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 taosdata/agent-skills --skill idmp-aigit clone --depth 1 https://github.com/taosdata/agent-skillsWrote 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/taosdata/agent-skills/idmp-ai)<a href="https://agentmods.dev/skills/taosdata/agent-skills/idmp-ai"><img src="https://agentmods.dev/badge/skills/taosdata/agent-skills/idmp-ai/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/taosdata/agent-skills/idmp-ai"><img src="https://agentmods.dev/badge/skills/taosdata/agent-skills/idmp-ai.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 | $0.00047 | $0.01487 |
| Opus 5 | $0.00023 | $0.00744 |
| Sonnet 5 | $0.00009 | $0.00297 |
| Haiku 4.5 | $0.00005 | $0.00149 |
Grade A, and why
idmp-ai 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 10d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ai
Read ../idmp-shared/SKILL.md first.
What this skill covers
- Prove AI availability, AI-visible data, chat-session visibility, and generation boundaries before claiming success.
- Keep generation grounded in a real element scope and hand off to non-AI workflows when the backend is empty or unavailable.
Recommended reference
Missing context to resolve first
- AI backend availability.
- Record policy.
- Whether the operator wants availability only, recommendations, a draft object, or a recorded chat.
- The target element scope for recommend or create requests.
- Whether
record:trueis acceptable.
Constrained live behaviors
- Treat
datasource available list=falseas a hard stop. idmp-cli datasource available listis the hard availability gate.recommendcan return an empty array.idmp-cli ai anydata listmeasures AI-visible data, not chat history.idmp-cli ai chat sessionsis the safest proof that recorded chat is visible.ai recommend createandai recommend create-poststill needquestionTypevalues from the backendQuestionTypeenum. UseGENERAL_QUESTION,GEN_PANEL_QUESTION, orGEN_ANALYSIS_QUESTION; do not send intuitive aliases such asPANELorANALYSIS.- Keep the endpoint path in the evidence:
ai recommend createcalls/api/v1/ai/panels/recommend, whileai recommend create-postcalls/api/v1/ai/prompts/recommend. - Recommendation endpoints can return
[]; classify that as empty output instead of inventing advice. - If the backend returns a structured error, surface that error verbatim.
- If recommend fails with
Can't parse the value: PANEL to AiGenPromptType, classify it as a backend contract mismatch instead of datasource or auth unavailability. - If recorded chat creation complains about an invalid session, retry with
sessionId:null. - AI analysis draft creation can time out even when
datasource available listandai anydata listare healthy; classifycontext deadline exceededas backend AI/API latency and hand off to structured analysis workflows instead of mutating the request semantics blindly.
What ships with it
1 file 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.
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.
- 10d ago First seen · 97 lines · 47 tokens per session scan A 7e53f5a6b2de
idmp-ai is a skill published in the GitHub repository taosdata/agent-skills (3 stars, last pushed 2d ago), licensed MIT. It adds 47 tokens to every session and 1,487 once invoked, about $0.0002 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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