Writer Persona

writer-persona

A Claude Code plugin that extracts your writing persona from real messages, measures its accuracy, and writes in your voice.

The Problem

You want AI to write as you — in emails, Slack, code reviews. But how close is "close enough"? Without measurement, you're guessing.

The Solution

writer-persona creates a feedback loop: extract, measure, improve, write.

Bootstrap (analyze 100+ real messages)
    ↓
Backtest (AI writes drafts → compare with what you actually wrote)
    ↓
Score (8-axis linguistic evaluation)
    ↓
Auto-correct (fix the biggest gaps)
    ↓
Write (generate messages in your voice)

The AI never sees your actual response when generating drafts — it only gets the conversation context. This information isolation ensures honest evaluation.

Commands

| Command | What it does | |---------|-------------| | /writer-persona:writer-persona | Show persona status and score | | /writer-persona:writer-persona --bootstrap | Extract persona from 100+ real messages | | /writer-persona:writer-persona --backtest | Measure accuracy (last 24h by default) | | /writer-persona:writer-persona --backtest --days 7 | Measure over last 7 days | | /writer-persona:writer-persona --calibrate | Manual tuning with your feedback | | /writer-persona:writer-persona --write "context" | Write as you in a given situation | | /writer-persona:writer-persona --write | Interactive: describe the situation, get a draft |

> Note: When installed as a plugin, commands use the plugin-name:skill-name format. > If installed as a local skill (in .claude/skills/), use /writer-persona directly.

Key Features

• 8-axis evaluation grounded in computational stylometry research
• Self-similarity ceiling — your own writing varies; the AI is scored against your natural range, not perfection
• Data source agnostic — Slack, email, Discord, text files, or any MCP tool
• Language adaptive — English, Korean, Japanese, or any language
• Auto-convergence with overfitting guards (max 2 axes per run, stall detection)
• Write mode — the payoff: generate messages that sound like you

The 8 Axes

| Axis | Weight | What it measures | |------|--------|-----------------| | Semantic Fidelity | 25% | Does the draft say the right thing? | | Tone / Sentiment | 20% | Does it feel like you? | | Formality / Register | 15% | Right level of formal/casual? | | Discourse Patterns | 15% | How you structure responses | | Lexical Choice | 10% | Your characteristic vocabulary | | Function Words | 5% | Unconscious grammatical habits | | Sentence Structure | 5% | Length, complexity patterns | | Formatting | 5% | Emoji, punctuation, layout |

See [references/evaluation-rubric.md](references/evaluation-rubric.md) for the full framework and academic citations.

Installation

Via Plugin Marketplace (Recommended)

If the marketplace hosting this plugin is already added:

/plugin install writer-persona@

From GitHub

Add this repo as a marketplace source, then install:

/plugin marketplace add cosmos-makers/writer-persona
/plugin install writer-persona@writer-persona

Local Development

Test the plugin locally without installing:

git clone https://github.com/cosmos-makers/writer-persona.git
claude --plugin-dir ./writer-persona

Manual (Legacy)

Copy the plugin into your project's .claude/plugins/ directory:

git clone https://github.com/cosmos-makers/writer-persona.git
cp -r writer-persona /path/to/your/project/.claude/plugins/writer-persona

Quick Start

1. Extract your persona

/writer-persona:writer-persona --bootstrap

The skill asks you:

• Your name and language
• How to collect your messages (Slack MCP, paste, file, email MCP, etc.)
• Your situation categories (defaults provided)

Then it analyzes 100+ messages and builds a comprehensive writing persona.

2. Measure accuracy

/writer-persona:writer-persona --backtest

Finds recent conversations where you responded, generates AI drafts without seeing your answers, and scores them on 8 axes.

3. Write in your voice

/writer-persona:writer-persona --write "reply to Sarah's Slack message about the API deadline"

Or interactively:

/writer-persona:writer-persona --write

The skill asks who you're writing to, what the situation is, and generates a draft in your style.

Supported Data Sources

writer-persona is data source agnostic. On first run, it asks how you want to provide messages:

| Source | How | |--------|-----| | Slack | Via MCP tools (e.g., mcp-slack) | | Email | Via email MCP tools | | Discord | Via Discord MCP tools | | Manual | Paste messages or provide a file path | | Any MCP | Describe the tool and query pattern |

How Scoring Works

Self-Similarity Ceiling

Even you don't write identically every time. A quick "lol nice" and a detailed technical explanation are both authentically you — but they'd score poorly against each other.

The self-similarity ceiling measures this natural variation by scoring pairs of your own messages. A typical ceiling is 70-80. This becomes the 100-point baseline.

Information Isolation

The draft-generating agent never sees your actual response. It only receives your persona definition and the conversation context. This ensures the backtest measures real predictive ability, not copying.

File Structure

writer-persona/
├── .claude-plugin/
│   └── plugin.json             # Plugin manifest
├── skills/
│   └── writer-persona/
│       ├── SKILL.md            # Main skill definition
│       ├── persona.template.md # Blank persona template
│       ├── references/
│       │   └── evaluation-rubric.md  # 8-axis framework + citations
│       └── examples/
│           ├── persona-english.md    # Example: English persona
│           └── persona-korean.md     # Example: Korean persona
├── README.md
└── LICENSE

After running, the skill creates user-specific files (gitignored):

skills/writer-persona/
├── persona.md                  # Your persona (personal data)
└── reports/                    # Backtest reports

Academic Foundations

| Concept | Source | |---------|--------| | Function word stylometry | Burrows' Delta (2002) | | Multi-axis author identification | Writeprints, Abbasi & Chen (2008) | | Formality benchmarks | GYAFC, Rao & Tetreault (2018) | | LLM persona consistency | PersonaGym (EMNLP 2025) | | Semantic preservation | BERTScore, Zhang et al. (2019) | | Self-similarity baseline | TST 3-axis evaluation standard |

License

MIT

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: cosmos-makers
• Source: cosmos-makers/writer-persona
• License: MIT

Install and usage instructions live in the source repository linked above.