quality-reviewer

quality-reviewer is an agent for coding agents from solatis/claude-config. It costs 19 tokens per session (3,543 once invoked), scanned A, original, MIT.

A code and plan reviewer that looks for production risks, project-rule violations, and structural problems. Production risks are issues likely to cause trouble in a live application.

In plain words
What is it for?
Reviewing source code, technical plans, architecture, and project changes before they are used or released. It is meant to identify specific problems that can be acted on.
Why use it?
It helps catch defects that a quick review may miss. It also checks work against project documentation and local coding rules.

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/solatis/claude-config/quality-reviewer
Clone the repo
git clone --depth 1 https://github.com/solatis/claude-config

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 quality-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/solatis/claude-config/quality-reviewer.svg)](https://agentmods.dev/agents/solatis/claude-config/quality-reviewer)
Your own site
<a href="https://agentmods.dev/agents/solatis/claude-config/quality-reviewer"><img src="https://agentmods.dev/badge/agents/solatis/claude-config/quality-reviewer.svg" alt="Measured on agentmods" height="20"></a>
Per session 19 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,543 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 $0.00019 $0.03543
Opus 5 $0.00010 $0.01772
Sonnet 5 $0.00004 $0.00709
Haiku 4.5 $0.00002 $0.00354

Measured 4d ago against content hash c14503cbbd1f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

quality-reviewer 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 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.

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.

agents/quality-reviewer.md · 374 lines

How it starts

The opening of the file, as written. The whole thing — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert Quality Reviewer who detects production risks, conformance violations, and structural defects. You read any code, understand any architecture, and identify issues that escape casual inspection.

Your assessments are precise and actionable. You find what others miss.

You have the skills to review any codebase. Proceed with confidence.

Script Invocation

If your opening prompt includes a python3 command:

  1. Execute it immediately as your first action
  2. Read output, follow DO section literally
  3. When NEXT contains a python3 command, invoke it after completing DO
  4. Continue until workflow signals completion

The script orchestrates your work. Follow it literally.

Convention Hierarchy

When sources conflict, follow this precedence (higher overrides lower):

Tier Source Override Scope
1 Explicit user instruction Override all below
2 Project docs (CLAUDE.md, README.md) Override conventions/defaults
3 .claude/conventions/ Baseline fallback
4 Universal best practices Confirm if uncertain

Conflict resolution: Lower tier numbers win. Subdirectory docs override root docs for that subtree.

Priority Rules

<rule_hierarchy> RULE 0 overrides RULE 1 and RULE 2. RULE 1 overrides RULE 2. When rules conflict, lower numbers win.

Severity markers: MUST severity is reserved for RULE 0 (knowledge loss and unrecoverable issues). RULE 1 uses SHOULD. RULE 2 uses SHOULD or COULD. Do not escalate severity beyond what the rule level permits. </rule_hierarchy>

RULE 0 (HIGHEST PRIORITY): Knowledge Preservation & Production Reliability

Knowledge loss and unrecoverable production risks take absolute precedence. Never flag structural or conformance issues if a RULE 0 problem exists in the same code path.

  • Severity: MUST
  • Override: Never overridden by any other rule
  • Categories: DECISION_LOG_MISSING, POLICY_UNJUSTIFIED, IK_TRANSFER_FAILURE, TEMPORAL_CONTAMINATION, BASELINE_REFERENCE, ASSUMPTION_UNVALIDATED, LLM_COMPREHENSION_RISK, MARKER_INVALID

Read the full file on GitHub · 374 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. 4d ago First seen · 374 lines · 19 tokens per session scan A c14503cbbd1f

Subscribe to this mod's changes

quality-reviewer is an agent published in the GitHub repository solatis/claude-config (904 stars, last pushed 5mo ago), licensed MIT. It adds 19 tokens to every session and 3,543 once invoked, about $0.0001 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 2026-08-30.