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/sancovp/dinf/loop-closurebanditnpx skills add sancovp/dinf --skill loop-closurebanditgit clone --depth 1 https://github.com/sancovp/dinfWrote 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/sancovp/dinf/loop-closurebandit)<a href="https://agentmods.dev/skills/sancovp/dinf/loop-closurebandit"><img src="https://agentmods.dev/badge/skills/sancovp/dinf/loop-closurebandit.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 | $0.00038 | $0.00276 |
| Opus 5 | $0.00019 | $0.00138 |
| Sonnet 5 | $0.00008 | $0.00055 |
| Haiku 4.5 | $0.00004 | $0.00028 |
Grade A, and why
loop-closurebandit 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 6d 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.
This is a copy
88% identical to dinfbandit — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
This is a chain of reasoning (CoR) — a SPOKEN, paragraphical reasoning chain that ends in a DECISION. Say it as a paragraph; keep the moves in order.
CoR (custom syntax)
[Task] ⇒ [Recall] ⇒ [Decide] ⇒ [Execute] ⇒ |Reward|
Say it as a paragraph, in order
State your reasoning as ONE paragraph that, in order, 5 moves: Task, Recall, Decide, Execute, and finally converges on Reward. [Task: …the task is…] → [Recall: …have I done this…] → [Decide: …exploit…] → [Execute: …run the chain…] → [Reward: …the result is…]
Inner attention chain (use silently to generate the above)
Attention chain — Loop-closureBandit
Attend, in order:
- Task
- Recall
- Decide
- Execute Hold: Reward ← converge attention here, then act
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.
- 6d ago First seen · 26 lines · 0 tokens per session scan A 237341ef4b67
loop-closurebandit is a skill published in the GitHub repository sancovp/dinf (1 stars, last pushed 29d ago), licensed MIT. It adds 38 tokens to every session and 276 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to dinfbandit, differing in 6 lines, and is treated as a copy.
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