judge-overengineering-review

judge-overengineering-review is a skill for Claude Code, Codex from PyModel/pythinker-cli. It costs 22 tokens per session (1,032 once invoked), scanned A, original, Apache-2.0.

A review checklist for judging whether a non-trivial code change is larger or more complex than necessary. It compares the requested work with the diff, new files, abstractions, dependencies and configuration changes.

In plain words
What is it for?
Use it before completing a multi-file change, reviewing a pull request, or checking a diff that feels heavier than the request requires.
Why use it?
It helps catch unnecessary engineering before a change is declared complete, such as adding an abstraction when a smaller existing mechanism would work.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

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/pymodel/pythinker-cli/judge-overengineering-review
Any agent
npx skills add PyModel/pythinker-cli --skill judge-overengineering-review
Clone the repo
git clone --depth 1 https://github.com/PyModel/pythinker-cli

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 judge-overengineering-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/pymodel/pythinker-cli/judge-overengineering-review.svg)](https://agentmods.dev/skills/pymodel/pythinker-cli/judge-overengineering-review)
Your own site
<a href="https://agentmods.dev/skills/pymodel/pythinker-cli/judge-overengineering-review"><img src="https://agentmods.dev/badge/skills/pymodel/pythinker-cli/judge-overengineering-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,032 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 $0.00022 $0.01032
Opus 5 $0.00011 $0.00516
Sonnet 5 $0.00004 $0.00206
Haiku 4.5 $0.00002 $0.00103

Measured 6d ago against content hash 9458fd918f6f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

judge-overengineering-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.

src/pythinker_code/skills/judge-overengineering-review/SKILL.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Judge Over-Engineering Review

Use when reviewing a non-trivial diff for over-engineering before declaring the work done. This skill is the parent-facing companion to the judge-minimum-diff rubric — the parent runs it as a pre-flight pass, and the judge subagent applies the same rubric as a quality-gate dimension.

When to run

  • Before declaring any non-trivial code change complete.
  • During code review of a pull request that touches more than one file or introduces new abstractions.
  • When a previous implementer or coder's diff feels heavier than the brief required.

For trivial one-line fixes or pure typo corrections, skip this skill — YAGNI applies to review overhead too.

Workflow

  1. Read the brief the implementer was given. Note the explicit asks and the explicit non-goals.

  2. Read the diff scoped to the allowed paths. Note every new file, new abstraction, new dependency, and new config key.

  3. Walk the reduction ladder from judge-minimum-diff:

    • Did the diff take the highest rung that holds?
    • Is there stdlib / native / installed-dep reuse the diff missed?
    • Could the change be one line and isn't?
  4. Score each finding under the rubric below.

  5. Report in the parent-facing review block format: path:line for every finding, severity per §4.1 of the base prompt, the suggested smallest fix.

Review checklist

A diff fails the over-engineering review when it has any of:

  • Speculative abstraction. Interface with one implementation, factory for one product, abstract base class with one subclass, config layer for a value that never varies.
  • New dependency without justification. The standard library, a native platform feature, or an already-installed dependency could have covered it. A new dep needs a one-line justification in the diff or PR body.
  • New config key without a consumer in the same diff. A new key with no reader is dead configuration.
  • New file without brief backing. A new module/folder the brief did not ask for, even if "tidier". Reuse the nearest neighbor first.
  • Error handling for impossible scenarios. Validating deep in business logic for inputs the boundary already filtered; re-validating after a function the caller controls.
  • Boilerplate scaffolding "for later". TODOs that fill a stub, fixtures the test doesn't use, helper modules with no callers yet.
  • Formatting churn outside the changed lines. Reformat, rename, or rewrap on lines the brief did not ask to change.
  • Self-evident comments. Restating what the next line of code already says. Comments only earn their keep when they document non-obvious algorithms, deliberate simplifications with a known ceiling, business rules, or genuine TODO: debt.
  • Clever over boring. Clever is what someone decodes at 3am. Boring is the default; clever needs justification.
  • Length-as-quality. A 500-line diff to replace a 50-line problem is a finding, not an accomplishment.

Read the full file on GitHub · 105 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 · 105 lines · 22 tokens per session scan A 9458fd918f6f

Subscribe to this mod's changes

judge-overengineering-review is a skill published in the GitHub repository PyModel/pythinker-cli (20 stars, last pushed 3d ago), licensed Apache-2.0. It adds 22 tokens to every session and 1,032 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.

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