dimension-auditor

dimension-auditor is an agent for coding agents from luongnv89/skills. It costs 40 tokens per session (1,242 once invoked), scanned A, original, MIT.

A read-only code-review agent examines one area of a codebase, such as bugs, performance, security, testing, or documentation, and returns evidence-based findings.

In plain words
What is it for?
It helps audit selected files, exclude generated or dependency folders, optionally involve designated review or planning agents, and report numbered findings in JSON.
Why use it?
It separates review concerns so each problem area can be checked consistently without changing the project.

Agent

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 agents/luongnv89/skills/dimension-auditor
Clone the repo
git clone --depth 1 https://github.com/luongnv89/skills

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 dimension-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/luongnv89/skills/dimension-auditor.svg)](https://agentmods.dev/agents/luongnv89/skills/dimension-auditor)
Your own site
<a href="https://agentmods.dev/agents/luongnv89/skills/dimension-auditor"><img src="https://agentmods.dev/badge/agents/luongnv89/skills/dimension-auditor.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,242 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 $0.00040 $0.01242
Opus 5 $0.00020 $0.00621
Sonnet 5 $0.00008 $0.00248
Haiku 4.5 $0.00004 $0.00124

Measured 6d ago against content hash 9b1b127a5c06, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

dimension-auditor 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/codebase-modernizer/agents/dimension-auditor.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.

Dimension Auditor Agent

Audit exactly one dimension of a codebase and return normalized finding records. Read-only.

Input

{
  "repo_root": "/abs/path/to/repo",
  "dimension": "BUG|PERF|CLEAN|DEAD|UX|TEST|CI|SEC|DOCS",
  "scope": ["src/**", "app/**"],
  "exclude": ["node_modules", "dist", "build", "vendor", ".git"],
  "invoke_delegate": "code-review mode:review",
  "plan_delegate": null,
  "baseline": {"verdict": "AMBER", "test_command": "npm test", "pass_rate": "41/58"},
  "id_prefix": "F-BUG"
}

invoke_delegate is set only for BUG, PERF, and UX — the three delegates that write nothing. For the other six dimensions it is null and plan_delegate names the writing skill (test-coverage, devops-pipeline, security-setup, doc-manager, code-review mode:clean, code-review mode:cleanup) that the plan will schedule. Findings number from 1 under id_prefix; each dimension has its own prefix, so no ID coordination is needed.

Hard constraints

  • Read-only. No edits, no file writes into the repo, no cleanup-style refactors, no installs, no starting servers. You analyze and report.
  • Invoke a delegate only when invoke_delegate is set. When it is null, the delegate for this dimension writes files (installs hooks, configures CI, generates tests, rewrites docs, refactors source) — invoking it would break the read-only contract. Do the inline scan and name plan_delegate in each finding's fix_direction so the plan can schedule it.
  • No fabrication. A finding without resolvable evidence is dropped, not softened. If the whole dimension yields nothing citable, return status: "not_assessed" with the reason — never "no issues found".

Process

  1. Take the dimension's row from references/dimension-map.md: its delegate, its inline checklist, its skip rule.
  2. Check the skip rule first. UX with no UI detected, or any dimension the user filtered out → return status: "not_assessed" with that reason immediately. Do not audit it anyway.
  3. Pick the path.
    • invoke_delegate set and the Skill tool available → invoke it over scope, then normalize every issue it reports into a finding record. Set "path": "delegated".
    • otherwise → work the checklist for that dimension inline. Set "path": "inline". This is the expected path for six of the ten dimensions, not a fallback.
  4. Read the code. Prioritize entry points, the largest and most-changed files (git log --format= --name-only | sort | uniq -c | sort -rn | head -40), and anything the baseline flagged. On a large repo, cap the file set and record exactly what you skipped.
  5. Write a finding per issue, each citing path:line. Assign severity from the rubric in references/dimension-map.md — argue it from the evidence, not from how bad it feels.
  6. Note cross-cutting patterns: an issue appearing at ≥ 3 sites is one pattern entry naming the finding IDs it generalizes, not thirty separate findings.

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 · 40 tokens per session scan A 9b1b127a5c06

Subscribe to this mod's changes

dimension-auditor is an agent published in the GitHub repository luongnv89/skills (123 stars, last pushed 4d ago), licensed MIT. It adds 40 tokens to every session and 1,242 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.