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Collect a change list

get_change_list
Read-only

Collect the result of record_screen or convert_video_link by job id. Waits up to 50 seconds; call it again while it says it is still working. Also accepts a tellscreen.com/v/ link to fetch the change list of an existing Tellscreen video.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

NameRequiredDescriptionDefault
jobNoThe job id returned by record_screen or convert_video_link.
video_urlNoOr: a tellscreen.com/v/… link (keep any ?agent= in it).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the description's job is to add operational detail — and it does: a 50-second wait budget and the need to re-invoke while the job reports in-progress. That is exactly the non-obvious behavior an agent needs. It does not say what happens on timeout, job expiry, or failure, which keeps it from a 5.

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 short sentences, front-loaded with the primary use (collect by job id), followed by the polling behavior and then the alternate input. No redundant or filler wording; each sentence carries 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?

For an async-poll tool with no output schema, it covers the essential mechanics: what it collects, how long it waits, and that repeated calls are expected. It leaves the returned change-list structure and failure/timeout behavior unexplained, which is the main remaining gap.

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 description coverage is 100%, so both parameters (job id and video_url with the ?agent= preservation note) are already documented in the schema. The description only restates that the job id comes from the two producer tools and that a tellscreen.com/v/ link is accepted, adding little beyond the structured fields. 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 (collect) and resource (the change list result) and names the two sibling tools that produce the job id it consumes. An agent can tell this is the retrieval/polling counterpart to record_screen and convert_video_link without opening either schema, and the alternate video_url path is also called out.

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?

Gives clear trigger context ('the result of record_screen or convert_video_link') plus the crucial polling instruction: call again while it reports it is still working. It also covers the alternative entry point for existing videos. It stops short of explicit exclusions (e.g., whether it works for convert_local_video jobs or when not to poll), so it is strong but not 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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