Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ahardin13/review-assistant/plugin install review-assistantWrote 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/ahardin13/review-assistant/auto-draft-review)<a href="https://agentmods.dev/skills/ahardin13/review-assistant/auto-draft-review"><img src="https://agentmods.dev/badge/skills/ahardin13/review-assistant/auto-draft-review/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/ahardin13/review-assistant/auto-draft-review"><img src="https://agentmods.dev/badge/skills/ahardin13/review-assistant/auto-draft-review.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 | $0.00042 | $0.01682 |
| Opus 5 | $0.00021 | $0.00841 |
| Sonnet 5 | $0.00008 | $0.00336 |
| Haiku 4.5 | $0.00004 | $0.00168 |
Grade A, and why
auto-draft-review 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.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Draft Review
Post analyzer findings as a pending GitHub review so the user can finalize on github.com. No walkthrough, no per-finding prompts. The user's first line ("Running auto review — ...") was already announced by the orchestrator; do not re-announce.
File I/O: Use Bash with heredocs or >> for session/temp files — not Write, Read, or Edit tools.
Inputs
pr_number: the PR numberrepo: owner/reposession_file: path to the session file (contains Why, Findings, etc.)
Step 1: Fetch the diff
gh pr diff <PR_NUMBER> --repo <REPO> > $HOME/.local/state/review-assistant/pr-<PR_NUMBER>-diff.txt
Read the session file separately for metadata (Why summary, review_sha, threshold, skipped files). Findings themselves flow through the classifier in the next step — do not re-parse them by hand.
Step 2: Classify and verify findings
Run the shared classifier against the ## Findings section:
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/classify-and-verify.py" \
--diff "$HOME/.local/state/review-assistant/pr-<PR_NUMBER>-diff.txt" \
--session "<session_file>" \
--section findings \
> $HOME/.local/state/review-assistant/pr-<PR_NUMBER>-classified.json
The script emits { inline, fallback, suspect, stats } where each bucket means:
- inline — safe to post as an inline review comment.
lineandsidehave been verified (or re-anchored within ±3 lines) against the finding's recordedcodetext. Use these verbatim. Each entry'sbodyis the finding's description as written by the analyzer (paragraph breaks preserved). Severity, confidence, and source live onsource_findingfor the review-body summary, not in the inline body — keep it that way; meta-prefixes like**high** (confidence 87, source: bug-scan)add noise to anyone reading the PR on github.com. - fallback — the line is outside every hunk for that file, or the finding was recorded with
in_diff: false. Put these in the review body, not incomments[]. - suspect — the line IS inside a hunk, but the finding's
codeanchor didn't match the diff line or any of its ±3 neighbors. Also goes in the review body, with an explicit "line anchor uncertain" flag so the reviewer knows not to trust the number.
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 · 136 lines · 42 tokens per session scan A b100eee8a8c8
auto-draft-review is a skill published in the GitHub repository ahardin13/review-assistant (3 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 1,682 once invoked, about $0.0002 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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