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propose_recipe_edit

Propose a typed recipe edit by sealing a prediction before rendering, enabling schema-validated changes and honest rejection of out-of-contract input.

Instructions

Change the world through the typed vocabulary, sealing the prediction FIRST (§5.1: the seal is committed before the render exists). The word's param schema is the contract; anything outside it is refused at the door and the refusal is honest. The render that tests the prediction is requested separately (request_render), so the bet stays sealed before its test exists.

Input Schema

NameRequiredDescriptionDefault
nodeNo
wordYes
paramsYes
regionNo
predictionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It usefully discloses that unknown params are refused outright and the prediction is committed before a render exists — real behavioral traits. However, it never says whether the proposal is applied or merely queued for approval, what state changes result, whether it requires a node/region to exist, or what comes back.

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

Conciseness2/5

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

At three sentences it is short, but it is not front-loaded: the operative fact (this proposes a recipe edit) is never stated and the opening sentence is atmospheric filler. The parenthetical section reference (§5.1) costs space without helping an agent act.

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

Completeness2/5

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

A five-parameter mutation-style tool with nested objects, no annotations, no output schema, and zero schema descriptions needs the description to do heavy lifting. Instead it covers ordering and rejection semantics while leaving the argument shapes and result behavior undocumented.

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

Parameters2/5

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

Schema description coverage is 0% across five parameters. The description only gestures at `word` (its own param schema is the contract) and `prediction` (sealed first); it says nothing about `node`, `region`, the expected shape of `params`, or what a prediction object should contain.

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

Purpose2/5

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

The description opens with metaphorical framing ("Change the world through the typed vocabulary") rather than stating a plain verb+resource: that this proposes an edit to a recipe. The mechanics it does disclose (the seal ordering, the param schema as contract) are about side-constraints, not the core action, so an agent has to infer the purpose from the tool name alone.

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

Usage Guidelines2/5

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

It does name one sibling and a sequencing rule — the render is requested separately via request_render, so the bet is sealed before its test exists — which is genuine routing help. But there is no guidance on when to choose this over propose_plan_intention, file_work_order, or other siblings, and no prerequisites stated.

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