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How an ingestion request is going

get_ingestion_request
Read-onlyIdempotent

State, stage, reason code and the time to wait before asking again, for one request you made. States: already_available, queued, running, available, partial, needs_clarification, needs_source_approval, failed, confirmed_unavailable. A fetch that timed out is failed and will be retried; confirmed_unavailable is the publisher itself saying it does not hold that manifestation, which is a different fact. Readable only by the account that made the request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYesThe request_id request_ingestion returned.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds important behavioral detail: the meaning of each state, the distinction between 'failed' (will be retried) and 'confirmed_unavailable' (publisher does not hold the manifestation), and the account-level read restriction. This is genuinely valuable context for the agent.

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?

The description is dense but well-organized: the first sentence states the core purpose, the second explains critical state semantics, and the third covers access control. Every sentence earns its place with no repetition or filler.

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

Completeness5/5

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

Given the presence of an output schema, robust annotations, a single required parameter, and the detailed state semantics in the description, the agent has everything needed to call this tool correctly and interpret its response. The only minor absence is an explicit pointer to get_ingestion_result for retrieving the final result, but that is not necessary for completing the description.

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 the schema already fully documents request_id. The description adds the context that it is 'one request you made' and that readability is account-scoped, but these are not parameter-specific semantics beyond what the schema communicates.

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 description clearly identifies the tool as returning state, stage, reason code, and wait time for a single ingestion request. It is specific and informative, but it does not explicitly differentiate itself from the sibling tool get_ingestion_result, so it falls short of a 5.

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

Usage Guidelines3/5

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

The description implies polling usage through 'time to wait before asking again' and notes the account restriction, but it does not explicitly state when to use this tool instead of get_ingestion_result or how to proceed once the state is available. Usage context is present but exclusions and alternatives are not.

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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