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Recommend kits for a project

recommend_kits

Recommend design kits from stored project context, returning each candidate's purpose, motifs, moods, industries, and surface fitness. Requires API key and set_project_context first.

Instructions

Kit candidates for a specific product, grounded in the context stored on its project rather than in a description you re-send. Each candidate comes back with the kit's own case for itself — what it is for, its motifs, its do's and don'ts, its moods and industries, and its computed fitness for the surfaces this product actually has — so you can rank them yourself. With a Pro account and a kits:write key you also get a model-authored ranking with a reason per candidate written against this product; meta.depth says which you got, ranked or candidates, and meta.order says plainly that the free ordering is computed lane fitness and not a recommendation. Two things that differ from the rest of discovery: this costs 3 quota units where list_themes and search_themes cost 1, and it requires an API key where every other discovery route works anonymously. Call set_project_context first: a project with no stored context returns 400 rather than guessing. Creates nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many candidates to return.
projectIdYesOwned brand project id whose stored context grounds the proposal. Write it with set_project_context first.
Behavior5/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool requires an API key, costs 3 quota units, returns meta.depth and meta.order to clarify mode and ordering, returns 400 if context is missing, and explicitly says 'Creates nothing' to signal no side effects. This far exceeds the transparency normally expected.

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?

The description is a single paragraph but each sentence adds distinct value: purpose, candidate contents, ranking mode, differences from other routes, and prerequisite. It is front-loaded with the core function and avoids fluff, though it is somewhat dense in presentation.

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?

Even without an output schema, the description explains what the response contains (candidate self-cases, meta.depth, meta.order), the auth and quota conditions, the error scenario, and the read-only nature. For a tool with two parameters and no output schema, this fully equips the agent to select and invoke it correctly.

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?

Schema coverage is 100%, so baseline is 3. The description adds contextual meaning to projectId by tying it to set_project_context and stored context, and clarifies that limit only controls candidate count. While limit is self-explanatory, projectId's prerequisite is well articulated, adding value beyond the schema.

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 clearly states the tool recommends kit candidates for a specific product, grounded in stored project context. It distinguishes from siblings by emphasizing that it uses stored context instead of a re-sent description, and explicitly differentiates from list_themes and search_themes by cost and auth requirements, plus 'Creates nothing' clarifies side-effect-free behavior.

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?

It explicitly says 'Call set_project_context first' as a prerequisite and notes that a project without stored context returns 400. It also highlights the two differences from other discovery routes: higher quota cost and API key requirement, and explains the two modes (free candidates vs. ranked with Pro+key), which gives clear when-to-use and alternative comparisons.

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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