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get_product

Read-only

Get the full record for a single product by its numeric ID.

Use after `search_products` returns a candidate the user is interested in,
when you need fields not in the search summary (full description, all
images, sold status, expiration). Don't loop `get_product` over many search
results — re-search with tighter filters instead.

Read-only. No authentication.

Args:
    product_id: Integer `id` from a `search_products` result, or visible in
        a Partle product page URL (`/p/<id>-<slug>`).

Returns:
    A single product object with all fields, including the canonical
    `partle_url` to share with the user. Returns ``{"error": ...}`` if the
    ID does not exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable context: 'No authentication' and the error return behavior for nonexistent IDs. This goes beyond the annotations, though it doesn't disclose rate limits or other edge cases.

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?

Every sentence serves a purpose: purpose statement, usage context, read-only note, parameter documentation, and return behavior. It is well-structured with clear separations (Args/Returns) and no filler.

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 simple, single-parameter tool without an output schema, the description covers usage, parameter source, return contents, and error behavior. It also includes the canonical `partle_url` as a useful return element, making the tool complete for the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% — the schema only gives type integer and title 'Product Id'. The description fully compensates by explaining the ID source (`search_products` result or URL pattern), validation (integer), and format, making the parameter's meaning and origin clear.

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?

The description opens with a clear, specific action: 'Get the full record for a single product by its numeric ID.' This verb+resource+scope structure distinguishes it from sibling tools like search_products (which searches) and get_my_products (which lists own products).

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?

Explicit guidance is provided: 'Use after `search_products` returns a candidate' and 'Don't loop `get_product` over many search results — re-search with tighter filters instead.' This states both when to use and when not to use, with an alternative approach named.

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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