setup-language

An interactive tool for documenting your personal writing style. It examines your existing articles, documentation, or commit messages, asks about your preferences, and creates a reusable style guide for Claude Code.

In plain words
What is it for?
Use it to create a writing-style skill from samples such as README files, technical guides, published articles, or Git commit messages.
Why use it?
It helps the coding agent write documentation and other text in your natural voice instead of applying generic writing advice.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/anilcancakir/claude-code-plugin/setup-language
Clone the repo
git clone --depth 1 https://github.com/anilcancakir/claude-code-plugin
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,781 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00016 $0.01781
Opus 5 $0.00008 $0.00890
Sonnet 5 $0.00003 $0.00356
Haiku 4.5 $0.00002 $0.00178

Measured yesterday against content hash 2fc36b05b600, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

setup-language scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

4. Verify paths via Bash (`test -f` or `test -d`). For URLs → fetch via Bash (`curl`)
plugins/ac/commands/setup-language.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Setup My Language Style

You are orchestrating an interactive session to build a personalized writing and documentation style skill. Analyze the developer's existing written content, interview them about voice preferences, then generate a skill at ~/.claude/skills/my-language/ using skill-creator.

Core Principles

  • Read before profiling: Extract voice patterns from actual writing samples first
  • Context-aware tone: Docs, articles, and commit messages each have different tone rules
  • Capture the voice, not grammar rules: HOW the person communicates, not generic writing advice
  • Preserve authenticity: Codify the developer's natural voice, not an idealized version

Phase 1: Discovery

  1. If $ARGUMENTS is a path → use as first sample source
  2. Ask for writing samples across categories:
    • "Share 1-3 sources that represent your writing voice"
    • Accepted formats:
      • Article URLs: Published blog posts, Medium articles, dev.to posts
      • Documentation paths: README files, docs/ directories, wiki pages
      • File paths: Markdown files, technical guides, tutorials
      • Git repos: Extract commit messages and PR descriptions automatically
  3. If no samples provided → skip to Phase 3 (pure interview mode)
  4. Verify paths via Bash (test -f or test -d). For URLs → fetch via Bash (curl)

Phase 2: Sample Analysis

  1. For each sample source (max 3), use Glob, Grep, and Read directly in the main context — no subagents. Extract:
    • Voice traits: Personal/formal, active/passive, sentence length average
    • Opening patterns: How sections/articles/docs begin
    • Transition phrases: Recurring connectors and segue patterns
    • Code introductions: How code blocks are introduced and followed up
    • Closing patterns: Abrupt, summary, call-to-action, or friendly
    • Signature expressions: Recurring phrases, verbal tics, characteristic word choices
    • Structure patterns: Section flow, heading hierarchy, list usage, callout usage
    • Tone differences: How tone shifts between documentation vs. articles vs. comments
    • Rhetorical devices: Questions, analogies, humor usage
    • Formatting habits: Bold/italic usage, table frequency, emoji usage
  2. Git availability check: run git --version to confirm git is installed, then git -C <path> rev-parse --git-dir to confirm the path is a git repo. If unavailable → skip commit/PR pattern extraction and note: "Git history unavailable — skipping commit style analysis."
  3. If a git repo is provided, additionally extract:
    • Commit message style (conventional commits? imperative? past tense?)
    • PR description patterns
    • Code comment voice
  4. Synthesize findings into a voice profile with direct quotes from the samples
  5. Present: "Here's your writing voice profile — confirm what's accurate and flag what to adjust"

Read the full file on GitHub · 182 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 182 lines · 16 tokens per session scan A 2fc36b05b600

Subscribe to this mod's changes

setup-language is a command published in the GitHub repository anilcancakir/claude-code-plugin (2 stars, last pushed 4mo ago), licensed MIT. It adds 16 tokens to every session and 1,781 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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