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get_collection_manifest

Read-only

Get a compact collection manifest listing modules, roles, and plugins with one-line descriptions to decide which components to explore. Returns cached or on-demand data.

Instructions

Get a lightweight collection overview: module/role/plugin names with one-line descriptions.

Prefer this over get_collection_docs when exploring a collection — it returns a compact summary suitable for deciding which modules to drill into with get_module_doc.

Returns cached MANIFEST.json if available, otherwise generates on-demand (metadata extraction only, no skill generation). On failure returns {"error": str}.

Module docs are fetched in batched ansible-doc calls. If the entire batch fails hard, the manifest is written with zero module entries (roles/plugins from list discovery are still included when present).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collection_namespaceYesCollection namespace (e.g. 'netbox.netbox')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The annotations only declare readOnlyHint: true, but the description adds substantial behavioral context: cached vs. on-demand generation, metadata extraction with no skill generation, error return shape, and the partial-failure behavior where a hard batch failure yields zero module entries but retains roles/plugins. This goes well beyond the annotation.

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?

Every sentence earns its place: purpose, usage guidance, caching behavior, error shape, and failure semantics. The description is front-loaded with the core purpose and then methodically covers edge cases without fluff.

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 single-parameter tool with an output schema, the description covers purpose, selection criteria, caching, generation side effects, error returns, and degraded batch behavior. It is fully self-sufficient for an agent to decide when and how to invoke it.

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%: the only parameter, collection_namespace, already includes an example ('netbox.netbox'). The tool description does not add additional parameter-level detail, so the schema carries the load; this meets the baseline but does not exceed it.

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?

The description opens with a specific verb and resource: 'Get a lightweight collection overview: module/role/plugin names with one-line descriptions.' It clearly distinguishes this from the sibling get_collection_docs by framing it as the preferred exploratory overview tool, and points to get_module_doc for drilling down.

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?

The description explicitly says 'Prefer this over get_collection_docs when exploring a collection' and notes it is 'suitable for deciding which modules to drill into with get_module_doc.' This gives clear context and names alternatives, though it does not enumerate explicit when-not-to-use cases beyond the preference statement.

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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