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Veltake Studio

Apply the agent's proposal

apply_turn

Apply a turn's proposed canvas. With run:true also start the run the agent asked for — this SPENDS coins; pass expected_total (the turn's estimate.total_coins) so the charge cannot differ from the quote. Without expected_total, a host that can ask the person confirms the price with them. The agent reviews the results when the run finishes. A turn's cut_proposal (a large cut edit held for review) is applied separately, with cut_only:true.

Input Schema

NameRequiredDescriptionDefault
runNo
fundingNowho pays: personal (the person's own coins) or team (their team's pool — only when the person allowed this connection to spend team coins and the team approved this app). Omit to use the payer the person chose when connecting
turn_idYesfrom send_message
cut_onlyNo
expected_totalNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description discloses the decisive behavior: with run:true the call SPENDS coins. It also explains the expected_total safeguard that pins the charge to the quoted estimate and the fallback where a host confirms the price with the person. That is exactly the cost/consent context the annotations do not carry.

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 dense and front-loads the primary action before the conditional variants. A few sentences, notably 'The agent reviews the results when the run finishes,' are of marginal value, and the cost warning could have been surfaced even earlier, but overall it is efficient.

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 mutation tool with no output schema, it covers cost, consent, the async nature of the run, and the cut_proposal exception. It does not say what applying a turn returns or whether the action is reversible (undo_turn exists), which is a modest remaining gap.

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 only 40%, and the description compensates for the undocumented parameters: run (starts the run), expected_total (the turn's estimate.total_coins, quoted price lock), and cut_only (separate application of a cut_proposal). funding and turn_id are covered by the schema itself, so nothing important is left unexplained.

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 opening states a specific verb and resource: 'Apply a turn's proposed canvas,' and then extends it with the run:true and cut_only:true variants. It is distinguishable from siblings like start_run and estimate_run, though it never names them explicitly.

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?

It gives clear conditional guidance: use run:true when the run the agent asked for should also start, and use cut_only:true for a cut_proposal held for review, which is applied separately. There is no explicit 'when not to use' or named alternative, which keeps it below a 5.

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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