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haydermuhib

Antigravity MCP Orchestrator

by haydermuhib

get_skill

Retrieves complete instructions, YAML frontmatter, procedures, scripts, references, and examples for a named Antigravity skill so agents can load guidance on demand.

Instructions

Retrieves the complete instructions (SKILL.md), YAML frontmatter, procedures, and associated scripts/references/examples for a specific Antigravity skill.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skill_nameYesName or directory identifier of the skill (e.g. 'bento', 'subagent-driven-development', 'deslop', 'systematic-debugging').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries full behavioral burden. It discloses the payload shape (complete instructions plus scripts/references/examples), which usefully signals a potentially large read-only response, but says nothing about permissions, unknown-skill-name behavior, or output size limits.

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?

A single front-loaded sentence beginning with the action verb, with the returned content grouped at the end. Efficient, though slightly dense in its enumeration of artifacts.

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 and no annotations, the description compensates by enumerating the returned content and identifying the tool as a details retriever. Missing only error/precondition context for an invalid skill name.

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% and the single skill_name parameter is well documented with real examples ('bento', 'deslop'). The description adds only the notion of "a specific skill" as the lookup key, so it does not meaningfully exceed what the schema already provides.

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 ("Retrieves") plus a specific resource ("a specific Antigravity skill") and enumerates what comes back (SKILL.md, frontmatter, procedures, scripts/references/examples). This clearly distinguishes a single-skill fetch from the sibling list_skills/search_skills, but it never names those alternatives explicitly.

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

Usage Guidelines3/5

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

The phrase "for a specific Antigravity skill" implies this is the detail-fetch step after discovery via list_skills/search_skills, but no when-to-use, when-not, or prerequisite is stated. Guidance is inferable rather than explicit.

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