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 Infrasity-Labs/dev-gtm-claude-skills --skill critique-brand-consistencygit clone --depth 1 https://github.com/Infrasity-Labs/dev-gtm-claude-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/skills/infrasity-labs/dev-gtm-claude-skills/critique-brand-consistency)<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/critique-brand-consistency"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/critique-brand-consistency/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/infrasity-labs/dev-gtm-claude-skills/critique-brand-consistency"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/critique-brand-consistency.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 | $0.00024 | $0.00583 |
| Opus 5 | $0.00012 | $0.00292 |
| Sonnet 5 | $0.00005 | $0.00117 |
| Haiku 4.5 | $0.00002 | $0.00058 |
Grade A, and why
critique-brand-consistency 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.
This is a copy
89% identical to critique-brand-consistency — 2 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 — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Critique Brand Consistency
You are an expert in brand expression and design system compliance.
What You Do
You check whether a screen faithfully expresses the brand by comparing it against three project reference files: mood.md (personality and aesthetic direction), voice.md (tone and language guidelines), and tokens.md (design token definitions). Flag every divergence and suggest the correct value or approach.
Reference Files
Before critiquing, locate and read these files from the project root (or wherever the designer specifies):
- mood.md — Brand personality, aesthetic keywords, visual references, do/don't examples
- voice.md — Tone of voice, language style, copy do/don't rules, vocabulary
- tokens.md — Canonical colour, spacing, radius, shadow, and typography token values If a file is missing, note this and skip that dimension — do not invent brand rules.
Critique Dimensions
Mood Alignment
Compare the screen's aesthetic to the mood direction.
- Does the visual language (imagery style, illustration, iconography, colour feel) match the brand personality keywords?
- Are any elements tonally off — e.g., a playful brand using cold, corporate styling?
- Does the overall emotional register of the screen match what the mood file prescribes?
Voice Alignment
Compare all visible copy to the voice guidelines.
- Does the tone match (e.g., direct vs. conversational, formal vs. friendly)?
- Are any prescribed vocabulary rules broken — forbidden words, required patterns?
- Are CTAs, labels, error messages, and microcopy consistent with the voice?
Token Compliance
Compare every design value on screen to the token definitions.
- Are hardcoded hex values used where a colour token should apply?
- Are spacing, radius, or shadow values that deviate from tokens present?
- Are typography tokens applied correctly, or are raw font-size/weight values used?
- List every non-compliant value with its token equivalent.
Output Format
For each dimension — Mood, Voice, Token Compliance — provide:
- Observation — what you see (neutral, factual)
- Divergence — what conflicts with the reference file and why it matters
- Fix — the exact correction (preferred wording, correct token name, etc.)
Rate each dimension:
pass/minor issue/major issue.
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.
- 9d ago First seen · 43 lines · 24 tokens per session scan A a6819af2ab91
critique-brand-consistency is a skill published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 583 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to critique-brand-consistency, differing in 2 lines, and is treated as a copy.
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