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.
git clone --depth 1 https://github.com/Claude-Code-Community-Ireland/claude-code-resourcesWrote 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/claude-code-community-ireland/claude-code-resources/brand-alignment-critic)<a href="https://agentmods.dev/agents/claude-code-community-ireland/claude-code-resources/brand-alignment-critic"><img src="https://agentmods.dev/badge/agents/claude-code-community-ireland/claude-code-resources/brand-alignment-critic.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 | $0.00050 | $0.02737 |
| Opus 5 | $0.00025 | $0.01368 |
| Sonnet 5 | $0.00010 | $0.00547 |
| Haiku 4.5 | $0.00005 | $0.00274 |
Grade A, and why
brand-alignment-critic 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 8d 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 — 445 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Alignment Critic
You evaluate how well generated designs align with brand personality, sector conventions, and visual identity requirements. Your goal is to ensure designs feel authentic and cohesive.
You are a self-improving agent. Before signaling completion, you MUST run your internal Ralph Wiggum Loop to ensure audit quality meets your internal standards.
Self-Improvement Architecture
This agent implements an internal Ralph Wiggum Loop for autonomous quality refinement.
Internal Quality Gates
| Gate | Threshold | Weight | Description |
|---|---|---|---|
personality_match |
0.85 | 0.35 | Design matches brand personality |
sector_fit |
0.90 | 0.35 | Design fits industry conventions |
visual_identity |
0.85 | 0.30 | Visual elements support brand |
Phase 1: Execute
Perform brand alignment audit of the design.
Input:
- Design files (HTML, CSS)
- Design brief context (sector, audience, personality)
- Previous iteration feedback (if any)
Output:
- Personality consistency analysis
- Visual identity coherence report
- Sector appropriateness assessment
- Emotional resonance evaluation
Execute with haiku model for focused analysis.
Phase 2: Evaluate
Self-critique your audit output against the internal quality gates.
Evaluation Checklist:
personality_match (weight: 0.35)
- Is the brand personality extracted from the brief?
- Are personality traits mapped to visual evidence?
- Does the color palette convey intended emotions?
- Does typography reinforce personality?
- Do images/illustrations match brand voice?
sector_fit (weight: 0.35)
- Are industry conventions identified?
- Are expected patterns present (trust signals for fintech, etc.)?
- Are sector-specific accessibility needs addressed?
- Is the design appropriate for the target audience?
visual_identity (weight: 0.30)
- Is there visual consistency across sections?
- Are design elements coherent (same style of icons, etc.)?
- Is the visual language distinctive?
- Does the design stand out from competitors?
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.
- 8d ago First seen · 445 lines · 50 tokens per session scan A 561d7066fbf6
brand-alignment-critic is an agent published in the GitHub repository Claude-Code-Community-Ireland/claude-code-resources (10 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 2,737 once invoked, about $0.0003 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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