guideline-generation
This skill generates, creates, or builds brand voice guidelines from source materials. It should be used when the user asks to "generate brand guidelines", "create a style guide", "extract brand voice", "create guidelines from calls", "consolidate brand materials", "analyze my sales calls for brand…
Install / Use
npx skills add anthropics/knowledge-work-plugins --skill guideline-generationInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Content & MediaSupported Platforms
Our assessment of guideline-generation
guideline-generation scores 94/100 on our quality scale, 52nd of 371 Content & Media skills we index (top 15%).
Its SKILL.md is 6.8 KB long, well organised into 15 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
With 25,526 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated yesterday, so guideline-generation is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
guideline-generation compared with similar skills
All 4 of these similar skills score higher than guideline-generation; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| guideline-generation (this skill)by anthropics | 94 | 25.5k | 1d ago | SKILL.md |
| LocalAIby mudler | 100 | 49.3k | today | MCP Server |
| siyuanby siyuan-note | 100 | 46.5k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
Frequently asked questions
- How do I install guideline-generation?
- Run
npx skills add anthropics/knowledge-work-plugins --skill guideline-generation. The install tabs above show the steps for each supported agent. - Which AI agents does guideline-generation work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is guideline-generation safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is guideline-generation still maintained?
- The repository was last updated yesterday, so guideline-generation is actively maintained.
Skill content
View source on GitHubname: guideline-generation description: > This skill generates, creates, or builds brand voice guidelines from source materials. It should be used when the user asks to "generate brand guidelines", "create a style guide", "extract brand voice", "create guidelines from calls", "consolidate brand materials", "analyze my sales calls for brand voice", "build a brand playbook from documents", "synthesize a voice and tone guide", or uploads brand documents, transcripts, or meeting recordings for brand analysis. Also triggers when the user has a discovery report and wants to convert it into actionable guidelines.
Guideline Generation
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.
Inputs
Accept any combination of:
- Discovery report from the discover-brand skill (structured, pre-triaged)
- Brand documents uploaded or from connected platforms (PDF, PPTX, DOCX, MD, TXT)
- Conversation transcripts from Gong, Granola, manual uploads, or Notion meeting notes
- Direct user input about their brand voice and values
When a discovery report is provided, use it as the primary input — sources are already triaged and ranked. Supplement with additional analysis as needed.
Generation Workflow
1. Identify and Classify Sources
Determine what the user has provided. If no sources are available:
- Check if a discovery report exists from a previous
/brand-voice:discover-brandrun - Check
.claude/brand-voice.local.mdfor known brand material locations - Suggest running discovery first:
/brand-voice:discover-brand
2. Process Sources
For 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.
3. Synthesize Into Guidelines
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:
- Voice = personality, values, "We Are / We Are Not" — constant across all content
- Tone = formality, energy, technical depth — flexes by context
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]" |
4. Assign Confidence Scores
Score each section using the methodology in references/confidence-scoring.md:
- High confidence: 3+ corroborating sources, explicit guidance found
- Medium confidence: 1-2 sources, or inferred from patterns
- Low confidence: Single source, inferred, or conflicting data
5. Surface Open Questions
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.
6. Quality Check
Before presenting, verify via the quality-assurance agent (defined in agents/quality-assurance.md):
- All major sections populated (including Brand Personality and Content Examples if sources support them)
- At least 3 voice attributes with evidence
- "We Are / We Are Not" table has 4+ rows
- Tone matrix covers at least 3 contexts
- Confidence scores assigned per section
- Source attribution for all extracted elements
- No PII exposed
- Open questions include recommendations
7. Present and Offer Next Steps
Summarize key findings:
- Total sections generated with confidence breakdown
- Strongest voice attribute and most effective message
- Number of open questions (if any)
8. Save for Future Sessions
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.
- Resolve the save path. The file MUST be saved to
.claude/brand-voice-guidelines.mdinside the user's working folder. Confirm the working folder path before writing. - Check if guidelines already exist at that path
- If they exist, archive the previous version: Rename the existing file to
brand-voice-guidelines-YYYY-MM-DD.mdin the same directory (using today's date) - Save new guidelines to
.claude/brand-voice-guidelines.mdinside the working folder - Confirm to the user with the full absolute path: "Guidelines saved to
<full-path>./brand-voice:enforce-voicewill 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:
- Walk through the guidelines section by section
- Start creating content with
/brand-voice:enforce-voice - Resolve open questions
Privacy and Security
Enforce these privacy constraints throughout the entire generation workflow, not only at output time:
- Redact customer names and contact information from all examples
- Anonymize company names in transcript excerpts if requested
- Flag any sensitive information detected during processing
Reference Files
references/guideline-template.md— Complete output template with all sections, field definitions, and formatting guidancereferences/confidence-scoring.md— Confidence scoring methodology, thresholds, and examples
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
