correctness-review

A deep review guide for checking code logic, architecture, rules, and maintainability.

In plain words
What is it for?
It helps review changed control flow, state, APIs, data transformations, bug fixes, refactors, and asynchronous or event-driven code.
Why use it?
It finds incorrect behavior and broken assumptions that a basic lint check may miss.

Skill for Claude CodeCodex

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 skills/whitequeen306/code-cortex-loop/correctness-review
Any agent
npx skills add whitequeen306/code-cortex-loop --skill correctness-review
Clone the repo
git clone --depth 1 https://github.com/whitequeen306/code-cortex-loop

Made for: Claude Code, Codex.

Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,692 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 $0.00040 $0.01692
Opus 5 $0.00020 $0.00846
Sonnet 5 $0.00008 $0.00338
Haiku 4.5 $0.00004 $0.00169

Measured 2d ago against content hash e927b3abc5a0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

correctness-review 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 2d 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.

skills/correctness-review/SKILL.md · 217 lines

How it starts

The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Correctness & Architecture Review (Deep)

Depth skill for pass 1 (review). Pair with cortexloop-expert-core and edge-case-and-state-analysis.

Go deep on correctness and architecture. This is not a shallow lint pass — trace logic, invariants, and structural fit. Other domains (security exploits, test gaps, perf bottlenecks, dead code) get defer notes, not scored findings in this pass.

When to go deep

  • New or changed control flow, state, APIs, data transforms
  • Bug fixes (verify fix and whether the root cause class exists elsewhere)
  • Refactors that move logic across modules
  • Concurrent, async, or event-driven paths
  • Domain rules encoded in multiple places

Correctness — deep checklist

Requirements & behavior

  • Does observable behavior match the stated task/spec?
  • Are success and failure outcomes both defined and reachable?
  • Do defaults match domain expectations (not just "non-null")?
  • Are implicit assumptions documented in code or violated silently?

Logic & arithmetic

  • Off-by-one, wrong comparator, inverted boolean, wrong operator precedence
  • Integer overflow/truncation, float comparison, unit mismatch
  • Wrong aggregation (sum vs count, average on empty set)
  • Timezone/date boundary errors, DST, leap seconds where relevant

State & concurrency

  • Read-modify-write races, check-then-act gaps
  • Stale reads after async gaps; cache not invalidated when state changes
  • Double application of events (idempotency missing on logic side)
  • Shared mutable state across requests/workers without synchronization
  • Lifecycle bugs: subscribe without unsubscribe, init order, teardown skipped

Edge inputs (logic angle)

  • null, undefined, empty string, empty array, empty map
  • Zero, negative, MAX_INT, empty pagination cursor
  • Duplicate keys, partial records, optional fields missing
  • Malformed but parseable input that reaches business logic

Input sanitization / injection → defer security. Missing test for an edge → defer tests.

Read the full file on GitHub · 217 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. 2d ago First seen · 217 lines · 40 tokens per session scan A e927b3abc5a0

Subscribe to this mod's changes

correctness-review is a skill published in the GitHub repository whitequeen306/code-cortex-loop (15 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 1,692 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens