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 skills add hyh0620/mcp-knowledge-service --skill setup-environmentgit 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/skills/hyh0620/mcp-knowledge-service/setup-environment)<a href="https://agentmods.dev/skills/hyh0620/mcp-knowledge-service/setup-environment"><img src="https://agentmods.dev/badge/skills/hyh0620/mcp-knowledge-service/setup-environment/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/hyh0620/mcp-knowledge-service/setup-environment"><img src="https://agentmods.dev/badge/skills/hyh0620/mcp-knowledge-service/setup-environment.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 | $0.00016 | $0.00221 |
| Opus 5.5 | $0.00006 | $0.00088 |
| Sonnet 5.5 | $0.00003 | $0.00044 |
| Haiku 4.5 | $0.00002 | $0.00022 |
Grade A, and why
setup-environment 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
Setup Environment
Pipeline
- Check Python:
python3.11 --version - Create or reuse
.venv:python3.11 -m venv .venv source .venv/bin/activate - Install:
pip install -e '.[dev]' - Create local config:
test -f .env || cp .env.example .env test -f config/settings.yaml || cp config/settings.example.yaml config/settings.yaml - Run:
.venv/bin/python -m pip check
Output
- Local
.venv. - Ignored local
.env. - Ignored local
config/settings.yaml.
Failure Handling
- Do not print API keys.
- If provider credentials are missing, stop before ingestion or real query verification.
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 · 43 lines · 16 tokens per session scan A 6a80a6049a37
setup-environment is a skill published in the GitHub repository hyh0620/mcp-knowledge-service (0 stars, last pushed 2mo ago), licensed MIT. It adds 16 tokens to every session and 221 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 2026-09-01.
Other skills, from other repositories
vector-hybrid-search
Retrieve knowledge from a vector-store collection via the vector-mcp MCP server's vectorsearch tool — semantic (ANN) search, lexical BM25 search, or a hybrid of the two fused with Reciprocal Rank Fusion. Use when the agent must answer a question from an indexed corpus, pull top-k relevant chunks for RAG context, or…
cortex-distill
A skill for turning raw session records into organised notes and project documents. It uses a personal vault, which is a folder for storing and retrieving knowledge.
cortex-broadcast
Propagate insights from a distilled Raw into related existing Notes/Projects pages through conversational per-page edits.
cortex-query
A search tool for finding and retrieving information from Cortex, an external personal memory made up of stored notes and project pages.
cortex-evolve
A tool that saves technical notes and project decisions to a Cortex vault, which is an Obsidian note collection stored as files.
using-cortex
A guide for deciding when to search a Cortex vault, the user's personal store of notes, projects, weekly reports, and session records. It sends searches through the Cortex query process when the request refers to earlier work or an explicitly listed topic.