search_documents

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

With no annotations, the description carries the behavioral burden and does add real semantics: query is full-text across content and title, tags are ANDed ('must have all specified tags'), date filters are strictly after/before, and limit caps the result set. It does not mention response format, sorting, or what happens when filters are combined, but the provided behavioral details are meaningfully beyond generic search.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with a one-sentence purpose followed by a parameter table with no wasted lines. The line-by-line format is functional and parseable, though it reads more like schema documentation than a narrative tool description, so it is not a perfect model of structure.

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

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

The description thoroughly covers parameter semantics for a 7-parameter, no-output-schema, no-annotation tool, but it does not explain return values, result ordering, or how multiple filter types interact. Given the lack of an output schema, an agent still has meaningful gaps about what this tool will actually return.

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

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

The schema has zero descriptions (0% coverage), so the description must compensate fully. It does: every parameter is explained with practical semantics—query scope, tag matching, correspondent/document_type names, strict date forms, and limit meaning. This is exemplary compensation for an underspecified schema.

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

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

The first sentence 'Search documents in Paperless' states a specific verb and resource, making the core purpose clear. However, it does not differentiate itself from siblings like get_document or list_tags; the agent must infer that this is for full-text/filtered search rather than single-document retrieval.

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

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

Usage is implied by the name and opening sentence: use this to search documents. There is no explicit when-to-use, when-not-to-use, or mention of alternatives among the sibling tools, so the guidance relies on inference rather than clear routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.