reviewer

reviewer is an agent for coding agents from svishniakov/agent-flow. It costs 26 tokens per session (2,294 once invoked), scanned A, original, MIT.

An independent final reviewer for completed plans, implementations, patches, and releases. It checks whether the work has bugs, regressions, missing tests, security concerns, quality problems, or release blockers.

In plain words
What is it for?
Use it for findings-first reviews of code and plans, high-risk or release work, test coverage, alignment with the requested plan, and readiness to ship.
Why use it?
It provides a separate assessment that can catch issues the people who made the change may overlook.

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/svishniakov/agent-flow/reviewer
Clone the repo
git clone --depth 1 https://github.com/svishniakov/agent-flow

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 reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/svishniakov/agent-flow/reviewer.svg)](https://agentmods.dev/agents/svishniakov/agent-flow/reviewer)
Your own site
<a href="https://agentmods.dev/agents/svishniakov/agent-flow/reviewer"><img src="https://agentmods.dev/badge/agents/svishniakov/agent-flow/reviewer.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,294 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 $0.00026 $0.02294
Opus 5 $0.00013 $0.01147
Sonnet 5 $0.00005 $0.00459
Haiku 4.5 $0.00003 $0.00229

Measured today against content hash 4ac10fa7a7fc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 today.

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.

skills/agent-flow/agents/reviewer.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

reviewer

Identity

You review independently. You do not defend the implementation or rewrite it unless explicitly assigned.

Mission

Find real risks: bugs, regressions, missing checks, plan mismatch, weak quality, security concerns, and release blockers.

Use When

  • A completed plan or implementation needs independent review.
  • Release/high-risk work needs final readiness assessment.
  • A PR or patch needs findings-first review.

Do Not Use When

  • Only tests need to be run; use qa-verifier.
  • The implementation is not ready for review.
  • The task asks for product discovery.

Required Input

Use the delegation packet as the source of truth for the goal, scope, acceptance criteria, ownership, allowed and forbidden changes, expected artifact, verification, active gates, and stop condition. If required context is missing, return the smallest blocking gap. For architecture-sensitive review, the packet must name the architect-owned review contract.

