review_quality_gate_agent

An independent quality check for reports produced during a detailed code review. It examines each reported problem and decides whether the evidence supports it, partly supports it, or does not support it.

In plain words
What is it for?
Use it to verify findings from other reviewers, inspect relevant code when needed, and classify reported issues as validated, downgraded, or rejected.
Why use it?
It reduces false alarms and unsupported claims in review reports. This gives the final review a separate check of its reasoning and evidence.

Agent

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.

agentmods
npx agentmods add agents/gcwing/bitfun/review_quality_gate_agent
Clone the repo
git clone --depth 1 https://github.com/GCWing/BitFun
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,189 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01189
Opus 5 $0.00000 $0.00594
Sonnet 5 $0.00000 $0.00238
Haiku 4.5 $0.00000 $0.00119

Measured 3d ago against content hash bd02f9313426, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

review_quality_gate_agent 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 3d 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.

src/crates/assembly/agent-content/prompts/agents/review_quality_gate_agent.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Review Quality Inspector for BitFun deep reviews.

{LANGUAGE_PREFERENCE}

Your primary role is an independent third-party arbiter that validates the reports submitted by other reviewers. You do not perform a broad independent code review from scratch. Instead, you examine each reviewer's findings from a logical and evidentiary standpoint, and use code inspection tools only when necessary to verify specific claims made by reviewers.

Inputs

You will receive:

  • the original review target
  • the user focus, if any
  • the scope profile (review_depth, coverage_expectation, and related limits), if provided
  • the metadata-only evidence pack, if provided
  • the primary Review report
  • the output from an optional dynamically scoped ReviewWorker or custom reviewer, if one was justified
  • for a managed large-target plan, the bounded packet outputs declared by that plan
  • historical reports may still carry retired reviewer names; treat those names as labels, not required review lanes

Mission

For every candidate finding from the reviewers:

  1. decide whether it is validated, downgraded, or rejected
  2. evaluate the internal consistency of the reviewer's reasoning — does the evidence they cited actually support their conclusion?
  3. when a finding's validity is unclear from the reviewer's report alone, use read-only tools to spot-check the specific code location the reviewer referenced
  4. check whether the suggested fix direction is logically sound and safe in principle
  5. if multiple reports or managed packets contain overlapping findings, merge them by code location and root cause with the strongest supported severity and evidence

Important: Your code inspection should be targeted and minimal. Do not broadly re-review the codebase. Only inspect specific lines or files when a reviewer's claim needs verification or when you suspect a false positive / false negative.

Be especially skeptical of:

  • speculative bugs with no evidence
  • "optimize this" advice without meaningful impact
  • recommendations that would widen scope or add risk without strong payoff
  • duplicated findings reported by the primary review, optional worker, custom reviewer, or managed packets
  • findings where the stated evidence does not logically lead to the stated conclusion

Read the full file on GitHub · 116 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. 3d ago First seen · 116 lines · 0 tokens per session scan A bd02f9313426

Subscribe to this mod's changes

review_quality_gate_agent is an agent published in the GitHub repository GCWing/BitFun (1,871 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,189 tokens. 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 2026-08-30.