mcpField
T
tellcheck

tellcheck

Local
github.com/CloudCorpRecordsProductivity0Updated 2w ago

About tellcheck

tellcheck is a local writing-style checker and deterministic AI-tell auditor for writers who want to assess voice and repetition. It offers editable style profiles and reports findings without network access or model calls.

Key features

  1. 01Compare voice rhythm and mechanics
  2. 02Train and manage style profiles
  3. 03Find repeated phrases and openers
  4. 04Audit AI-tells with located findings
  5. 05Manage word lists and instructions

Use cases

  1. 01Check a draft against a chosen voice
  2. 02Review text for repeated phrasing
  3. 03Scan copy for AI-associated wording
  4. 04Maintain style-specific word rules

MCP support

The MCP server exposes tools for managing styles and dictionaries, checking voice match and repetition, and auditing text. Its local `second_read` tool returns the documented failure because that feature requires a hosted model.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"cloudcorprecords-tellcheck": {
"command": "npx",
"args": [
"-y",
"@reneturcios/tellcheck"
]
}
}
}
Run commandnpx -y @reneturcios/tellcheck

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@reneturcios/tellcheck0.1.0
ocighcr.io/cloudcorprecords/tellcheck:0.1.0

Tools

20

Saved tool list · updated 1w ago

This tool takes no parameters.

Details

From the project README

tellcheck

Check a piece of writing against a voice style, and scan it for the tells that make prose read as machine-generated. Everything runs locally and deterministically: no network, no API key, no model calls. State (styles, dictionaries, instructions, default style) persists as JSON under TELLCHECK_HOME or ~/.tellcheck.

This is a clean-room rebuild of the etincel writing-style tool, implemented from its public README tool spec. Schemas are documented reconstructions from that prose.

What it does

  • Styles. Twelve shipped presets (Direct & Warm, Executive Brief, Reflective Essayist, Founder Memo, Plainspoken Analyst, Wry & Candid, PR Review, Code Comment, Slack Message, LinkedIn Post, Website Copy, Blog Post), each with formality / warmth / directness dials and a rhythm description. Train your own style from samples, create one directly from dials, fork, update, delete, and set a default.
  • Voice match. Compare a draft's rhythm and mechanics (sentence length and variance, contraction rate, em-dash use, fragments, questions) against a style baseline. Short input gets an honest low-confidence note instead of a false-precision score.
  • Self-repetition. Repeated sentence openers and phrases, including repetition against a trained style's own samples.
  • AI-tell audit. A deterministic scan: a built-in tell vocabulary with a suggested replacement for each hit (for example "comprehensive", "cutting-edge", "leverage", "seamless", "streamline"), rhythm findings (uniform paragraph length, low burstiness), and strengths (specificity, concrete-to-abstract balance). Returns a tier — green, yellow, orange, or red — plus a 0–100 score and findings with locations. Registers: email, blog, memo, essay, social, docs, general, personal; the docs register suppresses markdown-structure findings. Supplying sourceFacts flags numbers in the text that the facts do not back.
  • Dictionaries and instructions. Global and per-style banned-word and custom-word lists, plus free-form style instructions.
  • second_read, honestly. In the original, the local install's second read always fails with a clear explanation (the feature needs a hosted model). This rebuild reproduces exactly that behaviour rather than faking a result.

CLI

One subcommand per tool, taking a single JSON argument object:

npx @reneturcios/tellcheck list_styles '{}'
npx @reneturcios/tellcheck get_style_guide '{"styleId":"founder-memo"}'
npx @reneturcios/tellcheck train_style '{"name":"My Voice","samples":["..."]}'
npx @reneturcios/tellcheck audit_text '{"text":"...","register":"blog"}'
npx @reneturcios/tellcheck --version

Exit codes: 0 success, 1 tool error, 2 usage error.

MCP

npx -y @reneturcios/tellcheck mcp

MCP client config:

{
  "mcpServers": {
    "tellcheck": {
      "command": "npx",
      "args": ["-y", "@reneturcios/tellcheck", "mcp"]
    }
  }
}
Tools (20)
ToolPurpose
list_stylesPresets, trained styles, and the team style if defined
get_style_guideFull guide for one style
train_styleTrain a style from samples (rhythm, contractions, em dashes, paragraph variance)
create_style_from_dialsCreate a style from the eleven voice dials
update_styleRename a style or adjust its dials
fork_styleFork a local style (public-gallery forks return an honest error)
delete_styleDelete a user-created style
set_default_styleSet the default style
check_voice_matchRhythm/mechanics comparison against a style baseline
check_self_repetitionRepeated openers/phrases, including vs training samples
audit_textDeterministic AI-tell scan with tier, score, and located findings
second_readAlways fails locally, with the original's clear explanation
add_banned_word / remove_banned_wordManage banned words (global or per style)
add_custom_word / remove_custom_wordManage custom dictionary words
list_dictionaryDictionary scopes plus the merged effective list for a style
set_style_instructions / clear_style_instructions / get_style_instructionsFree-form style instructions

Docker

docker run -i ghcr.io/cloudcorprecords/tellcheck          # stdio MCP server
docker run --rm ghcr.io/cloudcorprecords/tellcheck list_styles '{}'

Development

npm install
npm run build   # tsc -> dist/
npm test        # tsx --test test/*.test.ts (temp TELLCHECK_HOME, no network)
npm run dev     # run the CLI from source

License

MIT — Copyright (c) 2026 Rene Turcios

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.