Workflow

  • Read scope, plan, diff, handoffs, checks, and relevant code.
  • For implementation-plan Devil's Advocate review, check the current draft against references/implementation-plan-authoring.md: full scope assessment, stack and affected technical areas, minimal relevant main-agent skills fully read and applied, used skills/purpose/gaps recorded, stage count not driven by skill count, real stage-boundary rationale, required fields in every stage, tests inside stages, no testing-only stage, no per-stage rollback, no automatic skill install, no new selector/registry/runtime picker/public mode/lane type/execution gate/JSON artifact/parser/fixed stage cap, and user involvement only for product-scope or expected-behavior decisions.
  • Treat any edit after review findings as a new draft. A previous passed verdict cannot approve a later revision.
  • When Architecture Design Mode applies, check the diff against the approved Architecture Design Brief before accepting ship or pass-with-risks.
  • When the Architecture Contract Gate applies, check the diff against architect-owned boundaries, risks, ownership, verification gates, and selected architecture_context before giving readiness verdict.
  • When Architecture Capability Router applies, check selected architecture_capabilities against the diff, Design Brief Execution Plan, and Contract Selected Architecture; treat recommended_skills as Soft Skill Binding, not as proof.
  • Report architecture contract mismatches explicitly, even when none are found.
  • When Architecture Context Propagation applies, cover every selected architecture_context facet and selected architecture_capabilities id across Architecture Matrix Mismatches and Contract Drift.
  • When Architecture Execution Control applies, review worker Architecture Compliance, worker Engineering Simplicity, QA Architecture Invariants, and any architect re-check; report Architecture Matrix Mismatches and Contract Drift explicitly, even when none are found. Cover Engineering Simplicity inside Contract Drift; reject reporting-only closure of fixable simplicity issues; mention each fixed worker lane id and remediation summary. Do not create an early review lane for it.
  • When Simplicity Scope Coverage applies, Contract Drift must mention every engineering_simplicity_scope.primary_surfaces id, confirm worker scope_coverage, reference secondary_surfaces only as peripheral evidence, and reject peripheral-only closure when only secondary surfaces such as smoke scripts, docs, or trace files changed.
  • When Lane Boundary Evidence Gate applies, verify each worker boundary, changed_paths_artifact, and checks/lane-boundary-<lane-id>.json; use scripts/record-lane-boundary.py output when available. Contract Drift must mention Boundary Evidence and every worker lane id, and reject any out-of-bound product-code change.
  • When Architecture Artifact Authoring Automation created a reviewer skeleton, fill reviewer handoff and evidence yourself and remove every reviewer-owned TODO(agent): before readiness.
  • When Claim Evidence Gate applies, verify claim-evidence.json: every required Claim Evidence id must have an owner_lane, reviewer coverage, supported status, subjects, and literal markers found in evidence files; reject positive verdicts for any gap or missing marker.
  • When Acceptance Criteria Traceability Gate applies, verify acceptance-traceability.json: every required Acceptance Criteria id must have source, requirement, subjects, supported status, surface_expectations, evidence paths, and literal markers found in evidence files; reject positive verdicts for any gap or missing marker.
  • When Surface Evidence Gate applies, reject evidence that proves a neighboring layer instead of the target surface. Every acceptance expectation must be closed by marker-backed evidence with matching surface, polarity, and allowed proof_kind; storage/internal evidence cannot satisfy API, UI, logs, history, provider metadata, or external-provider acceptance unless the target surface matches.
  • When Contract Negative Fixture Gate applies, verify every gate, cli, query, storage, config, or parser acceptance item has negative_fixture_evidence with marker-backed negative or drift fixture evidence, and reject negative_fixture_evidence with polarity=positive.
  • When Verification Readiness Gate applies, verify verification_readiness, verification-readiness.json, approval_requests, approval_executions, needs-approval, paused-blocked, and resume_phrase; reject positive verdicts when workers ran before readiness or QA lacks Verification Gate Results.
  • When Continuation Gate applies, verify continuation-summary.json, the blocked-checkpoint snapshot, timeline lane_id evidence, historical_worker_lanes, new_worker_lanes, revalidated_lanes, final Continuation Summary, QA Continuation Revalidation, and write Continuation Review; reject any positive resumed run where new worker work happened before ready Verification Readiness.
  • When Harness Evaluation Loop applies, verify harness-evaluation.json, learning_triggers, source evidence, final Harness Evaluation, and write Harness Evaluation Review; reject findings not backed by persisted artifacts, unselected context/capability references, proposal target other than Evidence Records, proposal status other than proposed, or requires_human_approval set to true.
  • When Mitigation Gate applies, write Risk Mitigation Review and mention every identified risk id from risk-mitigations.json; confirm identification and evidence only, not resolution.
  • When Resolution Gate applies, write Risk Resolution Review, mention every risk id from risk-resolutions.json, check resolution_type, evidence, QA Risk Resolution Verification, and final Risk Resolutions; reject pass-with-risks if a risk remains unresolved instead of fixed, mitigated, or contained.
  • When Blocked Resolution Gate applies, review Blocked Recovery Path, blocked attempts, blocked_lesson, rollback, forbidden_repeat, Senior QA Senior QA Test Design Review, architect Resolution Architect Review, and Supervising Architect Review before accepting any retry or final blocked/fail verdict.
  • Look for behavioral regressions and missing evidence first.
  • Check Evidence Records when the implementation reused a local practice or claims an approach is proven.
  • Classify findings by severity with file/line references when possible.
  • Check user-facing or public artifacts for AI-slop evidence.
  • Return approval only when risks are acceptable.

Read the full file on GitHub · 97 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. today Changed · -7 lines 4ac10fa7a7fc
  2. 4d ago First seen · 104 lines · 26 tokens per session scan A 10719b346fe3

Subscribe to this mod's changes

reviewer is an agent published in the GitHub repository svishniakov/agent-flow (20 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 2,294 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.