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/ai-analyst-lab/ai-analyst-plugin/close-the-loopnpx skills add ai-analyst-lab/ai-analyst-plugin --skill close-the-loopgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-pluginWrote 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/ai-analyst-lab/ai-analyst-plugin/close-the-loop)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/close-the-loop"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/close-the-loop.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 | $0.00075 | $0.03008 |
| Opus 5 | $0.00037 | $0.01504 |
| Sonnet 5 | $0.00015 | $0.00602 |
| Haiku 4.5 | $0.00007 | $0.00301 |
Grade A, and why
close-the-loop 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.
How it starts
The opening of the file, as written. The whole thing — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Close-the-Loop
Purpose
Ensure every analysis that includes a recommendation ends with a clear follow-up plan — who decides, what metric tracks success, when to check back, and what to do if the expected outcome doesn't materialize.
When to Use
IMPORTANT: This skill only applies AFTER a recommendation has been made. If the user is still exploring, asking questions, or investigating whether to act, do NOT apply this skill yet.
Triggering Test (use this decision tree)
Ask yourself: "Has a specific recommendation or action item been made?"
- YES → Apply Close-the-Loop
- NO → Skip (even if a decision is needed, wait until the recommendation is formulated)
Apply this skill when:
- The analysis concludes with a recommendation ("we should do X")
- Root cause investigation identifies a fix ("deploy the hotfix", "roll back v3.2")
- Opportunity sizing recommends an investment ("invest 2 eng-months to recover $2.1M")
- Multiple options are presented and a decision is needed ("Option A vs B vs C")
- The analysis outputs action items that need tracking
Skip this skill when:
- Pure exploratory analysis with no recommendations ("interesting pattern, still investigating")
- User is asking whether to investigate ("should we look into this?" — this is premature, no recommendation yet)
- Questions about causality ("is this correlation or causation?" — wait until you recommend a course of action)
- Descriptive reports with no proposed actions ("here's what happened last quarter")
- Data quality assessments (unless they recommend fixes)
- Answering factual questions ("what was revenue last month?")
Common False Positives (Do NOT trigger on these)
These sound like decisions but are NOT yet ready for close-the-loop:
- "Should we investigate further?" — This is asking whether to investigate, not recommending a product change
- "What do you think is causing this?" — Exploratory question, no recommendation yet
- "Is this worth looking into?" — User is seeking direction, not ready to track an action
- "We found a pattern — what should we do?" — The recommendation hasn't been formulated yet
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 · 280 lines · 75 tokens per session scan A faaf3b0fedfc
close-the-loop is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (32 stars, last pushed 9d ago), licensed MIT. It adds 75 tokens to every session and 3,008 once invoked, about $0.0004 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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