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 instructions/hyh0620/mcp-knowledge-service/agents-mdgit clone --depth 1 https://github.com/hyh0620/mcp-knowledge-serviceWrote 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/instructions/hyh0620/mcp-knowledge-service/agents-md)<a href="https://agentmods.dev/instructions/hyh0620/mcp-knowledge-service/agents-md"><img src="https://agentmods.dev/badge/instructions/hyh0620/mcp-knowledge-service/agents-md.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 5.1 | $0.00266 | $0.00266 |
| Opus 5 | $0.00133 | $0.00133 |
| Sonnet 5 | $0.00053 | $0.00053 |
| Haiku 4.5 | $0.00027 | $0.00027 |
Grade A, and why
mcp-knowledge-service AGENTS.md 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 5d 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
AGENTS.md
- Python version: 3.11.
- Install:
python3.11 -m venv .venv && source .venv/bin/activate && pip install -e '.[dev]'. - Local config: copy
config/settings.example.yamlto ignoredconfig/settings.yaml. - MCP server command:
python -m src.mcp_server.server. - MCP stdio rule: stdout is reserved for JSON-RPC protocol messages; logs must go to stderr.
- Collection names must come from tool arguments, CLI arguments, environment variables, or config. Do not hardcode
salon_knowledgein service code. - Default public collection is
knowledge_hub; salon data is only an example underexamples/salon. - Ingest:
python scripts/ingest.py --path <SOURCE_PATH> --collection <COLLECTION> --force. - Query:
python scripts/query.py --query "<QUESTION>" --collection <COLLECTION>. - Do not commit
.env, API keys,config/settings.yaml, ChromaDB data, BM25 indexes, SQLite runtime data, logs, traces, or cache files. - After changing MCP tools or response format, verify initialize, tools/list,
query_knowledge_hub, citations, and collection isolation.
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.
- 5d ago First seen · 14 lines · 266 tokens per session scan A 8ff8dc418d5e
mcp-knowledge-service AGENTS.md is an instructions file published in the GitHub repository hyh0620/mcp-knowledge-service (0 stars, last pushed 1mo ago), licensed MIT. It adds 266 tokens to every session, about $0.0013 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 2026-09-01.
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