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corpus

vela.corpus.ground_claim

vela.corpus.ground_claim
Read-only

Ground a claim in the corpus: hybrid semantic + theme retrieval over real passages, returning citations with source, passage code, scores, and a SHORT snippet. Use to check whether the corpus supports, complicates or is silent on an assertion. COSTS a small amount (one embedding per call).

[capability: corpus-ingestion-dual-grade · mirrors: internal — lib/audit/retrieve.ts]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYesThe claim to ground.
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hitsYes
claimYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond annotations: it notes the tool performs real-passage retrieval, returns a short snippet, and costs 'a small amount (one embedding per call).' This helps the agent anticipate side effects and output character.

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 compact and front-loaded: the first sentence states the action and output, the second sentence states the usage, and the third sentence warns about cost. The capability/mirror metadata is supplementary but not bloated. Every sentence earns its place.

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 only two simple parameters, an output schema, and annotations that cover read-only/destructive behavior, this description is complete. It explains the purpose, mechanism, return contents, usage scenario, and cost. Nothing critical is missing for an agent to decide whether and how to call this tool.

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?

The schema describes the 'claim' parameter but not 'limit', providing 50% coverage. The description adds no new parameter-level detail beyond the schema, and the default/max/min on 'limit' are self-explanatory. This is an adequate but not exceptional level of parameter guidance.

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?

The description uses a specific verb ('ground') with a clear resource ('a claim in the corpus') and explains the mechanism ('hybrid semantic + theme retrieval over real passages') and output ('citations with source, passage code, scores, and a SHORT snippet'). It clearly positions this tool as distinct from siblings by focusing on claim verification against corpus passages.

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?

The description explicitly states the intended use case: 'Use to check whether the corpus supports, complicates or is silent on an assertion.' This gives clear context for when to invoke the tool, though it does not explicitly name alternative sibling tools or state when not to use it.

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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