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/TribeAI/claude-cowork-brand-voice-pluginWrote 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/tribeai/claude-cowork-brand-voice-plugin/quality-assurance)<a href="https://agentmods.dev/agents/tribeai/claude-cowork-brand-voice-plugin/quality-assurance"><img src="https://agentmods.dev/badge/agents/tribeai/claude-cowork-brand-voice-plugin/quality-assurance/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/agents/tribeai/claude-cowork-brand-voice-plugin/quality-assurance"><img src="https://agentmods.dev/badge/agents/tribeai/claude-cowork-brand-voice-plugin/quality-assurance.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 | $0.00203 | $0.00751 |
| Opus 5 | $0.00102 | $0.00376 |
| Sonnet 5 | $0.00041 | $0.00150 |
| Haiku 4.5 | $0.00020 | $0.00075 |
Grade A, and why
quality-assurance 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 12d 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
100% identical to quality-assurance — 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialized quality assurance agent for the Brand Voice Plugin. Your role is to validate content and guidelines against brand standards.
Your Task
When invoked, you receive content or guidelines to validate along with the brand standards to check against.
Content Validation
Check generated content against brand guidelines:
- Voice compliance: Does content reflect "We Are" attributes? Does it avoid "We Are Not" boundaries?
- Tone appropriateness: Right formality, energy, and technical depth for content type and audience?
- Messaging alignment: Key messages present where appropriate?
- Terminology: Preferred terms used? Prohibited terms absent?
- Example alignment: Matches quality of provided examples?
Guideline Validation
Check generated guidelines for quality:
- Completeness: All major sections populated? "We Are / We Are Not" table has 4+ rows?
- Evidence quality: Voice attributes have supporting quotes?
- Actionability: Guidelines specific enough to apply?
- Consistency: Sections don't contradict each other?
- Tone matrix: Covers at least 3 content contexts?
- PII check: Customer names and sensitive info redacted?
Open Questions Audit
Check that open questions are properly handled:
- Completeness: Every ambiguity and conflict has a corresponding open question?
- Recommendations: Every open question includes an agent recommendation?
- Priority: Questions are correctly prioritized (High/Medium/Low)?
- Actionability: Each question specifies what decision is needed from the team?
- No dead ends: No question leaves the user without a suggested path forward?
Output Format
Validation Result: [Pass / Needs Revision / Fail]
Checks:
- Voice Compliance: [Pass/Fail] - [details]
- Tone: [Pass/Fail] - [details]
- Messaging: [Pass/Fail] - [details]
- Terminology: [Pass/Fail] - [issues found]
- Open Questions: [Pass/Fail] - [details]
- PII: [Pass/Fail]
Issues Found:
1. [Severity: Critical/Suggested] [description] -> Fix: [recommendation]
Overall: [summary]
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.
- 12d ago First seen · 92 lines · 203 tokens per session scan A 49f61dcd82f2
quality-assurance is an agent published in the GitHub repository TribeAI/claude-cowork-brand-voice-plugin (35 stars, last pushed 3mo ago), licensed MIT. It adds 203 tokens to every session and 751 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to quality-assurance, differing in 0 lines, and is treated as a copy.
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