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Moltline Business Suite

Get Full Product

get_full_product
Read-onlyIdempotent

Load one product in full: its persona plus every paid skill. PREMIUM (license).

Typical input {"slug": "smb-ops-desk"} returns {"slug": ..., "name": ..., "persona": "", "skills": [{"name": ..., "instructions": ...}, ...], "free_skill": {...}}.

Returns persona plus every skill for one product. Use when the caller wants the whole product. Not for a single skill (get_full_skill) and not for a free look, which list_products and get_free_skill provide with no plan. Errors: on invalid, missing, or malformed input this tool never raises a protocol error; it returns {"error": ""} (for example {"error": "unknown slug ''"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

NameRequiredDescriptionDefault
slugYesProduct slug exactly as returned by list_products, e.g. "smb-ops-desk"; must be non-empty.

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 declare read-only, idempotent, non-destructive, closed-world, so the bar is lower – yet the description adds context beyond them: the PREMIUM license requirement and a precise error contract (never raises a protocol error, returns {"error": ...} with an example) plus retry safety after correction. That is meaningful behavioral disclosure the annotations do not carry.

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-loaded with purpose and examples, and the alternative routing is near the top. Slightly redundant: 'Returns persona plus every skill for one product' restates the opening sentence, and the error sentence is long, but overall it earns its space.

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?

With an output schema present, the return shape needn't be explained, yet the description shows it anyway; combined with license requirements, error semantics, retry safety, and sibling routing, an agent has everything needed to call it correctly.

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 the slug parameter is fully documented, including 'exactly as returned by list_products' and non-empty constraint. The description adds only a typical input example and an example error string, which is a marginal gain over the schema – baseline 3 is appropriate.

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?

Opens with a specific verb and resource: 'Load one product in full: its persona plus every paid skill.' It explicitly names the sibling tools it is not (get_full_skill, list_products, get_free_skill), so an agent can route correctly without opening any 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 both sides: 'Use when the caller wants the whole product' plus explicit exclusions for a single skill (get_full_skill) and for a free look (list_products, get_free_skill). No inference is required.

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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