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monroedean

doctor-of-credit-mcp

by monroedean

search_posts

Search Doctor of Credit posts by text, with optional filters for category and publication date. Retrieve matching articles up to a specified limit.

Instructions

Search Doctor of Credit posts by text, optionally filtered by category slug and publication date (default limit: 10; maximum: 100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNo
limitNo
queryYes
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
postsYes
Behavior3/5

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

No annotations exist, so the description carries the full burden. It discloses the default limit (10) and maximum (100), and the presence of optional filters, which is helpful. However, it omits behavioral details such as sort order, whether the search covers title/body, or read-only status (though 'search' implies read-only). Some value is added, but gaps remain.

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?

The description is a single, sentence-length structure that front-loads the action and resource. Every clause adds value (search, filters, limits) with no waste. It is highly concise and well-structured.

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

Completeness4/5

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

An output schema exists, so return values are covered. The description gives essential usage details (query, filters, limits) and is appropriate for a moderate-complexity search tool. It lacks some behavioral nuances like matching fields and ordering, but the presence of the output schema and the core information makes it reasonably complete. A small gap remains around search semantics.

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 description coverage is 0%, but the description provides meaningful natural-language mappings for all parameters: query→text, category→category slug, after→publication date, and limit→default/max. This fully compensates for the lack of schema descriptions and adds significant 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?

The description uses a specific verb 'Search' with a clear resource 'Doctor of Credit posts' and defines scope via text search with optional filters. This distinguishes it from siblings like get_post (single post) and get_recent_posts (no text search). The purpose is immediately clear.

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?

The description outlines what the tool does (text search, optional category/date filters) and implies its use case, but it does not explicitly state when to use this over siblings or provide exclusions. There is clear context but no explicit alternative guidance.

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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