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 sancovp/dinf --skill 0.3.2-loop-closure-attention-2git 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/0.3.2-loop-closure-attention-2)<a href="https://agentmods.dev/skills/sancovp/dinf/0.3.2-loop-closure-attention-2"><img src="https://agentmods.dev/badge/skills/sancovp/dinf/0.3.2-loop-closure-attention-2/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/sancovp/dinf/0.3.2-loop-closure-attention-2"><img src="https://agentmods.dev/badge/skills/sancovp/dinf/0.3.2-loop-closure-attention-2.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 | $0.00018 | $0.00168 |
| Opus 5 | $0.00009 | $0.00084 |
| Sonnet 5 | $0.00004 | $0.00034 |
| Haiku 4.5 | $0.00002 | $0.00017 |
Grade A, and why
0.3.2-loop-closure-attention-2 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.
This is a copy
83% identical to 0.3.1-loop-closure-attention-1 — 15 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 an attention chain — an INNER template for how to think about something (a scaffold for a section or for your thinking). Not necessarily spoken.
Chain (custom syntax)
[Run] ⇒ [Check] ⇒ [Spend] ⇒ |Verified|
How to use it
Attention chain — loop-closure-attention-2
Attend, in order:
- Run
- Check
- Spend Hold: Verified ← converge attention here, then act
(leaf — this is an actual skill.)
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 · 22 lines · 18 tokens per session scan A 0c8bc930e225
0.3.2-loop-closure-attention-2 is a skill published in the GitHub repository sancovp/dinf (1 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 168 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to 0.3.1-loop-closure-attention-1, differing in 15 lines, and is treated as a copy.
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