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Installed module/plugin spec

ansible_module_doc
Read-onlyIdempotent

Retrieve exact installed Ansible module or plugin options, defaults, aliases, and collection version before writing tasks; avoids version drift errors.

Instructions

Exact options (type, required, default, choices, aliases, suboptions) of a module or plugin as INSTALLED here (ansible-doc), with the collection version that provides it and redirects resolved. Use before writing a task; options drift between collection versions, so training-data guesses are often wrong.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dirNoAnsible project directory. Default: ANSIBLE_MCP_DIR, else the server's working directory.
nameYesFQCN or short name, e.g. community.general.ufw or ufw
typeNomodule | lookup | filter | test | callback | connection | inventory | become | cache | vars | strategy | shell | cliconf | httpapi | netconf | keywordmodule
include_returnNoList documented return values (modules)
include_examplesNoAppend the EXAMPLES block
description_charsNoTruncate each description to this many characters; 0 = no limit (default 160)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.2/5.0
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 adds meaningful behavior: redirects are resolved and the providing collection version is included, which matters for version-drift correctness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero filler, front-loading what the tool returns before the when-to-use rationale. Every clause earns its place.

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 usefully previews the returned fields and notes truncation/example toggles exist via parameters. It could say a bit more about the response shape (e.g. redirect chains, version placement), but an agent has enough to call it correctly.

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 the schema already documents all six parameters including the 'dir' fallback chain and the 'description_chars' truncation semantics. The description adds no parameter-level syntax or format detail beyond what the schema provides; baseline 3 is appropriate.

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 resource ('Exact options of a module or plugin as INSTALLED here') and enumerates the payload ('type, required, default, choices, aliases, suboptions'), plus the collection version and resolved redirects. This is clearly distinguished from sibling tool ansible_module_search, which finds modules rather than describing one.

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

Usage Guidelines4/5

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

Gives an explicit trigger ('Use before writing a task') and a rationale ('options drift between collection versions, so training-data guesses are often wrong'). No named alternative or exclusion, but the usage context is unambiguous.

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