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selectSkill

Recommends the most relevant skill for a specific task by analyzing task descriptions to identify appropriate reusable instruction sets.

Instructions

Recomienda el skill más relevante para una tarea concreta

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesDescripción de la tarea para la que necesitas un skill
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 states the tool recommends a skill but doesn't explain how the recommendation is generated (e.g., based on criteria, rankings, or AI models), what the output format is (since no output schema exists), or any limitations like rate limits or authentication needs. This leaves key behavioral traits unspecified.

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, clear sentence in Spanish that directly states the tool's function without unnecessary words. It's front-loaded and efficiently conveys the core purpose, making it easy to parse and understand quickly.

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 of a recommendation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like how recommendations are made, what data is returned, or error handling. For a tool that likely involves ranking or selection logic, 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.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description implies the 'task' parameter is used to determine relevance, but it doesn't add meaning beyond the schema's description ('Descripción de la tarea para la que necesitas un skill'). With 100% schema description coverage, the baseline is 3, as the schema adequately documents the parameter without extra semantic value from the description.

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 'Recomienda el skill más relevante para una tarea concreta' clearly states the tool's purpose: recommending the most relevant skill for a specific task. It uses a specific verb ('recomienda') and resource ('skill'), making the intent understandable. However, it doesn't explicitly differentiate from sibling tools like 'findSkills' or 'analyzeProjectStack', which might have overlapping or related functions.

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, exclusions, or compare it to siblings such as 'findSkills' (which might list skills) or 'installSkill' (which might apply a skill). Without this context, an AI agent might struggle to choose between these tools appropriately.

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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