Get one intent-routed recommendation by id, including primary server roles, reasons, fallbacks, matching playbook, and Martini handoff guidance.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Recommendation id, e.g. 'fast-commercial' or 'hosted-only-stack' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes on the full burden. It discloses the key behavioral aspect—what the response contains—by listing the included fields. It does not mention auth, rate limits, or error behavior, but for a read-only get-by-id the coverage is strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that names the action and resource first, then efficiently lists the included output fields. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema, so the description's enumeration of return contents is appropriately complete. It lacks explicit alternative guidance, but that is covered under usage guidelines.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the id parameter with examples. The description adds the context 'intent-routed' but does not enrich parameter meaning beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets one recommendation by id and enumerates the response contents (roles, reasons, fallbacks, playbook, Martini handoff). This distinguishes it from list_film_recommendations by specifying single-item retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a single recommendation by id but gives no explicit comparison to sibling tools like list_film_recommendations or recommend_film_mcps. There are no when-to-use or when-not-to-use guidelines.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct entities (capabilities, playbooks, recommendations, servers, install configs). The only potential confusion is between plan_film_stack and recommend_film_mcps, but their descriptions clarify different scopes: full pipeline vs intent-routed brief.
All tools follow a consistent verb-first snake_case pattern: get_ for singular resources, list_ for plural, plus search_, plan_, recommend_, and submit_. No mixed conventions or vague verbs.
15 tools is at the upper end of the ideal range but each earns its place: search, retrieval, listing, planning, recommendation, install config, and submission. No redundant tools.
Covers the full directory lifecycle: discovery, retrieval, contextual listings, planning, recommendations, install config generation, and submission. Minor gap: there's no explicit list-all-servers endpoint, but search_film_mcps can fulfill that role.
