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Enhanciar: AI company brain

list_skills

List the team's recurring procedures ("skills") Enhanciar wrote up.

A skill is a step-by-step how-to (cut a release, onboard a customer) compiled from the wiki, written so an agent can follow it. Use this when someone asks "how do we usually do X", then read one with get_skill; for a one-off fact use query. It takes no arguments. Returns [{name, title, description, confidence, last_compiled, sources}]; an empty list means none are compiled yet (a person can run a compile in the Enhanciar app).

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

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 burden and does well: it declares the tool takes no arguments, describes the return fields, and explains that an empty list means nothing is compiled yet, with the remediation path (a person runs a compile in the app). It never explicitly frames the call as read-only/side-effect-free, which is the only remaining gap.

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 purpose, then the definition, then usage routing — a sensible order with no filler. Slight overlap remains in enumerating return fields even though an output schema already documents them.

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?

For a zero-argument list tool with an output schema present, everything an agent needs is covered: purpose, trigger, follow-up tool, alternative tool, and the meaning of an empty result with its remedy.

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 and the description confirms this explicitly ("It takes no arguments"), matching the empty schema. Baseline for a no-param tool applies; no additional parameter meaning is needed.

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 the team's recurring procedures") and defines what a skill is — a step-by-step how-to compiled from the wiki. It also implicitly distinguishes itself from get_skill (single read) and query (one-off fact), so an agent can identify it without opening the schema.

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 an explicit trigger phrase ("how do we usually do X"), names the follow-up tool (get_skill), and names the alternative for a different need (query for a one-off fact). Both the when-to-use and the when-to-use-something-else conditions are stated.

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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