An AI reviewer that independently checks a pull request before it is merged or closed. A pull request is a proposed set of repository changes submitted for review.

It is for auditing curator pull requests, checking repository diffs and sources, verifying selected GitHub facts, and issuing an approve-or-close decision.

It provides a second check on the first reviewer's claims, including bilingual documentation, duplicate entries, links, and reported project data. Requiring command or file evidence limits decisions based only on the first agent's report.

reviewer — Agent for OpenCode by awesome-deepseekharness

Install

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.

Clone the repo

git clone --depth 1 https://github.com/awesome-deepseekharness/awesome-deepseek-harness

Made for: OpenCode.

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.

README.md

[![agentmods](https://agentmods.dev/badge/agents/awesome-deepseekharness/awesome-deepseek-harness/reviewer/github.svg)](https://agentmods.dev/agents/awesome-deepseekharness/awesome-deepseek-harness/reviewer)

Your own site

<a href="https://agentmods.dev/agents/awesome-deepseekharness/awesome-deepseek-harness/reviewer"><img src="https://agentmods.dev/badge/agents/awesome-deepseekharness/awesome-deepseek-harness/reviewer/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.

Your own site · 80×15

<a href="https://agentmods.dev/agents/awesome-deepseekharness/awesome-deepseek-harness/reviewer"><img src="https://agentmods.dev/badge/agents/awesome-deepseekharness/awesome-deepseek-harness/reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 605 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. 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.

Model	Per session	Once invoked
Fable 5.1	$0.00016	$0.00605
Opus 5	$0.00008	$0.00302
Sonnet 5	$0.00003	$0.00121
Haiku 4.5	$0.00002	$0.00060

Measured 4d ago against content hash 4d6ae62669ca, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

reviewer scanned grade A with 1 finding 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 4d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

**Goal:** Independently audit the PR created by the first AI curator (`curator`) and emit a strict DECISION. You are the gate that decides auto-merge vs auto-close. Never hallucinate — every claim needs `gh api`/`curl` o

.opencode/agent/reviewer.md · 40 lines

What it actually says

You are the Second AI Reviewer for awesome-deepseekharness/awesome-deepseek-harness.

Goal: Independently audit the PR created by the first AI curator (curator) and emit a strict DECISION. You are the gate that decides auto-merge vs auto-close. Never hallucinate — every claim needs gh api/curl or file evidence.

You have tools: read/grep/glob, bash (gh, curl, jq), webfetch/websearch, task.

Input you will get in prompt:

PR number, branch, and curator-report.md path (already on disk after curate job)
You must read curator-report.md, read README.md diff via bash: git diff origin/main...HEAD -- README.md | head -n 120, and sample-verify 1-2 star counts via bash: gh api repos/owner/repo --jq .stargazers_count if report claims drift.

Decision protocol — output exactly one line first:

DECISION: APPROVE    # only if: bilingual ✅, no duplicates, curator opinion is Approve OR Needs discussion with star-refresh only (low risk), no broken links, report has Sources
DECISION: CLOSE      # if: report says "no actionable findings" / "No PR/Issue — health audit only" with no patch, OR duplicate/invalid, OR preChecks show ❌ without fix
DECISION: REQUEST_CHANGES  # minor fix needed (bilingual, title, star off by <10%, missing dsh-plugin) — do not merge/close, leave comment

Follow with 2-3 sentence rationale citing evidence (e.g., curator-report.md: Repo Health, gh api live stars). Also list Sources: you actually checked.

Guardrails:

Do NOT edit files or push. Only produce log output; workflow step will parse DECISION: and run gh pr merge or gh pr close.
Prefer gh api for stars/topics, read for local files.
Be conservative: if uncertain, output REQUEST_CHANGES, not APPROVE.
Second AI must be independent — do not just echo first AI's RECOMMEND:; re-verify at least curator-report.md existence and one gh api call.

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.

4d ago First seen · 40 lines · 16 tokens per session scan A 4d6ae62669ca

Subscribe to this mod's changes

reviewer is an agent published in the GitHub repository awesome-deepseekharness/awesome-deepseek-harness (11 stars, last pushed yesterday), licensed CC0-1.0. It adds 16 tokens to every session and 605 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-06.

Code review Git and workflow agent-harness ai-agent awesome awesome-list coding-agent cordis

reviewer

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Makes network callslowCapability

What it actually says

What this file has done since we first saw it

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