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Update article

update_article

Update article text content from markdown. Use <SCREENSHOT {id}> placeholders to position screenshots. Screenshots in the markdown are kept. Screenshots removed from markdown are deleted. Order in markdown defines final order. Get the current article first with get_article, modify the markdown, then call this.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
markdownYesUpdated article content as markdown with <SCREENSHOT {id}> placeholders
project_idYesProject ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • removedInput schema / properties / context
      Removed value: -{
      -  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
      -  "type": "string"
      -}
    • removedInput schema / properties / conversation_id
      Removed value: -{
      -  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
      -  "type": "string"
      -}
    • removedInput schema / properties / llm_model
      Removed value: -{
      -  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
      -  "type": "string"
      -}
    • changedInput schema / required
      Previous value: -[
      -  "project_id",
      -  "markdown",
      -  "context",
      -  "llm_model"
      -]New value: +[
      +  "project_id",
      +  "markdown"
      +]
  2. Changed4 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
      +  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
      +  "type": "string"
      +}
    • addedInput schema / properties / conversation_id
      Added value: +{
      +  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
      +  "type": "string"
      +}
    • addedInput schema / properties / llm_model
      Added value: +{
      +  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
      +  "type": "string"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "project_id",
      -  "markdown"
      -]New value: +[
      +  "project_id",
      +  "markdown",
      +  "context",
      +  "llm_model"
      +]
  3. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  4. First observed

TDQS

B3.4/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses important behavioral details like screenshots in markdown being kept, removed screenshots being deleted, and markdown order defining final order. However, this directly contradicts the annotation destructiveHint: false, since deleting screenshots is a destructive side effect. Per scoring rules, contradiction forces a 1.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, with each sentence serving a purpose: what the tool does, how placeholders work, side-effect behavior, and usage workflow. It is well-structured and front-loaded, though slightly repetitive with the word 'markdown'.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter mutation tool with no output schema, the description covers the essential workflow, side effects, and ordering semantics. It doesn't mention return value or error handling, but those are less critical given the simplicity and the strong workflow guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema by explaining how markdown placeholders control screenshot positioning, preservation, deletion, and ordering. This enriches the markdown parameter's meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool updates article text content from markdown, giving a specific verb and resource. It doesn't explicitly differentiate from sibling tools like update_article_media or add_article_media, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit workflow guidance: get the article first with get_article, modify the markdown, then call this tool. This is clear contextual usage, but it doesn't mention when not to use it or name alternatives, so it misses the top score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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