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load_skill

Load complete skill instructions on demand after confirming relevance from metadata, reducing token usage by fetching details only when needed.

Instructions

Load the complete instructions for a skill. Use this when you've decided a skill is relevant based on the skill metadata in your system prompt. Returns the full SKILL.md content without frontmatter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skill_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.3

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that it returns the full SKILL.md content without frontmatter, which is a key behavioral detail. However, it doesn't mention whether the operation is read-only, any permissions needed, or behavior on failure (e.g., if the skill doesn't exist). It gives some transparency but not exhaustive detail.

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 concise sentences that immediately state the action and return value, then provide the usage condition. Every word earns its place, and the 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?

For a simple one-parameter tool with an output schema, the description covers the core purpose, the trigger condition, and the return format. It lacks details about error handling or edge cases, but given the simplicity and the presence of an output schema, it is fairly complete. An agent can call it correctly based on this description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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

The schema has 0% description coverage for the only parameter, skill_name. The description does not explicitly define what skill_name is or its format, only implying it's the skill identifier from metadata. There are no examples or constraints, so the agent must infer the expected value. This is a significant gap given the low schema coverage.

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 action ('Load') and the resource ('complete instructions for a skill'), and specifies that it returns 'the full SKILL.md content without frontmatter'. This distinguishes it from sibling tools like fetch_resource (generic resource retrieval) and read_skill_file (likely reading a specific file), making its purpose unambiguous.

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?

It provides an explicit condition for use: 'when you've decided a skill is relevant based on the skill metadata in your system prompt'. This tells the agent when to invoke it, though it doesn't explicitly mention alternatives or when not to use it. The guidance is clear enough to avoid misuse.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.