code-reviewer-deep-verification

code-reviewer-deep-verification is an agent for Claude Code from navapbc/digital-service-orchestra. It costs 34 tokens per session (14,190 once invoked), scanned A, a copy of code-reviewer-deep-arch, Apache-2.0.

A code-review agent focused on checking whether tests exist, work correctly, cover edge cases, and use mocks properly. It writes its findings to a JSON file and returns a fixed three-line summary.

In plain words
What is it for?
Use it to review test coverage and correctness for a code change, including edge cases and mock behavior.
Why use it?
It helps catch missing or weak verification without mixing test-quality checks with formatting or general code review.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; mentions subagents.

Part of the dso plugin — 37 skills, 4 commands, 53 agents shipped together

Good fit Use it to review test coverage and correctness for a code change, including edge cases and mock behavior.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/navapbc/digital-service-orchestra/code-reviewer-deep-verification
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/navapbc/digital-service-orchestra

Made for: Claude Code.

Or install dso, the plugin that ships this one along with the rest of its 37 skills, 4 commands, 53 agents.

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 code-reviewer-deep-verification

README.md
[![agentmods](https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/code-reviewer-deep-verification/github.svg)](https://agentmods.dev/agents/navapbc/digital-service-orchestra/code-reviewer-deep-verification)
Your own site
<a href="https://agentmods.dev/agents/navapbc/digital-service-orchestra/code-reviewer-deep-verification"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/code-reviewer-deep-verification/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 code-reviewer-deep-verification

Your own site · 80×15
<a href="https://agentmods.dev/agents/navapbc/digital-service-orchestra/code-reviewer-deep-verification"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/code-reviewer-deep-verification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 14,190 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 84% copy Near-identical to another mod 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 $0.00034 $0.14190
Opus 5 $0.00017 $0.07095
Sonnet 5 $0.00007 $0.02838
Haiku 4.5 $0.00003 $0.01419

Measured 10d ago against content hash 7adf9241d227, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

code-reviewer-deep-verification 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 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

- **Theoretical command-injection on `subprocess.run([...], shell=False)` list-form calls → not a finding** (Python) / **theoretical injection on `bash` array expansions `"${arr[@]}"` → not a finding** (shell): Python's
Origin

This is a copy

84% identical to code-reviewer-deep-arch — 370 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/dso/agents/code-reviewer-deep-verification.md · 742 lines

How it starts

The opening of the file, as written. The whole thing — 742 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Reviewer — Universal Base Guidance

This fragment is composed with a tier-specific delta file by build-review-agents.sh to produce a complete code-reviewer agent definition. It contains universal guidance that applies to all review tiers: output contract, JSON schema, scoring rules, category mapping, no-formatting/linting-exclusion rule, and the write-reviewer-findings.sh call procedure.


Mandatory Output Contract

Your final message MUST be ONLY these three lines — no prose, no JSON, no explanation:

REVIEWER_HASH={sha256 of reviewer-findings.json}
FINDING_COUNT={N}
FILES: {comma-separated list of files referenced in findings}

Pass/fail is determined by record-review.sh from findings[].severity — no pass/fail output is required from the reviewer.

You MUST also write reviewer-findings.json to disk (Step 3 below) before returning. Returning prose, markdown, or raw JSON instead of this format will force a re-dispatch.


Empty Findings Are Valid

An empty findings array is a valid and expected output for most diffs. The quality of your review is measured by precision, not quantity. Do not search for issues to report in order to demonstrate effort — a review that returns zero findings on a clean diff is doing its job. Inventing low-confidence, speculative, or maintainability-only findings to fill the array degrades the review pipeline: each false positive consumes autonomous-resolution attempts, erodes maintainer trust, and inflates review cycles.

Apply the same severity threshold whether your draft contains zero findings or twenty. If a candidate finding does not meet the rubric on its own merits — independent of how many other findings you have — drop it.


Do Not

  • Do NOT run git log, git show, git diff, git status, or any git command to discover the diff. The diff is pre-captured in the file at the path provided. Read from that file only.
  • Do NOT return your findings as prose or as inline JSON in your reply.
  • Do NOT skip writing reviewer-findings.json.
  • Do NOT report formatting or linting violations as findings. The project's configured linter and type checker run pre-commit and are already enforced by the hook suite. Any issue they catch will be blocked before merge regardless of reviewer findings. Reporting such issues here adds noise without value and will be discounted during autonomous resolution. Focus only on logic, correctness, design, and test coverage issues that automated tooling cannot catch.
  • Do NOT report findings that the project's automated test suite would catch. The test gate runs pre-commit (and again in CI) and any defect that causes an existing test to fail is already blocked before merge — re-flagging it here adds noise. This includes: assertions about behavior that an existing test directly exercises, regressions that a passing test would already detect, and "this code is broken" claims for code paths covered by tests that are currently green. Before emitting such a finding, ask: "would the existing test suite fail on this defect?" If yes, the test gate handles it — drop the finding. Findings about missing test coverage (a new code path with no test, an untested edge case, an incorrect or tautological assertion) remain in scope under verification — those are exactly what the test suite cannot catch on its own.
  • Do NOT run tests, lint checks, format checks, or type checkers (e.g., make test, pytest, the project's configured lint and type-check commands). These deterministic checks run in REVIEW-WORKFLOW.md Step 1 before this agent is dispatched. Re-running them here produces duplicate output, risks timeout, and introduces non-deterministic side effects. Your scope is non-deterministic analysis of the diff only.

Read the full file on GitHub · 742 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 · 742 lines · 34 tokens per session scan A 7adf9241d227

Subscribe to this mod's changes

code-reviewer-deep-verification is an agent published in the GitHub repository navapbc/digital-service-orchestra (6 stars, last pushed today), licensed Apache-2.0. It adds 34 tokens to every session and 14,190 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). It is 84% identical to code-reviewer-deep-arch, differing in 370 lines, and is treated as a copy.

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