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dotmoose

Recommend a current DotMoose product

recommend_product
Read-only

Recommend the smallest currently orderable public product set for a goal, or return the workload-specific Dedicated quote handoff when bare metal is explicitly requested. Fixed-product recommendations and optional backup/object-storage components come from live public availability, not a hard-coded price table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workloadNounknown
needsRootNo
needsBackupNo
needsDomainNo
expectedTrafficNotiny
needsObjectStorageNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

readOnlyHint=true is consistent with a recommendation operation, and the description adds real context beyond the annotation: it discloses that recommendations and optional add-ons are derived from live public availability rather than a hard-coded price table, and that the dedicated path returns a quote handoff instead of a product. Return shape is only partially characterized (no output schema), which keeps it below 5.

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?

Two dense sentences with zero filler, and the primary behavior is front-loaded before the dedicated-case exception. Slightly jargon-heavy ('workload-specific Dedicated quote handoff'), but every clause conveys information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six undocumented parameters and no output schema, the description should explain what a recommendation actually contains and how the traffic/root/domain flags alter the result. It covers the availability-sourcing and the dedicated branch well, but leaves the agent guessing about the returned structure and about three of the six inputs.

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 description coverage is 0%, so the description must carry the burden. It adds meaning for roughly half the parameters — the 'goal' maps to workload, 'bare metal explicitly requested' maps to workload=dedicated, and 'optional backup/object-storage components' maps to needsBackup/needsObjectStorage — but expectedTraffic, needsRoot, and needsDomain get no explanation of how they change the recommendation.

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+resource: recommend the smallest currently orderable public product set, with a named secondary behavior for the dedicated/bare-metal case. It is clearly distinct from the sibling listing/quoting tools (list_public_products, quote_public_product) because it produces a recommendation rather than a list or a firm quote.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage ('for a goal') and gives one routing condition — bare metal explicitly requested routes to the Dedicated quote handoff. It does not say when to prefer this over quote_public_product or list_public_products, nor what the agent should do with the recommendation afterwards, so the guidance is implied rather than explicit.

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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