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/reportnpx skills add emaballarin/ccplugins --skill reportgit 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 | $0.00109 | $0.00800 |
| Opus 5 | $0.00055 | $0.00400 |
| Sonnet 5 | $0.00022 | $0.00160 |
| Haiku 4.5 | $0.00011 | $0.00080 |
Grade A, and why
report 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 yesterday.
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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ar:report — write the run up
Turn the record into something a person can read. Do not iterate.
Steps
-
Read state (
cat ./.ar/ar.jsonl | tail -50, plusworklog.mdandresults.tsvif present). Noar.jsonlmeans nothing to report — say so and stop. -
Reconstruct the run per
${CLAUDE_PLUGIN_ROOT}/references/resume-loop.md§1, across all segments, not just the last: a segment boundary marks a harness or baseline change, so metrics either side of it are not comparable and the report must say where the boundaries fell rather than plotting through them. -
Pull the winner chain from git — it is an independent record of the same run:
git log --format='%h %s' --grep='"status":"keep"' <config.branch> git diff <config.snapshotCommit>..<bestCommit> --stat -
Write
./.ar/final_report.md:- Goal and setup — objective, metric, direction, harness, budget.
- Result — baseline → best, absolute and relative, with the confidence tier. State plainly whether the total gain clears the noise floor; a run that ended inside its own scatter did not find anything, and the report says so rather than dressing it up.
- Trajectory — the keep chain, each with commit, metric, delta and the one-line description of the change.
- What worked — the winning changes and, where the record supports it, why they worked. Distinguish an explanation from a guess.
- What failed — discarded families of hypotheses. This is the part with the most reuse value; a future run should not re-derive these.
- Caveats — crashes,
checks_failediterations, seeds that disagreed, segment boundaries. - Next — the strongest untried ideas, from
ideas.mdand the plateau history.
-
Report the path.
.gitignorecarries!.ar/final_report.md, so the report is trackable if it should be committed — offer, do not commit unasked.
Hard rules
- Write
final_report.mdand nothing else. No iterating, no commits, no branch switches, no reverts. - Every number comes from
ar.jsonlor git. Never recompute or estimate one. - Report failures and null results as prominently as wins. A loop that banked noise is a finding; concealing it wastes the next run.
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.
- yesterday First seen · 61 lines · 109 tokens per session scan A ceca4dca7bc5
report is a skill published in the GitHub repository emaballarin/ccplugins (3 stars, last pushed 26d ago), licensed MIT. It adds 109 tokens to every session and 800 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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