Skip to main content
Glama

Get Source Evidence

get_source_evidence_v1
Read-onlyIdempotent

Fetch and hash-verify the raw source row behind a returned citation.

Pass a citation object inside params. Two ready-to-pass shapes come straight from the query tools: each aggregate row's citations[ref].verify object, or a detail record's citation (from include_records). Either proves the number with no re-query. The tool verifies the raw workbook SHA-256 before returning source-header row values. Use this when an agent must prove an answer from the underlying source row.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive. The description adds valuable behavioral details: it verifies the raw workbook SHA-256 before returning source-header row values, and states that it proves the number with no re-query. This goes beyond the annotations without contradicting them.

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 about 80 words and front-loaded with the core purpose. Each subsequent sentence adds necessary context: input shapes, verification behavior, and use case. No redundant information.

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?

Despite minimal schema, the description covers the purpose, input requirements, and behavioral outcome (verified source-row values). An output schema exists, so the description need not enumerate return fields. It is complete for an agent to select and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is nearly empty (params is an arbitrary object/null, 0% coverage). The description fully compensates by specifying exactly what to pass: a citation object from either citations[ref].verify or a detail record's citation from include_records. This is critical semantic information not present in the schema.

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 first sentence clearly states the action and target: 'Fetch and hash-verify the raw source row behind a returned citation.' It uses a specific verb and resource, and distinguishes from sibling query/describe tools by focusing on evidence retrieval for a citation.

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 says when to use it: 'Use this when an agent must prove an answer from the underlying source row.' It also explains the two input shapes from query tools, providing clear context. It doesn't explicitly list alternatives or exclusions, but the use case is unambiguous.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Each capability has a clearly named describe/query pair, and domains like power, AI infrastructure, robotics, and space are distinct. The generic describe_capability_v1/query_capability_v1 could be confused with the named variants, and the many ISO-specific interconnection queues share similar names, but descriptions explicitly disambiguate them.

Naming Consistency5/5

All tools follow a consistent lowercase snake_case verb_noun pattern: describe_<capability>_v1 and query_<capability>_v1, with a few utility tools like list_capabilities_v1 and get_source_evidence_v1. There is no mixing of conventions.

Tool Count2/5

At 62 tools, the set is far too large for typical server scope. The describe/query pairs inflate the count even though each is justified, and the generic capabilities plus per-ISO variants make it feel heavy and hard to navigate.

Completeness4/5

The server covers each domain thoroughly with describe, query, and evidence verification, plus generic fallbacks for capabilities not yet in the client's tool list. Minor gaps exist (e.g., no county/state attribution for some data, no load types in ISO queues) but they are explicitly documented and workable.

Resources