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runwhen-contrib

RunWhen Platform MCP

List Skills

list_skills

Discover every server-exposed skill's name, description, and URI before running a tool. Use it to see what guidance exists and decide which full skill to fetch.

Instructions

List every progressive-disclosure skill the server exposes.

Returns [{name, description, uri}]. Use this when you want to know what guidance is available before running a tool — read the description to decide whether you need the full body, then fetch it with get_skill(name) (or, if your client supports MCP resources directly, read the uri via the resource read API).

Cross-vendor note: this is the same information that list_resources returns for the runwhen-skill:// family. Clients that surface MCP resources should prefer that path; this tool is the explicit fallback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the return shape, the read-then-fetch workflow, and the cross-vendor equivalence/fallback relationship with list_resources. It stops short of noting caveats such as whether the listing is complete, paginated, or scoped, but the core behavioral profile is clear.

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?

Front-loaded with the core purpose, then the return shape, then the routing advice, so the important information comes first. The cross-vendor note is somewhat verbose but it is genuinely load-bearing because it steers clients to a different mechanism.

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?

An output schema already exists, so the description need not explain return values, yet it still names the fields for orientation. Combined with the explicit alternatives and fallback guidance, an agent has everything needed to call it correctly and act on the result.

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 takes zero parameters, which establishes the baseline of 4. There is nothing for the description to add on parameter meaning, and it correctly stays silent rather than inventing inputs.

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?

States a specific verb and resource ('List every progressive-disclosure skill the server exposes') and immediately distinguishes itself from the sibling get_skill by noting it is the enumeration step that precedes fetching. An agent can tell what it returns and how it differs from related tools.

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

Usage Guidelines5/5

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

Explicitly says when to use it ('when you want to know what guidance is available before running a tool'), names the follow-up alternative get_skill(name), and prescribes a preference order against list_resources for MCP-resource-capable clients, naming this tool as the explicit fallback.

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