Moltline Catalog — 138 Agent Skills & Personas

Recommend Products

recommend_products

Read-onlyIdempotent

Recommend catalog products for a need described in plain language. FREE.

Typical input {"need": "help answering customer support emails"} returns {"need": ..., "recommendations": [{"slug": ..., "name": ..., "why": ..., "area": ..., "try_free": ""}], "next": "..."}.

Use when the caller describes a problem instead of naming a product; ranking is by fit to the described need. Not for exact keyword or slug lookups (search_catalog). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`need`	Yes	The job or problem in plain language, a few words or a sentence, e.g. "help answering customer support emails".
`limit`	No	Maximum recommendations; values outside 1-10 are clamped. Default 5.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.8/5.0

Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint), the description adds: 'Every call is read-only and idempotent, so after correcting the input it is always safe to retry' and describes the error response format, providing behavioral context not in annotations.

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?

Description is a single paragraph but well-organized: purpose, FREE note, example, usage guidelines, error behavior. Every sentence adds value, though it could be slightly more terse.

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?

Given the presence of an output schema and good annotations, the description covers all necessary context: purpose, usage scope, error handling, and retry safety. No gaps remain for a generic recommendation tool.

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%, baseline 3. The description adds a detailed example of input and output, which clarifies the 'need' parameter's purpose and the structure of the response, providing additional context beyond the schema descriptions.

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?

Clearly states 'Recommend catalog products for a need described in plain language' with specific verb and resource. Distinguishes from sibling tool 'search_catalog' by mentioning 'not for exact keyword or slug lookups'.

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?

Explicitly says 'Use when the caller describes a problem instead of naming a product' and 'Not for exact keyword or slug lookups (search_catalog)', providing an alternative. Also explains error behavior: 'never raises a protocol error — it returns an error object'.

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

All Moltline Catalog — 138 Agent Skills & Personas tools Inspect

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TDQS

A4.4/5.0

Disambiguation4/5

Most tools have clearly distinct purposes: listing, searching, recommending, previewing, and fetching different levels of detail. However, get_full_skill and get_free_skill could be confused since both return skill instructions but differ in which skill they target and plan requirements.

Naming Consistency4/5

The naming is largely consistent with a verb_noun pattern (list_kits, preview_product, search_catalog, etc.). However, there are minor deviations: get_free_skill uses 'free' as a qualifier rather than a verb, and upgrade_info is noun-heavy instead of verb_noun.

Tool Count5/5

With 10 tools covering discovery (search/recommend/list), preview, and detail retrieval across products, skills, personas, and kits, the count is well-scoped for a catalog API. Each tool has a clear role, and there is no noticeable bloat or deficiency.

Completeness4/5

The tool surface covers the full discovery-to-detail pipeline: browse/search/recommend, preview, then drill into free skill, full product, persona, kit, or specific paid skill. An 'upgrade_info' helper fills a support gap. A minor gap is the lack of a tool to list all products or browse by category without a keyword query.

Resources

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