auto-draft-review

auto-draft-review is a skill for Claude Code from ahardin13/review-assistant. It costs 42 tokens per session (1,682 once invoked), scanned A, original, MIT.

An automated process for reviewing a GitHub pull request and preparing findings as a pending review.

In plain words
What is it for?
It fetches the proposed code changes, checks analyzer findings against the diff, and posts the verified findings as a draft review on GitHub.
Why use it?
It removes the need for a live walkthrough when the review should run automatically, while leaving the final approval decision to a person.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_ROOT} variable.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the review-assistant plugin — 3 skills, 1 command, 1 agent shipped together

Good fit It fetches the proposed code changes, checks analyzer findings against the diff, and posts the verified findings as a draft review on GitHub.

Compare 6 skills from other repositories ↓
Install

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.

Claude Code
/plugin marketplace add ahardin13/review-assistant
Claude Code
/plugin install review-assistant

Made for: Claude Code.

Or install review-assistant, the plugin that ships this one along with the rest of its 3 skills, 1 command, 1 agent.

Wrote 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.

agentmods badge for auto-draft-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/ahardin13/review-assistant/auto-draft-review/github.svg)](https://agentmods.dev/skills/ahardin13/review-assistant/auto-draft-review)
Your own site
<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.

agentmods 80×15 button for auto-draft-review

Your own site · 80×15
<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>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,682 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 10d ago against content hash b100eee8a8c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

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.

skills/auto-draft-review/SKILL.md · 136 lines

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 number
  • repo: owner/repo
  • session_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. line and side have been verified (or re-anchored within ±3 lines) against the finding's recorded code text. Use these verbatim. Each entry's body is the finding's description as written by the analyzer (paragraph breaks preserved). Severity, confidence, and source live on source_finding for 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 in comments[].
  • suspect — the line IS inside a hunk, but the finding's code anchor 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.

Read the full file on GitHub · 136 lines

Changes

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.

  1. 10d ago First seen · 136 lines · 42 tokens per session scan A b100eee8a8c8

Subscribe to this mod's changes

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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