brand-voice-enforcement▌
anthropics/knowledge-work-plugins · updated Apr 8, 2026
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Apply existing brand guidelines to all sales and marketing content generation. Load the user's brand guidelines, apply voice constants and tone flexes to the content request, validate output, and explain brand choices.
Brand Voice Enforcement
Apply existing brand guidelines to all sales and marketing content generation. Load the user's brand guidelines, apply voice constants and tone flexes to the content request, validate output, and explain brand choices.
Loading Brand Guidelines
Find the user's brand guidelines using this sequence. Stop as soon as you find them:
-
Session context — Check if brand guidelines were generated earlier in this session (via
/brand-voice:generate-guidelines). If so, they are already in the conversation. Use them directly. Session-generated guidelines are the freshest and reflect the user's most recent intent. -
Local guidelines file — Check for
.claude/brand-voice-guidelines.mdinside the user's working folder. Do NOT use a relative path from the agent's current working directory — in Cowork, the agent runs from a plugin cache directory, not the user's project. Resolve the path relative to the user's working folder. If no working folder is set, skip this step. -
Ask the user — If none of the above found guidelines, tell the user: "I couldn't find your brand guidelines. You can:
- Run
/brand-voice:discover-brandto find brand materials across your platforms - Run
/brand-voice:generate-guidelinesto create guidelines from documents or transcripts - Paste guidelines directly into this chat or point me to a file"
Wait for the user to provide guidelines before proceeding.
- Run
Also read .claude/brand-voice.local.md for enforcement settings (even if guidelines came from another source):
strictness: strict | balanced | flexiblealways-explain: whether to always explain brand choices
Enforcement Workflow
1. Analyze the Content Request
Before writing, identify:
- Content type: email, presentation, proposal, social post, message, etc.
- Target audience: role, seniority, industry, company stage
- Key messages needed: which message pillars apply
- Specific requirements: length, format, tone overrides
2. Apply Voice Constants
Voice is the brand's personality — it stays constant across all content:
- Apply "We Are / We Are Not" attributes from guidelines
- Use brand personality consistently
- Incorporate approved terminology; reject prohibited terms
- Follow messaging framework and value propositions
Refer to references/voice-constant-tone-flexes.md for the "voice constant, tone flexes" model.
3. Flex Tone for Context
Tone adapts by content type and audience. Use the tone-by-context matrix from guidelines to set:
- Formality: How formal or casual should this be?
- Energy: How much urgency or enthusiasm?
- Technical depth: How detailed or accessible?
4. Generate Content
Create content that:
- Matches brand voice attributes throughout
- Follows tone guidelines for this specific content type
- Incorporates key messages naturally (not forced)
- Uses preferred terminology
- Mirrors the quality and style of guideline examples
For complex or long-form content, delegate to the content-generation agent (defined in agents/content-generation.md).
For high-stakes content, delegate to the quality-assurance agent (defined in agents/quality-assurance.md) for validation.
5. Validate and Explain
After generating content:
- Briefly highlight which brand guidelines were applied
- Explain key voice and tone decisions
- Note any areas where guidelines were adapted for context
- Offer to refine based on feedback
When always-explain is true in settings, include brand application notes with every response.
Handling Conflicts
When the user's request conflicts with brand guidelines:
- Explain the conflict clearly
- Provide a recommendation
- Offer options: follow guidelines strictly, adapt for context, or override
Default to adapting guidelines with an explanation of the tradeoff.
Open Questions Awareness
Open questions are unresolved brand positioning decisions flagged during guideline generation, stored in the guidelines under an "Open Questions" section. When generating content, check if the brand guidelines contain open questions:
- If content touches an unresolved open question, note it
- Apply the agent's recommendation from the open question unless the user specifies otherwise
- Suggest resolving the question if it significantly impacts the content
Reference Files
references/voice-constant-tone-flexes.md— The "voice constant, tone flexes" mental model, "We Are / We Are Not" table structure, and tone-by-context matrix explanationreferences/before-after-examples.md— Before/after content examples per content type showing enforcement in practice
How to use brand-voice-enforcement on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add brand-voice-enforcement
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches brand-voice-enforcement from GitHub repository anthropics/knowledge-work-plugins and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate brand-voice-enforcement. Access the skill through slash commands (e.g., /brand-voice-enforcement) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★31 reviews- ★★★★★Diya Torres· Dec 16, 2024
brand-voice-enforcement fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Shikha Mishra· Dec 12, 2024
brand-voice-enforcement is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Hassan Garcia· Dec 4, 2024
I recommend brand-voice-enforcement for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Min Farah· Nov 23, 2024
Useful defaults in brand-voice-enforcement — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Min Khan· Nov 7, 2024
brand-voice-enforcement is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Rahul Santra· Nov 3, 2024
brand-voice-enforcement fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Sophia Khan· Oct 26, 2024
Solid pick for teams standardizing on skills: brand-voice-enforcement is focused, and the summary matches what you get after install.
- ★★★★★Pratham Ware· Oct 22, 2024
brand-voice-enforcement has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Jin Martin· Oct 14, 2024
Registry listing for brand-voice-enforcement matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Jin Yang· Sep 21, 2024
brand-voice-enforcement reduced setup friction for our internal harness; good balance of opinion and flexibility.
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