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 skills add unrealandychan/clean-code-skill --skill benchmark-methodologygit clone --depth 1 https://github.com/unrealandychan/clean-code-skillWrote 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/skills/unrealandychan/clean-code-skill/benchmark-methodology)<a href="https://agentmods.dev/skills/unrealandychan/clean-code-skill/benchmark-methodology"><img src="https://agentmods.dev/badge/skills/unrealandychan/clean-code-skill/benchmark-methodology/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.
<a href="https://agentmods.dev/skills/unrealandychan/clean-code-skill/benchmark-methodology"><img src="https://agentmods.dev/badge/skills/unrealandychan/clean-code-skill/benchmark-methodology.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00072 | $0.02223 |
| Opus 5.5 | $0.00029 | $0.00889 |
| Sonnet 5.5 | $0.00014 | $0.00445 |
| Haiku 4.5 | $0.00007 | $0.00222 |
Grade A, and why
benchmark-methodology 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 1mo 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.
This is a copy
94% identical to benchmark-methodology — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark Methodology
Use this skill to turn a scoped competitor set into comparable, defensible scores. Each competitor is assessed on the same nine dimensions, with explicit 1–5 rubrics, then captured in a uniform profile card. Consistency is the point: scores are only useful if the same evidence would earn the same number for any competitor.
When to Activate
- A scoped, tiered competitor set from competitive-platform-analysis is ready to score.
- Need comparable, evidence-anchored scores across competitors — not gut-feel rankings.
- Client's strategic tension (the paired axes defining their target white-space) has been established.
- Preparing to produce profile cards for assembly in competitive-report-structure.
Client positioning brief (establish first)
Before scoring, establish the client's positioning brief. It supplies:
- Strategic tension — the two axes (e.g., memorability × hireability) whose intersection marks the client's target white-space. Dimension 9 is always the client's named tension; report both poles separately, never averaged.
- Differentiator — what makes the client's moat. This informs which dimensions matter most for the client's positioning argument.
- Brand balance — the intended mix of distinct strategic emphases. Strategic recommendations must not break this balance without flagging it.
Why these dimensions
The client competes on a specific tension held across two poles, not on service breadth. The dimensions are weighted to reflect that moat. Two dimensions — the tension poles — are scored separately and never averaged together, because the client's strategic question is precisely whether a rival achieves both simultaneously.
The nine dimensions (with weights)
Weights guide synthesis emphasis, not a single blended score (avoid a false composite — see Bias controls). Sum = 100%.
- Positioning clarity & distinctiveness (18%) — Is the studio's position sharp, ownable, and instantly legible? Or generic?
- Brand voice / verbal distinctiveness (15%) — Does the copy have an ownable register, or is it interchangeable agency-speak?
- Visual identity & site craft (15%) — Quality and ownership of the visual system; site as proof-of-craft.
- Service offer & packaging (12%) — Productized and legible (named sprints/audits) vs vague. Packaging maturity.
- Evidence & credibility (12%) — Named clients, quantified outcomes, case-study depth. Proof beyond assertion.
- Enterprise-readiness / commercial maturity (10%) — Signals they can land and hold SaaS/fintech/B2B/enterprise work (process, logos, scale, contracts).
- Thought leadership / content presence (8%) — Owned POV: writing, talks, newsletters, frameworks. Depth over volume.
- Pricing transparency & engagement model (5%) — Is pricing/engagement legible? Productized vs bespoke vs opaque.
- [Client's strategic tension] (5% as a flag; score BOTH poles, report separately) — Read the tension name and axis descriptions from the client's positioning brief. Plot both; the gap is the insight. The client's target quadrant is the single most important finding: who else is already there?
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.
- 1mo ago First seen · 192 lines · 72 tokens per session scan A f2cba14bb87f
benchmark-methodology is a skill published in the GitHub repository unrealandychan/clean-code-skill (12 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 2,223 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to benchmark-methodology, differing in 0 lines, and is treated as a copy.
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