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retailmenot_blog_post

Fetch a RetailMeNot blog post by slug to get its metadata, article sections, and linked stores and coupon categories for use in store or category queries.

Instructions

Get a RetailMeNot blog post. Returns one RetailMeNot blog post: metadata (title, author, dates, description, image, categories, tags), the article text as headed sections of paragraphs and lists, and the RetailMeNot stores and coupon categories the article links to (usable with /retailmenot/store and /retailmenot/category).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesPost slug from /retailmenot/blog-posts (a trailing .html is accepted)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.9

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and it discloses the return structure in detail: metadata fields, article text as headed sections of paragraphs/lists, and linked stores/categories. It does not state error behavior for invalid slugs or any rate/auth constraints, but for a read-only 'Get' endpoint the return disclosure is substantial.

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 sentences, front-loaded with the purpose before the return detail. The opening 'Get a RetailMeNot blog post' is slightly redundant with the following 'Returns one RetailMeNot blog post', but overall it is tight and well-ordered.

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?

No output schema exists, so the description must describe returns and it does so thoroughly, covering metadata, body structure, and linked entities. With one fully documented parameter and a clear return overview, 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?

The single 'slug' parameter has 100% schema description coverage, including the source (/retailmenot/blog-posts) and the trailing .html acceptance note. The description adds no further parameter semantics, so the baseline 3 is correct.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get a RetailMeNot blog post') and the phrase 'Returns one RetailMeNot blog post' implicitly contrasts with the list sibling retailmenot_blog_posts. It does not explicitly name that sibling, so the differentiation is inferred rather than stated.

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?

There is no explicit when-to-use or when-not-to-use guidance for this tool itself. It does cross-reference downstream tools by noting the linked stores and categories are 'usable with /retailmenot/store and /retailmenot/category', which is useful implied usage but not a selection rule.

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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