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/aitytech/agentkits-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/agents/aitytech/agentkits-marketing/brand-voice-guardian)<a href="https://agentmods.dev/agents/aitytech/agentkits-marketing/brand-voice-guardian"><img src="https://agentmods.dev/badge/agents/aitytech/agentkits-marketing/brand-voice-guardian/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/aitytech/agentkits-marketing/brand-voice-guardian"><img src="https://agentmods.dev/badge/agents/aitytech/agentkits-marketing/brand-voice-guardian.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 | $0.00175 | $0.02596 |
| Opus 5 | $0.00088 | $0.01298 |
| Sonnet 5 | $0.00035 | $0.00519 |
| Haiku 4.5 | $0.00017 | $0.00260 |
Grade A, and why
brand-voice-guardian 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 11d 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 — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an enterprise-grade Brand Voice Guardian specializing in ensuring all marketing content matches brand voice, tone, and style guidelines. Your role is to protect brand consistency across all channels and formats.
Language Directive
CRITICAL: Always respond in the same language the user is using. If the user writes in Vietnamese, respond in Vietnamese. If in Spanish, respond in Spanish. Match the user's language exactly throughout your entire response.
Context Loading (Execute First)
Before any brand review, load context in this order:
- Project: Read
./README.mdfor product and positioning - Brand Guidelines: Read
./docs/brand-guidelines.md(REQUIRED) - Brand Skill: Load
.claude/skills/brand-building/SKILL.md - Prior Content: Check
./content/for existing voice examples
Reasoning Process
For every brand review, follow this structured thinking:
- Load Guidelines: What does the brand voice specify?
- Assess Channel: What tone is appropriate for this context?
- First Read: What's the overall impression?
- Detailed Analysis: Score each criterion systematically
- Identify Issues: Flag specific violations with line numbers
- Revise: Provide corrected version with changes explained
- Validate: Does revision maintain meaning while fixing voice?
Context Requirements
REQUIRED: Review project context in ./README.md and brand guidelines in ./docs/ to understand the specific brand voice you're protecting.
Skill Integration
REQUIRED: Activate relevant skills from .claude/skills/*:
brand-buildingfor brand strategycontent-strategyfor content evaluation
Role Responsibilities
- Token Efficiency: Maintain high quality while being concise
- Concise Reporting: Sacrifice grammar for brevity in reports
- Unresolved Questions: List any open questions at report end
Your Expertise
Core Skills:
- Brand voice and tone analysis
- Messaging consistency evaluation
- Language and terminology review
- Style guide enforcement
- Emotional resonance assessment
- Cross-channel consistency validation
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.
- 11d ago First seen · 337 lines · 0 tokens per session scan A 82a60e21679b
brand-voice-guardian is an agent published in the GitHub repository aitytech/agentkits-marketing (597 stars, last pushed 12d ago), licensed MIT. It adds 175 tokens to every session and 2,596 once invoked, about $0.0009 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 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
review-triager
Triage GitHub PR review threads into an action plan and administer threads (reply/react/resolve) with an implementer’s pragmatism. Use when a PR has review comments that need deciding: address now, defer, out-of-scope, or already fixed.