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 skills/chatt-state/teamdynamix-mcp-server/knowledge-basenpx skills add chatt-state/teamdynamix-mcp-server --skill knowledge-basegit clone --depth 1 https://github.com/chatt-state/teamdynamix-mcp-serverWrote 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/chatt-state/teamdynamix-mcp-server/knowledge-base)<a href="https://agentmods.dev/skills/chatt-state/teamdynamix-mcp-server/knowledge-base"><img src="https://agentmods.dev/badge/skills/chatt-state/teamdynamix-mcp-server/knowledge-base.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 | $0.00069 | $0.00767 |
| Opus 5 | $0.00034 | $0.00383 |
| Sonnet 5 | $0.00014 | $0.00153 |
| Haiku 4.5 | $0.00007 | $0.00077 |
Grade A, and why
tdx-knowledge-base 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 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.
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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 98 lines · 69 tokens per session scan A 2f898a723036
tdx-knowledge-base is a skill published in the GitHub repository chatt-state/teamdynamix-mcp-server (1 stars, last pushed 1mo ago), with no licence file. It adds 69 tokens to every session and 767 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 2026-08-31.
Other skills, from other repositories
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implementation_review_supervisor
Autonomous code review — supervisor delegates to engineer subagents with knowledge base.
qec-memory-experiment
使用 OpenQuantum 的固定版本 Stim 与 PyMatching 运行有界 rotated surface-code X/Z memory 蒙特卡洛实验,生成 detector error model、采样 syndrome、执行 MWPM 解码并报告逻辑错误率及区间。用于 QEC 教学、解码回归、噪声设置对比和小规模研究预检;不用于从单点估计阈值、声称真实硬件性能、接受任意 Stim 文件或在缺少来源链时宣称最终科学验收通过。.
xmemo-memory
Persistent, user-owned memory for agents. Use the standalone runtime to remember, recall, search, preserve restart continuity, manage TODOs and expenses, or diagnose XMemo when MCP tools are unavailable.
open-knowledge
Authoritative agent-runtime contract for working inside an OpenKnowledge project — a markdown-CRDT knowledge base exposed over MCP. Use whenever reading, listing, searching, or editing any .md or .mdx file in the project, and before any mcpopen-knowledge tool call (exec, search, write, edit, and the rest). Installed…
knowledge-audit
Review and clean up stored memories — find duplicates, contradictions, stale entries, and consolidate.