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/emaballarin/ccplugins/resumenpx skills add emaballarin/ccplugins --skill resumegit clone --depth 1 https://github.com/emaballarin/ccpluginsWhat 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 | $0.00107 | $0.01023 |
| Opus 5 | $0.00053 | $0.00511 |
| Sonnet 5 | $0.00021 | $0.00205 |
| Haiku 4.5 | $0.00011 | $0.00102 |
Grade A, and why
resume 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 2d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ar:resume — advance the loop
Iterate until the target is met, the budget is spent, or the run is stopped.
First action, always (MANDATORY)
Read state from disk before saying or doing anything else. Context is never the carrier — this is what makes the loop survive compaction and session resets.
cat ./.ar/ar.jsonl 2>/dev/null | tail -50; git branch --show-current
No ar.jsonl means no run exists — say so and point at /ar:start. Otherwise
reconstruct best-so-far, run count, plateau streak and budget per
${CLAUDE_PLUGIN_ROOT}/references/resume-loop.md §1, then print the status block
before the first iteration.
Hard rules
- Never act on a branch this run did not create. If the current branch is
not
config.branch, do not switch onto it — create a fresh branch from the present state and open a new segment (references/protocol.md§0). - One atomic change per iteration. No compound edits. Two changes give one number and no attribution.
- Commit before measuring, with a
Result: pendingtrailer; amend it with the real result on keep. - Revert with
git checkout -- . && git clean -fdon discard or crash. Never-fdx— that flag deletes./.ar/and the run with it. - Locked harness. Any diff touching
benchmark.sh,checks.sh,evaluator.pyor the metric-emitting code is rejected and the hypothesis abandoned. Optimising a number while free to redefine it is not optimisation. - Keep only above the noise floor. Improvement must exceed
noiseFloor × noiseFloorMultiple; borderline candidates get a multi-seed re-run before the verdict, not after. - Respect the budget —
maxRuns,maxSeconds,targetMetric. - Defer execution. Print the measurement command; do not launch long jobs.
- Do not stop to ask permission. Once looping, keep going until the target
is met, the budget is exhausted,
/ar:stopfires, or interruption.
The iteration
Pick one hypothesis → apply one change → commit pending → measure → gate on
checks.sh → decide keep/discard/crash/checks_failed → amend or revert → append
to ar.jsonl and results.tsv, update research.md, worklog.md, ideas.md →
next. Three consecutive non-improvements switch strategy family; five propose a
paradigm shift. Full detail in references/protocol.md §2–§3.
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.
- 2d ago First seen · 78 lines · 107 tokens per session scan A 8d92548fab6d
resume is a skill published in the GitHub repository emaballarin/ccplugins (3 stars, last pushed 27d ago), licensed MIT. It adds 107 tokens to every session and 1,023 once invoked, about $0.0005 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 2026-08-31.
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