static.md

Read a whiteboard

read_board

Read-only

Returns a static.md Excalidraw whiteboard the user can open: element count, element types, the text on the board, and the scene JSON (when under 300 KB). Board text is written by users and comes back marked as untrusted data. Encrypted boards are refused.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "read_board"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	The id at the end of the link, e.g. "k3v9qa" in https://static.md/md/k3v9qa

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 8, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Adds substantial context beyond the annotations: the 300 KB cap on returning scene JSON, the fact that user-authored board text is returned marked as untrusted data, and that encrypted boards are rejected. It does not say what happens above the size cap (truncation vs. omission), which is the one behavior an agent might trip on.

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

Conciseness5/5

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

Three sentences, front-loaded with the return payload, then size constraint, then security and refusal notes. No filler and no repetition of name or annotations.

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

Completeness5/5

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

No output schema exists, and the description enumerates the returned fields (element count, element types, board text, scene JSON) plus the size condition. For a single-parameter read tool nothing an agent needs in order to call it is missing.

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

Parameters3/5

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

Only one parameter and schema coverage is 100%, with the pattern and link-suffix example already documented in the schema. The description adds nothing about the id, so the baseline 3 applies.

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

Purpose5/5

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

States a specific verb (returns) and resource (a static.md Excalidraw whiteboard), then enumerates exactly what comes back. The whiteboard framing plus sibling names like read_note and create_board make the resource distinction unambiguous without opening a schema.

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

Usage Guidelines3/5

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

Usage is implied by the id-based read of a board, and 'Encrypted boards are refused' supplies one real exclusion. However, it never explicitly routes the agent between this and read_note/read_note_ciphertext, or says what to do when a board is encrypted.

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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