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 commands/brainbytes-dev/everything-claude-marketing/brand-reviewgit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-marketingWrote 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/commands/brainbytes-dev/everything-claude-marketing/brand-review)<a href="https://agentmods.dev/commands/brainbytes-dev/everything-claude-marketing/brand-review"><img src="https://agentmods.dev/badge/commands/brainbytes-dev/everything-claude-marketing/brand-review.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 | $0.00023 | $0.01479 |
| Opus 5 | $0.00012 | $0.00740 |
| Sonnet 5 | $0.00005 | $0.00296 |
| Haiku 4.5 | $0.00002 | $0.00148 |
Grade A, and why
brand-review 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 5d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/brand-review
Review any content for brand consistency, covering voice, tone, messaging alignment, terminology, and visual guidelines compliance. Receive a scored assessment with specific fixes.
What This Command Does
The /brand-review command acts as your brand quality gate. It evaluates content against your brand standards and returns a structured assessment with an overall consistency score, specific findings organized by severity, and concrete revision recommendations. It catches the subtle inconsistencies that erode brand trust — off-tone language, unapproved terminology, messaging that contradicts your positioning, and guideline violations.
The command delegates to the brand-guardian agent, which maintains awareness of brand voice attributes, messaging frameworks, and content standards to perform systematic evaluations.
When to Use
- You are publishing content and want a brand consistency check before it goes live
- You have new team members or external agencies producing content that needs review
- You want to audit existing content (website pages, emails, sales decks) for brand alignment
- You are rolling out updated brand guidelines and need to assess current content
- You are reviewing translated or localized content for brand consistency
- Multiple teams produce content and you want to ensure a unified voice
- You want to establish a baseline brand consistency score for your content library
How It Works
- Content Ingestion — Reads and analyzes the provided content in full
- Voice Assessment — Evaluates whether the content matches your brand voice attributes (e.g., professional but approachable, confident but not arrogant)
- Tone Calibration — Checks if the tone is appropriate for the content type, audience, and context
- Messaging Alignment — Verifies that claims, value propositions, and positioning statements align with approved messaging frameworks
- Terminology Audit — Flags unapproved terms, inconsistent product names, or competitor language patterns
- Style & Format Check — Reviews against style guidelines (capitalization, punctuation, formatting conventions)
- Scoring & Recommendations — Produces an overall score with prioritized, specific revision suggestions
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.
- 5d ago First seen · 155 lines · 23 tokens per session scan A e0cda9c3ee92
brand-review is a command published in the GitHub repository brainbytes-dev/everything-claude-marketing (5 stars, last pushed 5mo ago), licensed MIT. It adds 23 tokens to every session and 1,479 once invoked, about $0.0001 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.