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Moltline Studio

by com.moltlinestudio
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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.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "need": "<need>"
    },
    "name": "recommend_products"
  }
}

Input Schema

NameRequiredDescriptionDefault
needYesThe job or problem in plain language, a few words or a sentence, e.g. "help answering customer support emails".
limitNoMaximum recommendations; values outside 1-10 are clamped. Default 5.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover read-only, idempotent, non-destructive and closed-world, and the description adds behavior those hints do not express: no cost ('FREE'), the guarantee that malformed input never raises a protocol error but returns an {"error": ...} payload, and the explicit instruction that retrying after correction is safe. That is meaningful context beyond the structured hints.

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?

Front-loads purpose in the first sentence, then example, then routing rule — the ordering is easy to scan. The multi-line pretty-printed response example is the least economical part, especially since an output schema already exists, so it spends slightly more space than it earns.

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 two-parameter read tool, everything an agent needs is present: input modality, ranking basis, sibling routing, cost, error contract, and retry safety. The return-shape example is technically redundant with the output schema but reinforces the 'why' field's role rather than omitting anything.

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 coverage is 100%, and both parameters (need, limit with 1-10 clamping and default 5) are fully described in the schema. The description's 'plain language' framing and the sample input echo rather than extend the schema, so the baseline 3 applies.

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 verb and resource ('Recommend catalog products') plus the defining input modality ('a need described in plain language'). The contrast clause 'Not for exact keyword or slug lookups (search_catalog)' lets an agent separate it from the nearest sibling without reading either schema.

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?

Gives an explicit selection rule — 'Use when the caller describes a problem instead of naming a product' — a stated ranking basis ('fit to the described need'), and a named exclusion routed to a specific alternative (search_catalog). This is the full when/when-not/alternative triad.

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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