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record_feedback

Log approved or corrected skill assignments to refine scoring weights and learn prompt-to-skill synonyms, improving future routing accuracy.

Instructions

Record user routing corrections to refine scoring weights and learn prompt-to-skill synonyms. Behavior: Local SQLite update in <5ms. Idempotent. Usage Guidelines: Use after route_skill when a user approves or corrects a skill route. Parameters: query is the routed prompt; chosenSkillId is the correct skill identifier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe original natural language prompt or task query that was routed by route_skill (required, non-empty string).
chosenSkillIdYesThe unique skill ID or skill name that correctly handles the query (required, non-empty string).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv1.0.1
    • changedInput schema / properties / chosenSkillId / description
      Previous value: -"The correct skill ID."New value: +"The unique skill ID or skill name that correctly handles the query (required, non-empty string)."
    • changedInput schema / properties / query / description
      Previous value: -"The prompt query that was routed."New value: +"The original natural language prompt or task query that was routed by route_skill (required, non-empty string)."
  2. First observedv0.1.0

TDQS

A4.5/5.0
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 behavioral burden. It discloses that this is a 'Local SQLite update', that it is 'Idempotent', and gives a performance expectation of '<5ms'. This goes beyond a generic 'records feedback' and provides meaningful side-effect and safety context, though it doesn't describe error/failure behavior.

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 compact, front-loaded with purpose, and logically structured with labeled Behavior, Usage Guidelines, and Parameters sections. Every sentence contributes operational value, and the key usage condition is immediately actionable.

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?

For a two-parameter, no-output-schema, feedback-recording tool, the description is complete. It covers purpose, when to invoke it, side-effect characteristics (idempotent local update), and parameter meanings in context. No critical operational detail appears to be missing.

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 100%, so the baseline is 3. The description restates 'query is the routed prompt; chosenSkillId is the correct skill identifier', but this adds minimal semantic value beyond the schema. It reinforces the routing context but does not introduce new format, constraints, or examples.

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 a specific verb and resource: 'Record user routing corrections to refine scoring weights and learn prompt-to-skill synonyms.' This clearly differentiates it from siblings like route_skill (routing), get_skill/list_skills (retrieval), and scan_skills (scanning). The resource and high-level effect are unambiguous.

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

Usage Guidelines5/5

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

Explicitly states when to use the tool: 'Use after route_skill when a user approves or corrects a skill route.' This gives a clear trigger condition and a sequencing relationship to its primary sibling. It leaves no ambiguity about the intended invocation context.

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

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