get_resource

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

Annotations already declare readOnly/idempotent/non-destructive, so the burden is light; the description adds real behavioral context by enumerating the response payload (facets, provider metrics, README excerpt, linked publications with relationship types, related directions). It does not cover failure modes for malformed IDs or slugs.

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?

Front-loads the one-line purpose, then input format, then response shape. Every sentence carries information, though the response-field enumeration is long and partially duplicated by the output schema.

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?

An output schema exists, so describing return values is redundant-but-helpful rather than necessary. Input format and sibling routing are covered; missing only error/auth behavior, which is minor for a read-only lookup.

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 coverage is 0%, so the description must carry the single parameter — and it does, specifying that it accepts an 'art_...' artifact ID or a Lacuna resource URL of the form /resource/<slug>/art_..., which is the key detail an agent needs to construct a valid call.

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?

States a specific verb (fetch) and resource (Lacuna research resource: code repository, dataset, model, or demo), which concretely bounds the tool and separates it from generic siblings like search_lacuna or get_paper.

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?

Explains the input form and routes the agent onward — 'Pass a publication's paper_id to get_paper' — which is genuine usage guidance. It does not, however, state when to choose this tool over search_lacuna or when-not conditions, so it stops short of full when/alternatives coverage.

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