RunWhen Platform MCP

Get Skill

get_skill

Retrieve a skill's full body and metadata by name, returning available skill names when unknown so agents can self-correct in one call.

Instructions

Return the full body of a skill by name.

Returns {name, description, uri, body, path} on success or {error, available} when the name is unknown so the agent can self- correct without a second round-trip.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "get_skill"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes	Skill name (e.g. 'build-runwhen-task'). Call list_skills first if you don't know the available names.
`reload`	No	Force re-read from disk (default: use cached version).

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 7, 2026

TDQS

B3.2/5.0

Behavior3/5

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

With no annotations, the description carries the burden, and it does add real value by disclosing the error path: an unknown name returns {error, available} so the agent can self-correct without a second call. However, it says nothing about permissions, side effects, or the cache/reload semantics beyond what the schema already documents.

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?

Two tight sentences with the core action front-loaded. The enumeration of return keys is somewhat redundant given an output schema exists, but the description stays short and readable.

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 two-parameter read tool with a full output schema, the description covers the essentials: what is returned, and what happens on failure. It is complete enough to call correctly, though a pointer to list_skills for discovery would close the remaining gap.

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?

Schema description coverage is 100%, so both the name and reload parameters are fully documented in the schema, including the list_skills fallback and the cache/re-read behavior. The description adds no additional parameter meaning, so the baseline 3 applies.

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?

States a specific verb and resource: 'Return the full body of a skill by name.' An agent can immediately tell this is a fetch-by-identifier operation. It does not explicitly differentiate itself from the sibling list_skills or render_codecollection_skill, so it falls short of a 5.

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 gives no when-to-use guidance, no prerequisites, and no named alternative (e.g. it never says to use list_skills when the name is unknown). The only routing hint, 'Call list_skills first', lives in the parameter schema, not the description.

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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