guideline-generation — скилл для Claude Code: суть и установка
Скилл собирает гайдлайны бренда и правила тональности из документов, отчётов и записей звонков. Пригодится, когда нужно зафиксировать голос компании для работы ИИ-агентов.
npx skills add anthropics/knowledge-work-plugins --skill guideline-generation -a claude-codeЧто делает guideline-generation
Скилл сводит разнородные материалы в структурированный документ с правилами тональности. В ход идут презентации, файлы PDF, заметки из Notion и расшифровки звонков из Gong или Granola. Для сложного парсинга текстов скилл привлекает субагент document-analysis, а распознавание речевых паттернов поручает агенту conversation-analysis.
На выходе формируется свод правил по шаблону references/guideline-template.md. Он включает таблицу «We Are / We Are Not» с подтверждениями из источников и матрицу тона под разные ситуации общения. Каждому разделу присваивается уровень достоверности: высокий статус требует явных инструкций минимум в трёх независимых источниках.
Готовый результат сохраняется в .claude/brand-voice-guidelines.md внутри рабочей папки, а прежняя версия автоматически архивируется с датой в имени. Если рабочая папка проекта не задана, файл не запишется на диск, а останется доступен только в памяти текущего диалога.
Какие задачи решает
- составить редполитику бренда на основе записей звонков и документов
- сформировать матрицу тональности под разные каналы коммуникации
- выявить противоречия в существующих материалах компании
- подготовить правила голоса бренда для проверки через
/brand-voice:enforce-voice
Примеры запросов агенту
- Собери гайдлайн голоса бренда на основе загруженных презентаций и звонков
- Сформируй правила тональности по недавнему discovery report
- Выдели голос бренда из файлов в папке и подготовь матрицу тона
Как установить guideline-generation
1Через Skills CLI (Vercel)
npx skills add anthropics/knowledge-work-plugins --skill guideline-generation -a claude-code2Вручную: положить файлы
~/.claude/skills/guideline-generation/SKILL.mdПапка скилла целиком; для одного проекта — .claude/skills/guideline-generation/
1Через Skills CLI (Vercel)
npx skills add anthropics/knowledge-work-plugins --skill guideline-generation -a codex2Вручную: положить файлы
.agents/skills/guideline-generation/SKILL.mdДля всех проектов — ~/.agents/skills/
1Через Skills CLI (Vercel)
npx skills add anthropics/knowledge-work-plugins --skill guideline-generation -a cursor2Вручную: положить файлы
.cursor/skills/guideline-generation/SKILL.mdCursor читает и .agents/skills/, и .claude/skills/
1GitHub CLI
gh skill install anthropics/knowledge-work-plugins guideline-generation2Вручную: положить файлы
.github/skills/guideline-generation/SKILL.md1Через Skills CLI (Vercel)
npx skills add anthropics/knowledge-work-plugins --skill guideline-generation -a gemini-cli2Командой платформы
gemini skills install https://github.com/anthropics/knowledge-work-plugins --path partner-built/brand-voice/skills/guideline-generationВручную: положить файлы
.devin/skills/guideline-generation/SKILL.mdСтарый путь .windsurf/skills/ тоже читается
Через Skills CLI (Vercel)
npx skills add anthropics/knowledge-work-plugins --skill guideline-generation -a opencodeClaude.ai
Упакуйте папку в zip и загрузите в Settings → Capabilities → Skills
Из того же набора133
Весь набор →Похожие
Вопросы о guideline-generation
Как установить guideline-generation в Claude Code?
Выполните команду npx skills add anthropics/knowledge-work-plugins --skill guideline-generation -a claude-code. Скилл сразу станет доступен в вашем терминале.
Куда сохраняются сгенерированные правила бренда?
Скилл записывает файл в .claude/brand-voice-guidelines.md внутри рабочей папки проекта. Если такой документ уже был, он переименовывается в архивный вид brand-voice-guidelines-YYYY-MM-DD.md.
Как скилл определяет уровень достоверности правил?
Оценка опирается на количество подтверждений в данных. Высокий уровень требует явных инструкций минимум в трёх источниках, средний ставится при наличии одного или двух документов, а низкий указывает на косвенные выводы или противоречия.
Исходный текст
SKILL.md · Apache-2.0
--- name: 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-brand` run - Check `.claude/brand-voice.local.md` for 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: ```markdown ## 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. 1. **Resolve the save path.** The file MUST be saved to `.claude/brand-voice-guidelines.md` inside the user's working folder. Confirm the working folder path before writing. 2. **Check if guidelines already exist** at that path 3. **If they exist, archive the previous version:** Rename the existing file to `brand-voice-guidelines-YYYY-MM-DD.md` in the same directory (using today's date) 4. **Save new guidelines** to `.claude/brand-voice-guidelines.md` inside the working folder 5. **Confirm to the user** with the full absolute path: "Guidelines saved to `<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: 1. Walk through the guidelines section by section 2. Start creating content with `/brand-voice:enforce-voice` 3. 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 guidance - **`references/confidence-scoring.md`** — Confidence scoring methodology, thresholds, and examples
© anthropics · Apache-2.0 · anthropics/knowledge-work-plugins