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brand-voice

Build a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows. Use when the user wants voice consistency without generic AI writing tropes.

brand-voice とは?

brand-voice is a Claude Code agent skill that build a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows. Use when the user wants voice consistency without generic AI writing tropes.

対応~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/brand-voice

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ドキュメント

Brand Voice

Build a durable voice profile from real source material, then use that profile everywhere instead of re-deriving style from scratch or defaulting to generic AI copy.

When to Activate

  • the user wants content or outreach in a specific voice
  • writing for X, LinkedIn, email, launch posts, threads, or product updates
  • adapting a known author's tone across channels
  • the existing content lane needs a reusable style system instead of one-off mimicry

Source Priority

Use the strongest real source set available, in this order:

  1. recent original X posts and threads
  2. articles, essays, memos, launch notes, or newsletters
  3. real outbound emails or DMs that worked
  4. product docs, changelogs, README framing, and site copy

Do not use generic platform exemplars as source material.

Collection Workflow

  1. Gather 5 to 20 representative samples when available.
  2. Prefer recent material over old material unless the user says the older writing is more canonical.
  3. Separate "public launch voice" from "private working voice" if the source set clearly splits.
  4. If live X access is available, use x-api to pull recent original posts before drafting.
  5. If site copy matters, include the current ECC landing page and repo/plugin framing.

What to Extract

  • rhythm and sentence length
  • compression vs explanation
  • capitalization norms
  • parenthetical use
  • question frequency and purpose
  • how sharply claims are made
  • how often numbers, mechanisms, or receipts show up
  • how transitions work
  • what the author never does

Output Contract

Produce a reusable VOICE PROFILE block that downstream skills can consume directly. Use the schema in references/voice-profile-schema.md.

Keep the profile structured and short enough to reuse in session context. The point is not literary criticism. The point is operational reuse.

Affaan / ECC Defaults

If the user wants Affaan / ECC voice and live sources are thin, start here unless newer source material overrides it:

  • direct, compressed, concrete
  • specifics, mechanisms, receipts, and numbers beat adjectives
  • parentheticals are for qualification, narrowing, or over-clarification
  • capitalization is conventional unless there is a real reason to break it
  • questions are rare and should not be used as bait
  • tone can be sharp, blunt, skeptical, or dry
  • transitions should feel earned, not smoothed over

Hard Bans

Delete and rewrite any of these:

  • fake curiosity hooks
  • "not X, just Y"
  • "no fluff"
  • forced lowercase
  • LinkedIn thought-leader cadence
  • bait questions
  • "Excited to share"
  • generic founder-journey filler
  • corny parentheticals

Persistence Rules

  • Reuse the latest confirmed VOICE PROFILE across related tasks in the same session.
  • If the user asks for a durable artifact, save the profile in the requested workspace location or memory surface.
  • Do not create repo-tracked files that store personal voice fingerprints unless the user explicitly asks for that.

Downstream Use

Use this skill before or inside:

  • content-engine
  • crosspost
  • lead-intelligence
  • article or launch writing
  • cold or warm outbound across X, LinkedIn, and email

If another skill already has a partial voice capture section, this skill is the canonical source of truth.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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