request_observation_resource

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

With no annotations, the description carries the full transparency burden. It discloses key behaviors: it performs CRUD, requires user-provided data without guessing, mandates confirmation before deletion, and returns JSON. It also notes the need to provide app links rather than API links. This goes beyond a simple 'makes HTTP request' statement and gives the agent actionable behavioral context, though it omits auth and error-handling details.

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 well-structured with clear sections for the workflow, rules, args, and returns. It front-loads the core purpose and uses bullets for rules. Every section serves a purpose; however, the volume of text could be trimmed slightly without losing essential information, so it's not a perfect 5.

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 that this is a generic HTTP tool for a specific resource, the description is complete: it covers the operation, the resource scope, preconditions (LOINC workflow), safety rules, parameter semantics, and return format. The output schema exists, so return values need not be detailed further. Sibling differentiation is adequate through the resource-specific wording.

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 0% description coverage for the top-level 'request' parameter, but the description's Args section explains each inner field with practical details: method enumerates HTTP verbs, path includes a concrete example with URL encoding, and body is described as optional JSON. This significantly adds meaning beyond the schema's terse descriptions and helps the agent construct valid requests.

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 clearly states the tool makes HTTP requests to the FHIR server and explicitly scopes it to 'CRUD operations only on the FHIR Observation resource.' This distinguishes it from sibling tools that handle other FHIR resources and from request_generic_resource. The verb 'request' combined with the resource name is specific and unambiguous.

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?

The description provides clear usage guidance: use this tool only for Observation resource operations, and includes a specific workflow ('First use get_loinc_code() tool... Then use this tool') for LOINC-dependent observations. It also gives explicit rules for creation, update, delete (requiring confirmation), and response formatting. While it doesn't name alternative tools for other resources, the resource-specific scope effectively implies when to use this tool vs siblings.

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