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Undo board strokes

undo_board
Destructive

Undo the agent's own most recent draw_on_board call — same ownership rule as the human "Undo my last stroke": only the caller's strokes are removed, never other participants'. One call = one batch (e.g. an arrow is one batch of 3 strokes). count undoes multiple previous batches (1-10). Broadcasts board-remove so connected clients drop those ids; get_board_state stops returning them.

Input Schema

NameRequiredDescriptionDefault
countNoHow many of the agent's previous draw calls (batches) to undo. Default 1, max 10.
roomIdYesThe room ID whose board to edit.
senderIdNoThe agent identity whose strokes to undo (must match the senderId used in draw_on_board). Defaults to "mcp-agent".
agentSecretNoOptional agent credential (8-128 chars). Must match the secret that claimed this senderId. REQUIRED on a locked pond.

Output Schema

NameRequiredDescriptionDefault
idsYes
noteYes
roomIdYes
removedYesStroke count removed
aiUserIdYes
deliveredYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / agentSecret
      Added value: +{
      +  "description": "Optional agent credential (8-128 chars). Must match the secret that claimed this senderId. REQUIRED on a locked pond.",
      +  "maxLength": 128,
      +  "minLength": 8,
      +  "type": "string"
      +}
  2. Added

TDQS

A4.4/5.0
Behavior5/5

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

Goes well past the annotations (destructiveHint=true, idempotentHint=false) by disclosing exactly what is destroyed — only the caller's strokes, never other participants' — and the batch granularity of a single undo. It also describes side effects: a board-remove broadcast to connected clients and the fact that get_board_state stops returning those ids.

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?

The ownership rule and inverse-of-draw_on_board framing are front-loaded, followed by the batch/count semantics and the broadcast effect. Three dense sentences with no filler, each carrying distinct information.

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?

With an output schema present, return values need not be explained, and auth requirements are covered by the parameter descriptions. The one gap is behavior when there is nothing left to undo (error vs. silent no-op), which matters for a non-idempotent destructive tool.

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?

Schema coverage is 100%, so roomId, senderId, and agentSecret are already fully documented, and the description's note that `count` undoes multiple previous batches largely restates the schema's own '(batches)' wording. The batch-vs-stroke mental model is a mild addition, so baseline 3 is appropriate.

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 and resource ("Undo the agent's own most recent draw_on_board call") and explicitly defines the ownership scope ("only the caller's strokes are removed, never other participants'"). An agent can distinguish this from remove_strokes or clear_board by the 'own most recent batch' semantics 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 Guidelines4/5

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

Clearly frames usage as the inverse of draw_on_board and explains that `count` handles multiple prior batches, giving a concrete when-to-use rule. It does not explicitly route away from siblings like remove_strokes (arbitrary stroke removal) or clear_board, so the alternative-selection guidance is implicit rather than complete.

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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