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Analyze Project

analyze_project

Scan a codebase to obtain a grounded architect-level analysis covering architecture, technologies, complexity, documentation coverage, and risks, with traceable recommendations.

Instructions

Scan a project (source tree, git history, package manifests, env files, existing docs) and return a grounded architect-level analysis: summary, architecture, technologies, complexity, documentation coverage, risk findings, and recommendations. Every claim traces back to a fact the scan actually computed — never fabricated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathYes
Behavior4/5

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

No annotations are provided, so the description must disclose behavioral traits. It states that the scan covers source tree, git history, manifests, env files, and docs, and importantly guarantees every claim is grounded in computed facts. It does not detail permissions or failure cases, but the read-only nature of a scan is clear, and the grounding claim adds valuable 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 two sentences with no filler. The first sentence efficiently packs the tool's scope and output list into one clause, and the second adds a concise quality guarantee. It is well-structured and 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?

For a one-parameter, read-only tool with no output schema, the description explains both the inputs and the return structure in sufficient detail. It could mention when not to use it relative to sibling tools, but that gap belongs to usage guidelines; the tool's functionality is fully described.

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?

With 0% schema description coverage, the description compensates by clarifying what a project consists of and implying the parameter is the path to the project root. It does not explicitly define projectPath syntax or absolute/relative semantics, but the context is sufficient for correct usage.

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 uses a specific verb ('Scan') and resource ('a project'), and enumerates both the input sources and the output fields of the analysis. It clearly distinguishes this holistic analysis tool from sibling tools that generate specific documents like README or changelog.

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 the tool is for obtaining a comprehensive, grounded project assessment and lists what it scans, but it does not explicitly state when to prefer this over sibling tools or mention any exclusions or prerequisites. The use case is inferable but not directly stated.

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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