Generate comprehensive, LLM-ready brand voice guidelines from any combination of sources — brand documents, sales call transcripts, discovery reports, or direct user input. Transform raw materials into structured, enforceable guidelines with confidence scoring and open questions.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionguideline-generationExecute the skills CLI command in your project's root directory to begin installation:
Fetches guideline-generation from anthropics/knowledge-work-plugins and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate guideline-generation. Access via /guideline-generation in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
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Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Generate comprehensive, LLM-ready brand voice guidelines from any combination of sources — brand documents, sales call transcripts, discovery reports, or direct user input. Transform raw materials into structured, enforceable guidelines with confidence scoring and open questions.
Accept any combination of:
When a discovery report is provided, use it as the primary input — sources are already triaged and ranked. Supplement with additional analysis as needed.
Determine what the user has provided. If no sources are available:
/brand-voice:discover-brand run.claude/brand-voice.local.md for known brand material locations/brand-voice:discover-brandFor documents: Delegate to the document-analysis agent for heavy parsing. Extract voice attributes, messaging themes, terminology, tone guidance, and examples.
For transcripts: Delegate to the conversation-analysis agent for pattern recognition. Extract implicit voice attributes, successful language patterns, tone by context, and anti-patterns.
For discovery reports: Extract pre-triaged sources, conflicts, and gaps. Use the ranked sources directly.
Merge all findings into a unified guideline document following the template in references/guideline-template.md. Key sections:
"We Are / We Are Not" Table — The core brand identity anchor:
| We Are | We Are Not |
|---|---|
| [Attribute — e.g., "Confident"] | [Counter — e.g., "Arrogant"] |
| [Attribute — e.g., "Approachable"] | [Counter — e.g., "Casual or sloppy"] |
Derive attributes from the most consistent patterns across sources. Each row should have supporting evidence.
Voice Constants vs. Tone Flexes — Clarify what stays fixed and what adapts:
Tone-by-Context Matrix:
| Context | Formality | Energy | Technical Depth | Example |
|---|---|---|---|---|
| Cold outreach | Medium | High | Low | "[example phrase]" |
| Enterprise proposal | High | Medium | High | "[example phrase]" |
| Social media | Low | High | Low | "[example phrase]" |
Score each section using the methodology in references/confidence-scoring.md:
Generate open questions for any ambiguity that cannot be resolved:
## Open Questions for Team Discussion
### High Priority (blocks guideline completion)
1. **[Question Title]**
- What was found: [conflicting or incomplete info]
- Agent recommendation: [suggested resolution with reasoning]
- Need from you: [specific decision or confirmation needed]
Every open question MUST include an agent recommendation. Turn ambiguity into "confirm or override" — never a dead end.
Before presenting, verify via the quality-assurance agent (defined in agents/quality-assurance.md):
Summarize key findings:
The default save location is .claude/brand-voice-guidelines.md inside the user's working folder.
Important: The agent's working directory may not be the user's project root (especially in Cowork, where plugins run from a plugin cache directory). Always resolve the path relative to the user's working folder, not the current working directory. If no working folder is set, skip the file save and tell the user guidelines will only be available in this conversation.
.claude/brand-voice-guidelines.md inside the user's working folder. Confirm the working folder path before writing.brand-voice-guidelines-YYYY-MM-DD.md in the same directory (using today's date).claude/brand-voice-guidelines.md inside the working folder<full-path>. /brand-voice:enforce-voice will find them automatically in future sessions."The guidelines are also present in this conversation, so /brand-voice:enforce-voice can use them immediately without loading from file.
After saving, offer:
/brand-voice:enforce-voiceEnforce these privacy constraints throughout the entire generation workflow, not only at output time:
references/guideline-template.md — Complete output template with all sections, field definitions, and formatting guidancereferences/confidence-scoring.md — Confidence scoring methodology, thresholds, and examplesPrerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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guideline-generation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
guideline-generation has been reliable in day-to-day use. Documentation quality is above average for community skills.
guideline-generation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
guideline-generation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
guideline-generation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: guideline-generation is focused, and the summary matches what you get after install.
guideline-generation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: guideline-generation is focused, and the summary matches what you get after install.
guideline-generation has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend guideline-generation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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