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 FradSer/dotclaude --skill loop-megit clone --depth 1 https://github.com/FradSer/dotclaudeWrote 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/fradser/dotclaude/loop-me)<a href="https://agentmods.dev/skills/fradser/dotclaude/loop-me"><img src="https://agentmods.dev/badge/skills/fradser/dotclaude/loop-me/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/fradser/dotclaude/loop-me"><img src="https://agentmods.dev/badge/skills/fradser/dotclaude/loop-me.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 | $0.00039 | $0.00592 |
| Opus 5.5 | $0.00016 | $0.00237 |
| Sonnet 5.5 | $0.00008 | $0.00118 |
| Haiku 4.5 | $0.00004 | $0.00059 |
Grade A, and why
loop-me 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 23d 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
89% identical to loop-me — 4 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.
How it starts
The opening of the file, as written. The whole thing — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run a stateful /mattpocock:grilling session whose only output is workflow specs. Use the grilling discipline (relentless, a round of questions at a time, a recommended answer attached to each) aimed at the vocabulary and goal below. Create, edit, and delete specs as the grilling resolves things.
The loop lens
A loop is a recurring pattern in the user's life: their career, their week, their morning, a single repeated activity. Picturing a life as loops within loops reveals how predictable its activities really are, which is what makes them worth delegating. Use the lens to find loops worth specifying, and propose ones the user hasn't noticed.
A workflow is the spec of one loop, made real. You run a workflow on a loop: the loop is its running instantiation. Workflows live in workflows/*.md and are the source of truth.
Vocabulary
A shared language, reached for only when a workflow calls for it: never a checklist. Mandate nothing structural: a workflow needs no AI, no checkpoint, and no schedule unless the grilling shows it does.
- Trigger: what fires each run, an event (a new email, a new issue) or a schedule (every morning). Event-triggering is usually the more efficient.
- Checkpoint: a human-in-the-loop point where the user is asked to verify or decide. Some workflows have none and run autonomously; some use no AI at all.
- Push right: defer the checkpoint as far as it will go. Do maximal work before involving the human, so they are asked once, late, with everything prepared.
- Brief: what a checkpoint presents, a tight, decision-ready summary (what was produced, why, and a link down to the asset itself), never the raw output. The user reads a brief, not a draft. Speed of review is imperative.
Definition of done
A workflow spec is done when an implementer agent could build it without asking a single question. Grill until then; nothing is done while a question remains.
The workspace
workflows/*.md: one spec per workflow.NOTES.md: raw notes on the user's world, the tools they use, the channels they process, and their own terminology for both. When it is empty or thin, interview them about their world before specifying anything. Sharpen fuzzy terms into canonical ones as they surface, and record them here.
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.
- 23d ago First seen · 33 lines · 39 tokens per session scan A 6bcf5656a7da
loop-me is a skill published in the GitHub repository FradSer/dotclaude (594 stars, last pushed 8d ago), licensed MIT. It adds 39 tokens to every session and 592 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to loop-me, differing in 4 lines, and is treated as a copy.
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