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 commands/vishnu2kmohan/mcp-server-langgraph/knowledge-searchgit clone --depth 1 https://github.com/vishnu2kmohan/mcp-server-langgraphWrote 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/commands/vishnu2kmohan/mcp-server-langgraph/knowledge-search)<a href="https://agentmods.dev/commands/vishnu2kmohan/mcp-server-langgraph/knowledge-search"><img src="https://agentmods.dev/badge/commands/vishnu2kmohan/mcp-server-langgraph/knowledge-search.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 | $0.00016 | $0.02578 |
| Opus 5 | $0.00008 | $0.01289 |
| Sonnet 5 | $0.00003 | $0.00516 |
| Haiku 4.5 | $0.00002 | $0.00258 |
Grade B, and why
knowledge-search scanned grade B with 1 finding 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 4d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat .claude/context/testing-patterns.md | grep -A 30 "Property" How it starts
The opening of the file, as written. The whole thing — 369 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Knowledge Search
You are tasked with searching the project knowledge base for relevant information. This command provides semantic search across code, documentation, ADRs, and context files.
Knowledge Base Context
Sources:
- Code: All Python source files
- Documentation: ADRs, guides, API docs
- Context: Testing patterns, code patterns, recent work
- Git History: Commit messages and changes
- Templates: Sprint planning, ADRs, bug investigation
Total Knowledge: ~220 Python files, 39 ADRs, 400+ tests, 100+ commits
Your Task
Step 1: Gather Search Query
Ask the user what they're looking for:
Question: What would you like to search for?
- Header: "Search Query"
- Provide text input
- Examples:
- "How do we handle authentication?"
- "What's our caching strategy?"
- "Examples of property-based tests"
- "How to deploy to GKE?"
Step 2: Determine Search Scope
Based on the query, determine where to search:
Search Scopes:
- Code - Source files in
src/ - Tests - Test files in
tests/ - Documentation - ADRs, guides in
docs/ - Context -
.claude/context/files - All - Search everywhere
Query-to-Scope Mapping:
- Authentication/Authorization → Code + ADRs
- Testing patterns → Tests + Context
- Deployment → Documentation + Scripts
- Configuration → Code + ADRs
- Error handling → Code + Context
Step 3: Execute Search
Search Strategy:
# 1. Grep for exact matches
grep -r "<query>" <scope>/ -l
# 2. Grep for case-insensitive matches
grep -ri "<query>" <scope>/ -l -n
# 3. Search related terms (synonyms)
# Example: "cache" → also search "redis", "session", "store"
# 4. Search ADRs specifically
grep -r "<query>" adr/ docs/architecture/ -l
# 5. Search code patterns
grep -r "class.*<query>" src/ -n
grep -r "def.*<query>" src/ -n
Step 4: Rank and Filter Results
Ranking Criteria:
- Relevance: Exact match > Partial match > Related term
- Recency: Recent files > Old files (check git log)
- Importance: ADRs > Code > Tests > Utils
- Usage: Frequently referenced > Rarely referenced
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.
- 4d ago First seen · 369 lines · 16 tokens per session scan B 5e6d12be8306
knowledge-search is a command published in the GitHub repository vishnu2kmohan/mcp-server-langgraph (4 stars, last pushed 11d ago), licensed MIT. It adds 16 tokens to every session and 2,578 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
hal-voice-toggle
Toggle HAL 9000 voice clips on or off.
refresh-obsidian
Refresh the real Obsidian projection from Oracle-backed state.
cs
Run ALL steps IN ORDER. Do NOT proceed to user work until Step 7 completes.
claude-flow-memory
Interact with Claude-Flow memory system.
post-edit
Execute post-edit processing including formatting, validation, and memory updates.
post-task
Execute post-task cleanup, performance analysis, and memory storage.