Mixer AI

Summarize batch results and progress

aimixer_batch_summary

Read-onlyIdempotent

Read progress and account-owned results for up to ten independently submitted scenes using the original batch and scene IDs. Recover lost responses and report partial success or refunds. Never starts another job or debits coins.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "batch_id": "<batch_id>",
      "scenes": "<scenes>"
    },
    "name": "aimixer_batch_summary"
  }
}

Input Schema

Name	Required	Default
`lang`	No	en
`scenes`	Yes
`batch_id`	Yes

Output Schema

Name	Required	Description	Default
`ok`	Yes
`state`	Yes
`counts`	Yes
`scenes`	Yes
`batch_id`	Yes
`read_only`	Yes
`retry_plan`	Yes
`scene_count`	Yes
`partial_results`	Yes
`next_poll_seconds`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 1, 2026

TDQS

A4/5.0

Behavior4/5

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

Adds useful behavior beyond annotations: account-owned results, original IDs, max ten scenes, recovery of lost responses, partial-success/refund reporting, and no coin debit. Annotations already cover read-only and non-destructive safety, so this is strong supplementary context.

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 tight sentences, front-loaded with the core read operation, followed by recovery behavior and safety boundaries. No wasted text.

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?

Given read-only annotations, an output schema, and a moderate nested schema, the description gives enough context to call the tool correctly for its main purpose. The main gap is that optional parameters are not described.

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 0%, so the description must explain parameters. It covers the core batch_id and scene_id semantics ('original batch and scene IDs', 'up to ten independently submitted scenes'), but does not explain the optional lang or request_id fields.

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: reading progress and account-owned results for a batch of scenes using original IDs. It clearly distinguishes itself from job-starting siblings by saying it never starts another job or debits coins, though it does not name batch_status as the closest alternative.

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?

Provides clear usage context: recover lost responses and report partial success or refunds. The exclusion 'Never starts another job or debits coins' helps avoid misuse, but no sibling tool is explicitly named for comparison.

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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