core_output_search_by_query

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

With no annotations, the description carries the full burden and exceeds expectations. It discloses that outputs are not de-duplicated, that the same paper can appear multiple times, that upstream may return HTTP 500 for some query expressions (and that this server does not retry), that `max_results` is capped at 100, and that upstream `fullText` is stripped from the returned items. This gives an agent an accurate behavioral model.

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 longer than typical but every sentence earns its place: purpose, differentiation, usage guidance, error behavior, and result-shape notes. The most important scoping point ('outputs', not de-duplicated) is front-loaded, and the separation into paragraphs aids scanning without redundancy.

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?

Given the tool's complexity (duplication semantics, upstream instability, result trimming) and the absence of annotations and an output schema, the description is remarkably complete. It explains the resource type, the difference from works tools, query syntax, error behavior, result content, and limits—everything an agent needs to invoke the tool correctly and interpret its outcome.

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?

Schema description coverage is 0%, so the description must compensate and does. For `query`, it explains that CORE's own syntax is accepted and recommends field-qualified forms with concrete examples (`title:"..."`, `doi:"..."`), plus warns about problematic expressions. For `max_results`, it states the hard cap of 100. This adds meaningful semantics beyond the bare schema types.

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 description states a specific verb and resource: 'Search CORE's raw harvesting records (`outputs`, not de-duplicated).' It also distinguishes itself from the sibling `core_work_search_by_query` by explaining the conceptual difference between `output` and `work`, making it immediately clear what this tool does and how it differs.

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?

Explicitly states when to use this tool: 'Use this tool to find a specific repository's copy of a paper and inspect its `license` / `fulltext_status` / `repositories`; use the works tools for the paper itself.' Also recommends field-qualified query forms and warns against certain expressions, providing clear guidance on how to invoke it correctly.

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