ai-code-tells

ai-code-tells is a skill for Claude Code from big-emotion/agent-atelier. It costs 123 tokens per session (1,244 once invoked), scanned A, original, MIT.

A read-only review of code changes that looks for signs that AI-generated code was accepted without careful human review. It reports each finding with its file and line.

In plain words
What is it for?
Use it as a self-review after generating code, before opening a pull request, or when checking staged, working-tree, or branch changes.
Why use it?
It catches vague names, unnecessary comments, weak tests, repeated documentation, and decisions that are not justified before code is shared or merged.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md.

Part of the code-quality plugin — 1 skill, 1 agent shipped together

Good fit Use it as a self-review after generating code, before opening a pull request, or when checking staged, working-tree, or branch changes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/big-emotion/agent-atelier/ai-code-tells
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 big-emotion/agent-atelier --skill ai-code-tells
Clone the repo
git clone --depth 1 https://github.com/big-emotion/agent-atelier

Made for: Claude Code.

Or install code-quality, the plugin that ships this one along with the rest of its 1 skill, 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 ai-code-tells

README.md
[![agentmods](https://agentmods.dev/badge/skills/big-emotion/agent-atelier/ai-code-tells/github.svg)](https://agentmods.dev/skills/big-emotion/agent-atelier/ai-code-tells)
Your own site
<a href="https://agentmods.dev/skills/big-emotion/agent-atelier/ai-code-tells"><img src="https://agentmods.dev/badge/skills/big-emotion/agent-atelier/ai-code-tells/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 ai-code-tells

Your own site · 80×15
<a href="https://agentmods.dev/skills/big-emotion/agent-atelier/ai-code-tells"><img src="https://agentmods.dev/badge/skills/big-emotion/agent-atelier/ai-code-tells.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 123 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,244 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 $0.00123 $0.01244
Opus 5 $0.00062 $0.00622
Sonnet 5 $0.00025 $0.00249
Haiku 4.5 $0.00012 $0.00124

Measured 9d ago against content hash e865ee30ec79, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

ai-code-tells 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 9d 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.

plugins/code-quality/skills/ai-code-tells/SKILL.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI-Code Tells Review

A focused, read-only review that catches the five consistent signatures of AI code that nobody read before accepting it. It does not fix anything by default — it reports findings so a human keeps the mental model. Apply fixes only when the user asks.

The five tells below are the complete rule set — the skill needs no external configuration. If your user-level or project CLAUDE.md defines equivalent always-on code-quality guardrails, this skill acts as their on-demand review pass; honor any project-level tightening in the repo's own CLAUDE.md (e.g. hard gates).

When to Activate

  • The user invokes /ai-code-tells or asks to "check for AI tells / AI smells".
  • After generating a non-trivial chunk of code, before presenting it as done.
  • Before opening a PR, as a self-review pass.

Scope — what to review

Resolve the target in this order, stop at the first that applies:

  1. An explicit path, file list, or PR number the user named.
  2. Staged changes: git diff --cached. If empty →
  3. Working-tree changes: git diff. If empty →
  4. The current branch vs its merge-base with the default branch: git diff $(git merge-base HEAD origin/main 2>/dev/null || git merge-base HEAD main)...HEAD.

Review only the changed lines and enough surrounding context to judge them. Do not audit the whole repo. If nothing is in scope, say so and stop.

The five tells

For each, scan the diff and record findings. A finding is file:line — <tell> — why it's a tell — concrete fix.

  1. Narrating comments. Comments that restate what the code literally does (// increment counter, // loop over the list and process each item, // return the result). The fix: delete it, or replace it with the why (a decision, constraint, or gotcha) if one exists. A method whose every line has a play-by-play comment is the strongest signal.

  2. Generic, domain-blind names. Identifiers like data, result, item, value, obj, temp, process(), handle(), doStuff(), Manager, Helper, Util where a domain word exists. The fix: rename to what it is in the problem domain. Flag only where a more meaningful name is genuinely available — loop indices and trivially-scoped temporaries are fine.

Read the full file on GitHub · 66 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. 9d ago First seen · 66 lines · 123 tokens per session scan A e865ee30ec79

Subscribe to this mod's changes

ai-code-tells is a skill published in the GitHub repository big-emotion/agent-atelier (2 stars, last pushed 2d ago), licensed MIT. It adds 123 tokens to every session and 1,244 once invoked, about $0.0006 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 2026-08-31.

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