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record_quality_score

Record a quality score (0-100) for a major component to track improvement over time. Specify dimension and notes on measurement method.

Instructions

TRIGGER: Call this when finishing a major component to grade the output. 📊 Record quality score (0-100). Tracks improvement over time. Args: score: 0-100 dimension: One of: test_pass_rate, tool_availability, sync_latency, dedup_effectiveness, security, performance, readability, overall notes: What was scored and HOW (must include measurement method)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNo
scoreYes
dimensionNooverall

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description bears full responsibility. It mentions 'Tracks improvement over time' and argument constraints, but does not disclose side effects (e.g., overwriting previous scores), persistence, or idempotency. Adequate but lacks deeper behavioral context.

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 extremely concise: a one-line trigger, one-line purpose, and a structured 'Args:' section. Every sentence adds value with no redundancy. The most critical information is front-loaded.

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?

The description covers trigger, purpose, and all parameter constraints. An output schema exists, so return value details are not required. However, it does not mention error handling (e.g., invalid score) or prerequisites. For a simple record tool, this is largely complete.

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?

The input schema has 0% description coverage, so the description adds essential meaning: score range (0-100), dimension enum list, and notes requirement ('must include measurement method'). This surpasses the schema's defaults and titles, providing clear guidance for correct invocation.

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 purpose: 'Record quality score (0-100). Tracks improvement over time.' with a trigger 'Call this when finishing a major component to grade the output.' This distinguishes it from numerous sibling tools.

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 provides a clear trigger for usage: 'Call this when finishing a major component'. It does not explicitly exclude alternative tools, but the context suggests it is for recording scores, not analyzing or generating them. Sibling tools include many analytic and decision tools, so this guideline is sufficient.

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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