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jbacalso24

io.github.jbacalso24/mimry

by jbacalso24

mimry_feedback

Records local AI coding agent usage feedback to tune future repository search rankings and improve result relevance.

Instructions

Record local agent usage feedback for future ranking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootNo
notesNo
queryYes
missedNo
openedNo
changedNo
contextNo
ignoredNo
outcomeNounknown
suggestedNo
verificationNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

D1.8/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It doesn't say whether this is a write operation, whether it's idempotent, what permissions are needed, whether it has side effects, or how the feedback is stored or used. 'For future ranking' is the only hint, and it's too vague to be actionable. With 11 parameters and no annotations, this is woefully insufficient.

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 a single short sentence, so it's concise and front-loaded. However, its brevity is due to under-specification rather than efficient communication. It doesn't waste words, but it also doesn't provide enough information, so conciseness is somewhat moot.

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

Completeness1/5

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

Given the complexity of the tool (11 parameters, no annotations, 0% schema coverage, and an output schema that isn't described), the description is completely inadequate. It doesn't explain what the tool does, how to use it, what feedback to provide, or what happens as a result. An agent would be guessing at every step.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides no information about any of the 11 parameters. Critical fields like 'query' (required), 'outcome', and arrays like 'missed', 'opened', 'changed', 'ignored', 'suggested' are completely undocumented. The description doesn't even mention what kind of data should be provided. This is a severe gap that would likely lead to incorrect usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Record local agent usage feedback.' This communicates the basic purpose, but it doesn't distinguish this tool from any sibling (none of the listed siblings appear to be feedback tools, but there's no explicit differentiation). The word 'local' is vague, and 'for future ranking' hints at a downstream effect without explaining it. It's adequate but not specific enough to be strong.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool, when not to use it, or how it relates to alternatives. An agent would have to guess that this should be called after using other mimry tools, and there's no mention of prerequisites or timing. This is a significant omission for a feedback tool that likely has a specific place in a workflow.

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