Moltline Research Desk

List Products

list_products

Read-onlyIdempotent

List every product in the Research Desk line with its included skills. FREE.

Takes no arguments. Returns a list of 7 product objects, each {"slug": "thesis-advisor", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill.

Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). 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
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.9/5.0

Behavior5/5

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

Reinforces annotations (read-only, idempotent) and adds critical behavioral details: return format structure, metadata-only nature, no persona/skill instructions, and the error handling behavior (returns error object, never protocol error).

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?

Well-structured: purpose first, then return format, then usage guidelines, then error handling. Every sentence adds value. No redundancy or wasted words.

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 zero parameters, rich annotations, and presence of an output schema, the description fully covers the tool's behavior, return structure, error handling, and relationship to sibling tools. No gaps remain.

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?

No parameters exist in the input schema (coverage 100%). Baseline 4 is appropriate; the description correctly states 'Takes no arguments' and adds no further parameter semantics.

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 the verb 'list', resource 'products', and scope 'Research Desk line'. Explicitly distinguishes from sibling tools by noting it returns metadata only and that the returned slugs are used with other tools.

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?

Provides explicit when-to-use ('when the caller wants to see what this server covers') and when-not-to-use ('not for keyword search...catalog server's search_catalog', 'not for instructions...get_free_skill'). Names alternative tools.

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

All Moltline Research Desk tools Inspect

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TDQS

A4.7/5.0

Disambiguation5/5

Each tool targets a distinct function: statistics tools for descriptive, inferential, and planning; product tools for listing, free skill, paid skill, and full product; and citation formatting. No overlap or ambiguity.

Naming Consistency4/5

Most tools follow a verb_noun or noun_verb pattern, but there is a mix: some are noun phrases (confidence_interval, sample_size, stats_describe) while others are verb phrases (format_citation, list_products). The naming is clear but not perfectly uniform.

Tool Count5/5

With 8 tools, the server covers two functional domains (statistics and product browsing) without being bloated. Each tool serves a clear purpose, and the count feels well-scoped.

Completeness4/5

The product domain is covered thoroughly (list, free skill, paid skill, full product). The statistics domain is missing hypothesis tests and more advanced analyses, but the included tools cover basic descriptive, confidence intervals, and sample size planning, which is reasonable for a 'research desk' scope.

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