Skip to main content
Glama

Discover Verse's skills by family

skill_discovery
Read-onlyIdempotent

Skill Discovery (asked by Verse): what skills Verse has and how they are spread across its families, for an agent that wants to know where to look before it asks. Gives each family's id, name, what it is for, how many skills it holds, its share of all of Verse's skills (the distribution), and the skills in it by name with their rating; ask for one family, or only the skills at a rating. Read from a-to-mind.com/skills/families.json, rated from evidence only. Ask a skill by name through ask_void or the skill's own tool.

Input Schema

NameRequiredDescriptionDefault
tierNoOnly skills rated at least this high.
familyNoOnly this family (an id from the result, e.g. numbers).
response_typeNoWhat to get back: 'text' (default) or 'raw_data' (the structured result as JSON). 'image' is not offered yet.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real context: the backing source (a-to-mind.com/skills/families.json), that ratings come 'from evidence only', and that the 'image' response type is not yet offered. It omits pagination or result-size behavior.

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?

Purpose and scope are front-loaded in the opening clause, and there is no filler. The core sentence is very dense, enumerating five return fields in one breath, which makes it slightly harder to parse than it needs to be.

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?

With no output schema, the description carries the return-value burden and does so well: family id, name, purpose, count, share of distribution, and member skills with ratings. Missing only edge behavior such as invalid family ids or any limits on result size.

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?

Schema coverage is 100%, so a 3 baseline applies and the description only needs to add meaning. It does: 'rated from evidence only' explains what the tier scale represents, and 'image is not offered yet' pre-empts a valid enum value the agent might otherwise try.

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 ('what skills Verse has and how they are spread across its families') and immediately scopes it as a pre-query discovery tool. It is clearly distinguishable from the sibling skill_* tools, which each expose a single skill, and from ask_void, which is the actual interrogation path.

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?

Gives both the condition for use ('for an agent that wants to know where to look before it asks') and the alternative path ('Ask a skill by name through ask_void or the skill's own tool'). The filter conditions ('ask for one family, or only the skills at a rating') are stated too, so the routing decision is fully specified.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.