agentsclimarketplace

Ab review

Skill gigayaya/gigachang-skills/skills/ab-review

Useful skill for software engineer in engineering work

Install
npx -y skills add gigayaya/gigachang-skills --skill ab-review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when the user explicitly asks for an "AB", adversarial, two-sided, or "red-team" code review of code changes they have made — e.g. "AB review my diff", "do an AB review of my changes", "red-team this code change", "have two reviewers argue about my code". Dispatches two opposing sub-agents — one building the evidence-based case that the change is mergeable, one building the case that it must not merge — runs them in parallel, and returns both reports to the main agent to judge. The skill itself never issues the verdict. Manual-trigger only — never auto-invoke; always ask the user to choose the review scope first. Skip for a routine single-perspective code review.

SKILL.md

6.4 KB, as published. Nobody here has run it

AB Review

Two sub-agents with opposing assigned stances independently review the same code change and report concrete evidence. One argues the change is mergeable, the other argues it is not. The main agent then reads both reports and forms its own judgment.

A single-perspective review tends to anchor on one read of a change. Forcing one agent to build the strongest case for merging and another to build the strongest case against surfaces both the strengths and the risks a one-sided pass would miss — and leaves the final call to the main agent with both cases in hand.

When to invoke

  • Manual only. The user explicitly asks for an AB / adversarial / two-sided / red-team review of their code changes.
  • Never auto-invoke. Dispatching two sub-agents is expensive; wait for an explicit request.
  • The skill and the sub-agents never pronounce the final verdict — that is the main agent's job (Step 6), after the evidence is verified (Step 5).

Workflow

Step 1 — Confirm the review scope (always ask)

Before doing anything else, use AskUserQuestion to ask the user which code change to review. Offer these options:

  1. All unstaged changesgit diff
  2. Latest commitgit show HEAD
  3. All commits on the current feature branchgit diff main...HEAD
  4. Specific lines of code — then ask the user for file path(s) and line range(s)

Do not guess the scope. If the working directory is not a git repository, stop and tell the user.

Step 2 — Capture the code change once

Run the git command for the chosen scope and capture the diff text once — the identical text is handed to both sub-agents so they argue about the same artifact.

  • For scope 4, capture the specified line ranges with a few lines of surrounding context.
  • For scope 1, also list untracked files (git diff does not show them) and include their contents if they are relevant to the change.
  • If the chosen scope yields no changes, tell the user there is nothing to review and stop.

Step 3 — Dispatch the two reviewers in parallel

In a single message, make two Agent calls dispatching the plugin's bundled reviewer agents:

  • subagent_type: ab-review-pro — argues the change is correct and mergeable.
  • subagent_type: ab-review-con — argues the change is flawed and must not merge.

They run independently and in parallel; neither sees the other's findings. Each agent already carries its assigned stance, tool boundaries, the no-fabrication rule, and the required report format — defined in agents/ab-review-pro.md and agents/ab-review-con.md. Do not re-specify any of that here.

Pass both agents the same task prompt:

  • the captured code change from Step 2 (the identical text for both),
  • the review scope chosen in Step 1,
  • the repository path, so the agent can read surrounding code for context.

Step 4 — What each reviewer returns

Each agent returns a structured report (canonical format defined in its agent file): its side, a one-line position, numbered evidence items — each with a file:line location, a verbatim code snippet, an argument, and a strength rating — its single strongest point, and an honest statement of where its own side is weakest. Each report also ends with a machine-readable JSON evidence block (a [...] array under ## Evidence (machine-readable)) mirroring the prose evidence — Step 5 uses it.

Step 5 — Verify the cited evidence (mandatory)

Both reviewers are assigned advocates, so their citations must be checked, not trusted. This step is not optional.

  1. From each report, extract the JSON array under ## Evidence (machine-readable) and write it to a temp file — ./.tmp-ab-pro.json and ./.tmp-ab-con.json.
  2. Run the verifier (standard-library Python, no install needed):
    python ${CLAUDE_PLUGIN_ROOT}/skills/ab-review/scripts/verify_evidence.py \
      --repo <repo_path> ./.tmp-ab-pro.json ./.tmp-ab-con.json
    
  3. Read its output. Any item marked SNIPPET_NOT_FOUND or FILE_NOT_FOUND is an unverified citation — discount it in the judgment, and discount it heavily when its strength is strong (the script flags these and exits non-zero). Treat only VERIFIED items as load-bearing.
  4. Delete the two temp files after reading the result.

If a report omits or malforms its JSON block, verify that side's strongest claims manually with Grep before relying on them.

Step 6 — Judge (main agent)

After verification, the main agent — not a sub-agent, not the skill — does the judging. Present to the user:

  1. The review scope that was reviewed.
  2. Pro's strongest evidence and Con's strongest evidence — concise, pointing to file:line.
  3. The main agent's own independent judgment: which evidence holds up under scrutiny (built on the Step 5 verification — unverified citations carry no weight), and where the two sides genuinely disagree.
  4. A clear recommendation — merge as-is / merge after specific fixes / do not merge — with concrete action items.

Do not merely average the two sides; weigh the evidence. If a side cited something that does not hold up, say so.

Notes

  • No third-party dependencies — git, the Agent tool, and one standard-library Python script (scripts/verify_evidence.py) for Step 5.
  • The two reviewers are bundled plugin agents (ab-review-pro, ab-review-con, in agents/); they are review-only, with read-only file and git access.
  • Always exactly two sub-agents: one Pro, one Con.
  • The skill never writes files or changes code; it is review-only.
  • If the final write-up is long, the markdown-to-html-article skill may naturally apply for presenting it — optional and separate.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.