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speedofred

io.github.speedofred/ami-survey

by speedofred

ami_get_grading_scale

Retrieve the AMI output-quality grading scale before submitting results. Use it to confirm valid agent_output_grade codes, ensuring submissions pass validation.

Instructions

Return the AMI output-quality grading scale. Read this before grading: agent_output_grade must be one of its codes and is validated on submit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It lacks an explicit statement of no side effects or read-only status, though 'Return' suggests a safe getter. However, it adds meaningful normative context: the returned codes are validated at submit time, which signals the agent must treat the scale as authoritative. Missing output format/response shape is a typical gap here.

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?

Two sentences, arrest in front-loaded action first, second is a specific usage directive. There is no fluff, and every clause contributes (what, why, when).

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

Completeness4/5

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

For a no-parameter getter with no output schema, the description covers the essential: what the tool is for and how its output relates to a validation rule. Only principal missing piece is an example or format of the returned scale, but that is not critical for correct invocation.

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

Parameters4/5

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

There are zero parameters, so the schema coverage is trivially 100%. The description adds semantic value beyond that by explaining why the tool should be used (to obtain valid codes for agent_output_grade). Baseline 4 for a parameterless tool.

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?

States exactly what it does: returns the AMI output-quality grading scale. This is a specific resource with a specific verb, and no sibling tool overlaps with this responsibility; it's clearly distinct from ami_get_workflow_categories and ami_get_instructions.

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?

Gives explicit when-to-use guidance: 'Read this before grading' and explains why by noting agent_output_grade must use one of its codes and is validated on submit. It doesn't explicitly name alternatives or exclusions, but none are needed since this is the only source of the grading codes.

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