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archy_score

Compute a composite quality score for Python project structure based on modularity, acyclicity, depth, and equality. Optionally record results and compare against previous runs to detect regressions.

Instructions

Compute the composite quality score (modularity, acyclicity, depth, equality - geometric mean) for a Python project. Optionally append the result to .archy/history.jsonl and/or compare against the most recent recorded run as a regression gate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
internal_onlyNo
recordNo
strictNo
strict_toleranceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
overallYes
componentsYes
inputsYes
gateNo
Behavior4/5

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

Description discloses key behaviors: computation, optional file recording, and regression gate comparison. With no annotations, this provides sufficient behavioral context for a non-destructive main operation and side effects.

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?

Description is two sentences, front-loaded with core purpose, and every sentence adds value. No unnecessary words.

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?

Description covers primary function and key optional features. An output schema exists, so return values are not needed. However, 'internal_only' parameter is not addressed, which is a minor gap.

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?

Description adds meaning for 'record', 'strict', and 'strict_tolerance' via the regression gate mention, but does not explain 'internal_only'. Since schema descriptions are absent (0% coverage), the description should cover all parameters, leaving a 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?

Description explicitly defines the tool's verb (compute), resource (composite quality score), and specific metrics (modularity, acyclicity, depth, equality). It also distinguishes from sibling tools that focus on different aspects like archy_check or archy_cycles.

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?

Description implies usage for computing a quality score but does not provide explicit guidance on when to use this tool versus alternatives like archy_check or archy_cycles. No when-not or alternative comparisons are given.

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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