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.
npx agentmods add agents/luongnv89/skills/dimension-auditorgit clone --depth 1 https://github.com/luongnv89/skillsWrote 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.
[](https://agentmods.dev/agents/luongnv89/skills/dimension-auditor)<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>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.
| Model | Per session | Once 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 |
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.
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_delegateis set. When it isnull, 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 nameplan_delegatein each finding'sfix_directionso 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
- Take the dimension's row from
references/dimension-map.md: its delegate, its inline checklist, its skip rule. - Check the skip rule first.
UXwith no UI detected, or any dimension the user filtered out → returnstatus: "not_assessed"with that reason immediately. Do not audit it anyway. - Pick the path.
invoke_delegateset and the Skill tool available → invoke it overscope, 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.
- 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. - Write a finding per issue, each citing
path:line. Assign severity from the rubric inreferences/dimension-map.md— argue it from the evidence, not from how bad it feels. - Note cross-cutting patterns: an issue appearing at ≥ 3 sites is one pattern entry naming the finding IDs it generalizes, not thirty separate findings.
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.
- 6d ago First seen · 105 lines · 40 tokens per session scan A 9b1b127a5c06
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.
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