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james-julius

Markdrop MCP Server

by james-julius

search_pastes

Search Markdrop pastes by content, title, tags, or topics. Apply filters for category, document type, or specific tags to retrieve relevant markdown documentation.

Instructions

Search through Markdrop pastes by content, title, tags, or topics. Returns matching pastes with metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoFilter by specific tags (e.g., ["architecture", "api"])
limitNoMaximum number of results to return (default: 10)
queryYesSearch query to match against paste content, title, and tags
categoryNoFilter by category (e.g., "design", "architecture", "guide")
documentTypeNoFilter by document type (e.g., "architecture", "decision-record")
Behavior3/5

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

With no annotations provided, the description carries the burden of disclosing behavior. It states that the tool searches and returns matching pastes with metadata, which is a read-only operation. However, it does not disclose details like result ordering, matching semantics, or any access requirements, leaving some ambiguity.

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, compact sentence that front-loads the main purpose. It avoids unnecessary detail and earns its place.

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?

Without an output schema, the description should ideally clarify what 'metadata' includes and how results are ordered or paginated. It only states that matching pastes with metadata are returned, leaving the response structure under-specified. This is adequate but not complete for a search tool.

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 100%, so the schema already documents all parameters. The description adds marginal value by mentioning that search matches content, title, and tags, but it also introduces 'topics' which is not a distinct parameter in the schema, creating slight ambiguity. This is baseline with no significant added insight.

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') and resource ('Markdrop pastes'), clearly distinguishing it from siblings like get_paste (retrieval of a single paste) and get_recent_pastes (listing recent items). It also specifies the search dimensions (content, title, tags, topics).

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

Usage Guidelines4/5

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

The description clearly implies usage for finding pastes by search terms, which differentiates it from sibling tools. However, it does not explicitly mention when to use alternatives or provide exclusions, so it falls short of a 5.

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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