.py 5.3 KB runs code
- tests/test_indexidmap2_bug.py 8.8 KB runs code
- tests/test_integration.py 4.0 KB runs code
- tests/test_model_caching.py 5.8 KB runs code
- tests/test_search.py 6.2 KB runs code
- tests/test_status.py 2.3 KB runs code
- tests/test_utils.py 8.8 KB runs code
- tests/verify_cache.py 1.9 KB runs code
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.
- 11d ago First seen · 817 lines · 68 tokens per session scan A 5c64465f35db
semantic-search is a skill published in the GitHub repository ahmedibrahim085/Claude-Multi-Agent-Research-System-Skill (11 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 68 tokens to every session and 7,381 once invoked, about $0.0003 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 2026-08-30.
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