code-coherence-review

code-coherence-review is a skill for Claude Code, Codex from ntorga/agent-starter-kit. It costs 19 tokens per session (2,342 once invoked), scanned A, original, MIT.

A code and plan review that checks whether the logic makes sense, handles real inputs, and fits the project's structure.

In plain words
What is it for?
Use it to review an implementation or plan before delivery, tracing behavior from entry point to result and recording findings.
Why use it?
It catches broken flows, infinite loops, dead code, duplication, and gaps that style checks may miss.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review an implementation or plan before delivery, tracing behavior from entry point to result and recording findings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ntorga/agent-starter-kit/code-coherence-review
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.

Any agent
npx skills add ntorga/agent-starter-kit --skill code-coherence-review
Clone the repo
git clone --depth 1 https://github.com/ntorga/agent-starter-kit

Made for: Claude Code, Codex.

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-coherence-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/ntorga/agent-starter-kit/code-coherence-review/github.svg)](https://agentmods.dev/skills/ntorga/agent-starter-kit/code-coherence-review)
Your own site
<a href="https://agentmods.dev/skills/ntorga/agent-starter-kit/code-coherence-review"><img src="https://agentmods.dev/badge/skills/ntorga/agent-starter-kit/code-coherence-review/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-coherence-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/ntorga/agent-starter-kit/code-coherence-review"><img src="https://agentmods.dev/badge/skills/ntorga/agent-starter-kit/code-coherence-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,342 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00019 $0.02342
Opus 5 $0.00010 $0.01171
Sonnet 5 $0.00004 $0.00468
Haiku 4.5 $0.00002 $0.00234

Measured 2d ago against content hash 93c4544aef34, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-14, from the pricing page.

Security

Grade A, and why

code-coherence-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/code-coherence-review/SKILL.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

A correct function that violates a naming rule ships with a warning. A rule-compliant function with broken logic cannot ship. This skill checks what matters most: does the code make sense, survive real-world input, and respect the project's boundaries? Run it first — nothing else matters until the code is coherent.

Procedure

  1. Initialize the progress file. Create .memory/reviews/review-coherence-<timestamp>.md:

    # Coherence Review Progress
    
    ## Status
    - Last updated: <timestamp>
    - Overall: In Progress
    
    ## Phases
    - [ ] 1. Logic coherence
    - [ ] 2. Dead code, obsolete artifacts, and comments
    - [ ] 3. Correctness
    - [ ] 4. Structural coherence
    - [ ] 5. Duplication detection
    
    ## Findings
    
  2. Logic coherence. Read the work as a narrative. Trace the flow from entry point to exit. Check:

    • Does the algorithm solve what the task brief says it should?
    • Are there circular logic paths or infinite loops?
    • Do the data structures fit the problem, or is the code fighting its own model?
    • For plans: check for ambiguity (instructions that can be read two ways), logical gaps (steps that assume preconditions without establishing them), redundancy (duplicate steps), and contradictions.
    • For code and other non-plan artifacts: review against the task brief's acceptance criteria. Stress-test for blindspots, ambiguity, and false assumptions.

    Write any findings to the progress file under ## Findings with the heading ### Logic coherence. Mark phase 1 as [x].

  3. Dead code, obsolete artifacts, and comments. Scan every changed file for code that is no longer useful or reachable, and for comments that did not earn their place. For each file, check:

    • Unused functions and methods — functions or methods defined but never called anywhere in the codebase. Run rg -n 'func <name>' or rg -n 'def <name>' to find definitions, then verify with rg '<name>\(' that they are actually invoked elsewhere. If a function has zero callers, it is dead.
    • Unused variables and constants — variables or constants assigned but never read. Trace each assignment to its usage sites. Variables declared and initialized but never referenced in any subsequent statement are dead.
    • Unused imports — import statements for modules, packages, or symbols that are never referenced in the file. Compare every import against actual usage in the file body.
    • Unreachable code — code after return, break, continue, raise, exit, or panic statements within the same block. Code in conditional branches that can never be true (e.g., if false, if 1 == 0, or branches contradicted by earlier guards).
    • Commented-out code — commented code of any length. Version control holds old code, not inline comments; no justification preserves a commented-out block. Flag for removal.
    • Explanatory comments — comments that restate, narrate, or explain what code does. The fix is a rename, an extraction, or a type — not the comment. Do not flag a comment that explains why under an external constraint no code can express (see the Comments section in rules/code/general.md), and do not flag a comment a domain rule or tool contract mandates (shell headers, suppression justifications) — those are structure, not confession.
    • Deprecated or superseded logic — code paths replaced by newer implementations but not removed. Check for conditional branches that always take one path because a feature flag is permanent, or old implementations kept "just in case" with no callers.

Read the full file on GitHub · 125 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 · 125 lines · 19 tokens per session scan A 93c4544aef34

Subscribe to this mod's changes

code-coherence-review is a skill published in the GitHub repository ntorga/agent-starter-kit (142 stars, last pushed 2d ago), licensed MIT. It adds 19 tokens to every session and 2,342 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 2026-09-13.

Related

Other skills, from other repositories

python-code-quality

Code quality checks, linting, formatting, and type checking commands for the Agent Framework Python codebase. Use this when running checks, fixing lint errors, or troubleshooting CI failures.

microsoft/agent-framework · 40 tokens

trace

Use when encountering bugs, test failures, runtime errors, broken builds, or "this doesn't work" reports. Systematic root-cause analysis before any patch — never blind-patches symptoms. Standalone, ends with a final-integration review of the fix. Trigger with /hyperflow:trace, "debug this", "find the root cause", "why…

jeremylongshore/tons-of-skills-marketplace · 84 tokens

issue

Use when starting a chain from a GitHub issue — turning an issue URL or number into a triaged, planned, dispatched, and reviewed pull request. Classifies the thread (bug → root-cause discipline, feature → plan chain, question → drafted reply), synthesizes a spec from the issue's own acceptance criteria, then runs the…

jeremylongshore/tons-of-skills-marketplace · 115 tokens

skeptical-triage

Reusable 3-round self-challenge + arbiter pattern for filtering false positives from findings/verdicts. Use when the cost of a false-positive gate block exceeds the cost of 4 extra LLM turns.

avelikiy/great_cto · 49 tokens

anti-patterns

Catalogue of known SDLC anti-patterns that greatcto agents must actively reject when reviewing architecture, plans, code, or post-mortems. Used by architect (pre-impl), pm (planning), senior-dev (impl), l3-support (post-incident).

avelikiy/great_cto · 59 tokens

review-all

Multi-agent code review for diffs (project-agnostic). Covers standards, bugs, security, DRY, smells, perf, tests, API contracts, a11y/i18n. Verifies each finding to eliminate false positives. Use for /review-all, pre-PR/pre-commit review, or auditing uncommitted/staged changes.

ncoevoet/claude-review-all · 74 tokens