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Wait for Clips

wait_for_clipping
Read-only

Poll an AI clipping job until COMPLETED or FAILED. Returns clips with output URLs. Do NOT use this when the live preview panel is rendered (it polls by itself) — only in hosts without the preview, or when the user explicitly asks for output URLs. Checks every 30 seconds until the job is COMPLETED or FAILED.

Input Schema

NameRequiredDescriptionDefault
clippingIdYes
maxAttemptsNo
intervalSecondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only say readOnly/openWorld=false; the description adds polling cadence (30s), the terminal states, and what is returned, which is real added value. Minor gap: 'Checks every 30 seconds' reads as a fixed cadence even though intervalSeconds is exposed (2–60), and nothing says what happens when maxAttempts is exhausted.

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?

Purpose is front-loaded and the exclusion clause follows immediately; every sentence carries routing or behavior information. Slight redundancy in stating 'until COMPLETED or FAILED' twice, which could be tightened into one sentence.

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

Completeness3/5

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

There is no output schema, and the description does cover the return ('clips with output URLs'), which is the most important piece. It omits how long the call can block, what a non-terminal/exhausted result looks like, and whether it errors on an invalid clippingId — meaningful gaps for a tool that may wait hours.

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 three parameters, so the description must carry the load and only partially does: the 30-second figure implies intervalSeconds' default, but maxAttempts (what it counts, its default, and the outcome when it runs out) and the format/validity of clippingId are entirely undocumented.

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?

States a specific verb and resource ('Poll an AI clipping job until COMPLETED or FAILED') plus the return payload ('clips with output URLs'). It does not explicitly distinguish itself from the sibling clipping_status tool, which is the nearest ambiguity an agent faces.

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

Usage Guidelines5/5

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

Gives explicit negative guidance ('Do NOT use this when the live preview panel is rendered') and names the two conditions under which it should be used (hosts without the preview, user explicitly asks for output URLs). This is about as close to definitive routing as a description gets.

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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