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analyzeProjectStack

Analyzes package.json files to detect project technology stacks and recommend relevant coding skills for AI agents.

Instructions

Analiza el package.json y recomienda skills según el stack detectado.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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 mentions analysis and recommendation but doesn't specify whether this is a read-only operation, if it requires authentication, how it handles errors (e.g., missing package.json), or what the output format looks like. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 a single, efficient sentence in Spanish that directly states what the tool does. It uses clear language ('Analiza el package.json y recomienda skills según el stack detectado') with no wasted words or redundancy, making it highly concise and well-structured.

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

Completeness2/5

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

Given the complexity (analysis and recommendation based on package.json), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'skills' are, how recommendations are generated, the format of the output, or error handling. For a tool that performs non-trivial operations, more context is needed to guide effective use.

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 tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to compensate for any parameter gaps, and it appropriately focuses on the tool's purpose without unnecessary parameter details. A baseline of 4 is applied for zero-parameter tools when the schema is fully covered.

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

Purpose4/5

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

The description clearly states the tool's purpose: analyzing package.json and recommending skills based on the detected stack. It uses specific verbs ('analiza', 'recomienda') and identifies the resource (package.json). However, it doesn't explicitly differentiate from sibling tools like 'findSkills' or 'selectSkill', which may have overlapping functionality.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a package.json file), exclusions, or how it differs from siblings like 'findSkills' (which might search for skills) or 'selectSkill' (which might choose from recommendations). Usage is implied but not explicitly 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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