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speedofred

io.github.speedofred/ami-survey

by speedofred

ami_submit_survey

Submit survey results by providing a grade, justification, and evidence artifacts; persist them as JSON, Markdown, and CSV index, returning file paths.

Instructions

Submit and persist the survey. Requires a grade from the AMI grading scale, a justification, and evidence (the concrete artifacts produced). Writes JSON + Markdown + a CSV index row to disk and returns the paths.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
graderNo'self' when the agent grades its own output, 'human' or 'external_reviewer' when a person supplied the grade.
run_idNo
workflow_nameNo
grade_evidenceYesConcrete artifacts being graded: file paths, ticket ids, message ids, tool outputs.
workflow_end_timeNo
agent_output_gradeYesA grade code from ami_get_grading_scale.
grade_justificationYesWhy that grade, measured against the workflow's stated requirements. At least 40 characters.
workflow_descriptionNo
allow_empty_telemetryNoOnly for deliberately unmeasured runs; measurement fields will be null.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It explicitly discloses side effects: 'Writes JSON + Markdown + a CSV index row to disk and returns the paths.' This is significant behavioral transparency. It does not cover idempotency, failure modes, or overwrite behavior, but the key traits are stated.

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 with no filler. Purpose and side effects are front-loaded, making it easy for an agent to quickly understand what the tool does and what it returns.

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?

The tool has 9 parameters, no output schema, and no annotations. The description covers purpose, required inputs, side effects, and return paths, but lacks detail on optional parameters, validation rules, and error handling. For a submission tool with many parameters, more context would help, but the essentials are present.

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?

Schema description coverage is 56%, meaning 5 of 9 parameters have descriptions. The description reiterates the three required fields (grade, justification, evidence) but adds no new syntax or formatting details. It does not explain optional parameters like grader, run_id, workflow_name, or allow_empty_telemetry. It provides some added meaning for required fields but does not fully compensate for the coverage gap.

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 clearly states the tool's function: 'Submit and persist the survey.' It uses a specific verb (submit/persist) and resource (survey), and mentions side effects (writes files, returns paths). This distinguishes it from siblings like ami_survey_begin or ami_get_survey.

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 description implies usage by stating required inputs (grade, justification, evidence), suggesting it is the final step after grading. However, it does not explicitly state when to use it vs. other survey tools or mention any exclusions. Sibling tools like ami_survey_begin, ami_survey_status, and ami_get_survey exist, but no direct comparison is made.

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