Skip to main content
Glama

check_verdict

Read-only

Retrieve a complete verification verdict by report ID, including score, tier, and fail codes. Choose between machine-readable agent output or human-readable customer explanations.

Instructions

Retrieve an existing VOP verification verdict by report ID.

Use the report_id returned by verify_output to fetch full verdict details.

Args: report_id: The verification ID returned by verify_output (the report_id field). audience: Response detail level. "agent" (default) — machine-readable verdict for agent consumption. "customer" — adds human-readable explanations for presenting results to end users. Do not use "admin" — it is reserved for platform operators only.

Returns: dict with keys: report_id, verdict, score, tier, fail_codes, issued_at (ISO 8601), settlement (always None), agent_performance

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audienceNoagent
report_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description's 'Retrieve' verb is consistent. It adds valuable behavioral context: the settlement field is always None, the audience parameter has specific restrictions, and it lists the return keys. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise, but includes a Returns section that lists keys. It is well-structured with clear sections (purpose, usage, args, returns). It could be slightly more concise, but the structure aids readability.

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, the description effectively covers the tool's purpose, parameter usage, and return values. It provides enough context for an AI agent to understand when and how to use the tool, and what to expect from the response.

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?

With 0% schema description coverage, the description fully compensates. It explains report_id as 'the verification ID returned by verify_output', and audience details the 'agent' and 'customer' values with their purposes, plus a warning against 'admin'. This adds significant meaning beyond the bare 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 description specifies 'Retrieve an existing VOP verification verdict by report ID', using a clear verb and resource. It distinguishes this tool from siblings like verify_output (which creates a verification) and list_verifications (which lists), making the purpose unambiguous.

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 to use the report_id returned by verify_output, providing clear context for when to invoke this tool. It also offers guidance on the audience parameter, warning against using 'admin'. While it doesn't explicitly list when not to use or alternatives, the context is sufficient for correct selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/agenticsettleio/agenticsettle-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server