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 0.2-dinf-loopgit 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/0.2-dinf-loop)<a href="https://agentmods.dev/skills/sancovp/dinf/0.2-dinf-loop"><img src="https://agentmods.dev/badge/skills/sancovp/dinf/0.2-dinf-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 5.1 | $0.00025 | $0.00266 |
| Opus 5 | $0.00013 | $0.00133 |
| Sonnet 5 | $0.00005 | $0.00053 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
0.2-dinf-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 7d 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
92% identical to dinf-loop — 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 your default workflow for dinf — the BanditChain. Walk it on every task; it is a flow, not a function.
- Task — frame what's being asked.
- Recall = Select (search → neural-match) —
chaincompiler gba search <this-dir> "<query>"(--scope <coord>to look only in your region;--newestfor the latest versions). Read the hits and intuitively pick the best fit. - Decide — a fit → exec it. Nothing fits → construct.
- Construct —
chaincompiler gba construct <this-dir> <name> "[Focus] ⇒ [Focus] ⇒ |Converge|"(gated + coord-addressed + re-indexed; follow theadding-a-skilldiscipline — place it, AIOS it). - Execute — run the chosen/built chain.
- Reward — write a graded note to
kb/. Your KB + tree ARE your policy.
(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.
- 7d ago First seen · 16 lines · 0 tokens per session scan A d74f24e66d00
0.2-dinf-loop is a skill published in the GitHub repository sancovp/dinf (1 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 266 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to dinf-loop, differing in 6 lines, and is treated as a copy.
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