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submit_relevance_extraction_batch

Submit a bounded batch of relevance judgments and structured signal extractions from documents, validating exact spans and returning per-item success/failure for retry.

Instructions

Submit a bounded batch of combined host relevance judgments and structured signal extractions. This is the normal autonomous high-volume path: each document is read once, exact spans are validated unchanged, and per-item success/failure is explicit and idempotently retryable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes
run_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses single-read semantics, unchanged exact-span validation, explicit per-item success/failure, and idempotent retryability. These are genuinely useful behavioral traits, though it omits auth requirements and bounds/limits on batch size.

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?

Two tightly-packed sentences that front-load the action and then the operating characteristics, with no filler. Slightly dense but every clause carries information.

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?

Output schema exists, so return values need not be described, and the behavioral prose is solid. But for a batch submit tool with zero schema coverage and no annotations, the absence of any item-shape or run_id guidance leaves a real gap for correct invocation.

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% for two required parameters, so the description must compensate. It never explains what run_id identifies or what the items array should contain (shape, span format, judgment fields), leaving the caller to infer everything from an opaque schema.

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 ('Submit') and resource ('bounded batch of combined host relevance judgments and structured signal extractions'), and the 'combined' framing distinguishes it from the separate classify_document_relevance and submit_extracted_signals siblings. It stops short of naming those siblings explicitly, so it lacks full differentiation.

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 phrase 'normal autonomous high-volume path' implies this is the default bulk route and contrasts with some non-normal path, giving an agent usable routing context. However, it never names an alternative or states a when-not condition, so the guidance remains implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.