Catherine Ives-Yim: writing and assessments

Read-only search of Catherine Ives-Yim's writing on AI, IoT and the CRA, and scoring of four checks.

Should I use this

Quality & Safety

A
Description quality
100%
Schema completeness
82%
Naming quality
97%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~765Tokens (tool definitions)
~605 BTypical response size
Moderate attention impact (0.60% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "ives-yim": {
      "url": "https://ianuydptehkpowxqfivq.supabase.co/functions/v1/mcp"
    }
  }
}

Remote endpoints

https://ianuydptehkpowxqfivq.supabase.co/functions/v1/mcpstreamable-http

What it can do

Tool inventory

Tools (6)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢list_articles(theme, contains)

Catherine Ives-Yim's published articles (slug, title, standfirst, theme, publication label, address, length), optionally filtered by theme or a word in the title. Free to call; no model involved.

Input Schema

{
  "type": "object",
  "properties": {
    "theme": {
      "type": "string",
      "description": "Only articles in this theme (see list_themes)."
    },
    "contains": {
      "type": "string",
      "description": "Only articles whose title or standfirst contains this text (case-insensitive)."
    }
  },
  "additionalProperties": false
}
🟢list_themes

The themes the articles are grouped under, with counts.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢get_article(slug)

The full text of an article or site page by slug, with citation and source labels. About describes stated experience; Services describes the offering; articles describe published views. None is independent verification. Cite the address.

Input Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "The article slug from list_articles, or \"about\" or \"services\"."
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}
🟢search_articles(query, limit)

Keyword search over the bundled writing and site pages. Accepts questions or keywords, excludes further-reading sections, and returns a best passage per source before additional passages. Includes citation and source labels. Read get_article before making broader claims. No model is involved; this is retrieval, not an answer or independent verification.

Input Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Words or a short phrase. Up to 300 characters."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 12,
      "default": 6
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false
}
🟡list_assessments(pack)

The free questionnaire tools on the site and, for one of them, its full question set: modules, questions, answer anchors or options, and the conditions under which a question applies. Use this to put the questions to a user before calling score_assessment.

Input Schema

{
  "type": "object",
  "properties": {
    "pack": {
      "type": "string",
      "description": "A pack id (ladder, snapshot, strategy, cra) to get its questions; omit for the list."
    }
  },
  "additionalProperties": false
}
🟢score_assessment(pack, answers)

Runs the same deterministic rules engine the website uses for one of the assessments and returns the headline, module scores, flags and the plan. No model is involved: the result is computed from published rules, exactly as a visitor to the site would get. Answers: scale questions take 0 to 3 (worst to best anchor) or "dk" for don't know; single-choice questions take the option value; multi-select questions take an array of option values, e.g. {"CTX-markets": ["eu", "uk"]}. Unknown question ids or invalid values are rejected with an error listing them. Unanswered questions lower confidence rather than the score, and the result carries an "evidence" field: with no scored questions answered the headline is "Not enough answers", and below half confidence the headline is marked provisional. The result is a diagnostic to guide a conversation, not advice.

Input Schema

{
  "type": "object",
  "properties": {
    "pack": {
      "type": "string",
      "enum": [
        "ladder",
        "snapshot",
        "strategy",
        "cra",
        "cto"
      ]
    },
    "answers": {
      "type": "object",
      "description": "Question id to answer.",
      "additionalProperties": true
    }
  },
  "required": [
    "pack",
    "answers"
  ],
  "additionalProperties": false
}

Community

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Evidence

Recent observations

verifiedversion not recorded6 tools