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sipyourdrink-ltd

Bernstein - Multi-agent orchestration

load_skill

Load detailed skill documentation and optional reference or script files when a skill index becomes relevant to the current task, providing contextual guidance without execution.

Instructions

Load a skill pack body (and optionally a reference or script).

    Agents receive only a compact skill index in their system prompt.
    Call this tool to fetch the full ``SKILL.md`` body for a skill
    when you decide it's relevant to the current task. Pass
    ``reference`` to get a deeper-context file or ``script`` to read
    the content of an executable helper.

    Args:
        name: Skill name (matches the index entry, e.g. ``"backend"``).
        reference: Optional filename under ``references/`` — for
            example ``"python-conventions.md"``.
        script: Optional filename under ``scripts/`` — for example
            ``"lint.sh"``. The script content is returned as text; the
            MCP harness does not execute it.

    Returns:
        JSON with ``name``, ``body``, ``available_references``,
        ``available_scripts``, and the optional fetched content.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
referenceNo
scriptNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations exist; description compensates fully by noting script is not executed, return structure, and read-only nature. Provides safety and behavior details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections for args and returns, but slightly verbose. Could be tightened without losing clarity.

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

Completeness5/5

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

Given output schema existence (described in returns), the description covers purpose, parameters, behavior, and return format completely.

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

Parameters5/5

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

Zero schema description coverage; description explains each parameter's role (name, reference path, script path) and script non-execution, adding essential meaning.

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?

Clearly states the tool loads a skill pack body and optionally references/scripts, distinguishing it from the compact skill index. Explicitly lists optional filenames.

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?

Specifies when to use: when a skill is deemed relevant. Does not explicitly mention alternatives or when-not, but sibling tools are unrelated, making context clear.

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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