review

review is a skill for Claude Code from techygarg/lattice. It costs 95 tokens per session (2,761 once invoked), scanned A, original, MIT.

A structured code-review process that chooses relevant checklists based on the files and behavior changed, then reports findings by severity.

In plain words
What is it for?
Use it to review a code change for maintainability, architecture, domain design, security, and tests when those areas are affected.
Why use it?
It keeps reviews focused on the parts of the change that matter, while still applying core checks for code quality and project context.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the lattice plugin — 33 skills, 1 agent shipped together

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/techygarg/lattice/review
Any agent
npx skills add techygarg/lattice --skill review
Clone the repo
git clone --depth 1 https://github.com/techygarg/lattice

Made for: Claude Code.

Or install lattice, the plugin that ships this one along with the rest of its 33 skills, 1 agent.

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 review

README.md
[![agentmods](https://agentmods.dev/badge/skills/techygarg/lattice/review.svg)](https://agentmods.dev/skills/techygarg/lattice/review)
Your own site
<a href="https://agentmods.dev/skills/techygarg/lattice/review"><img src="https://agentmods.dev/badge/skills/techygarg/lattice/review.svg" alt="Measured on agentmods" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,761 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 5.1 $0.00095 $0.02761
Opus 5 $0.00048 $0.01380
Sonnet 5 $0.00019 $0.00552
Haiku 4.5 $0.00010 $0.00276

Measured 6d ago against content hash e016d6e8414a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

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 6d 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/review/SKILL.md · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review

Required Skills

Load/apply skills based on scope (see Step 2 for conditional loading):

  1. framework:knowledge-priming -- Load project context (tech stack, architecture, conventions) to evaluate against real standards (always loaded)
  2. framework:learning-harvest -- Load prior operational learnings inform review; harvest new patterns at session end (always)
  3. framework:collaborative-judgment -- Surface borderline findings with both interpretations instead of silently classifying (always loaded)
  4. framework:clean-code -- Code craft: SRP, naming, complexity, error handling (always loaded)
  5. framework:architecture -- Structural: layer rules, dependency direction, architectural flows (conditional)
  6. framework:domain-driven-design -- Domain modeling: aggregates, entities, value objects (conditional)
  7. framework:secure-coding -- Security: trust boundaries, injection, secrets, input handling (conditional)
  8. framework:test-quality -- Test: AAA structure, isolation, assertions, naming (conditional)

Config Resolution

Review molecule supports optional config thru review-standards doc from review-refiner (or hand-written). Configures review process — not what atoms check (that's atom-level config via atom refiners).

Resolution steps:

  1. Look for .lattice/config.yaml in repo root.
  2. Check for config key paths.review_standards.
  3. If doc exists at path, read & check YAML frontmatter for mode:
    • mode: overlay: Read embedded defaults first, then apply doc's sections on top. Sections matched by heading — custom replaces matching defaults, new appended.
    • mode: override (or no mode): Custom doc full precedence. Must be comprehensive.
  4. If no config or no review-standards doc found, use embedded defaults thruout workflow (full backward compat — identical to review with no config).

Review-standards doc has 7 sections map to workflow steps:

Section Affects step
§1 Atom Loading Policy Step 2 (Load Relevant Atoms)
§2 Severity Classification Step 4 (Produce Report)
§3 Report Preferences Step 4 (Produce Report)
§4 Scope Rules Step 1 (Identify the Delta)
§5 Insight Capture Preferences Step 5 (Harvest Learnings and Log Review)
§6 Health Log Preferences Step 5 (Harvest Learnings and Log Review)
§7 Custom Review Dimensions Step 3 (Run Targeted Validation)

Read the full file on GitHub · 206 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. 6d ago First seen · 206 lines · 95 tokens per session scan A e016d6e8414a

Subscribe to this mod's changes

review is a skill published in the GitHub repository techygarg/lattice (185 stars, last pushed yesterday), licensed MIT. It adds 95 tokens to every session and 2,761 once invoked, about $0.0005 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.

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