tebra_update_encounter_status

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

No annotations are provided, so the description must fully disclose behavioral traits. It confirms mutation but omits critical details: permissions required, whether status transitions are reversible, any ordering constraints (e.g., cannot move from Rejected to Draft), side effects on related records, or success/error response. This leaves significant uncertainty for a mutation tool.

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 two sentences with zero superfluous content. It immediately states the purpose and follows with supporting context. Every word earns its place, making it highly efficient for an AI agent to parse.

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?

For a simple tool with three parameters and no output schema, the description covers the core purpose but lacks behavioral and error context. It does not describe what happens on success or failure, nor any constraints beyond status values. Given the low complexity, the description is adequate but misses opportunities to round out completeness.

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 input schema has 100% coverage with descriptions for all three parameters. The description repeats the enum values and notes the optional nature of reviewNote, but does not add new meaning beyond the schema. Baseline 3 is appropriate as the schema already provides sufficient parameter documentation.

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 action ('Update'), the resource ('status of an encounter in Tebra'), and the scope (workflow states: Draft, Review, Approved, Rejected). It effectively distinguishes from sibling tools like tebra_create_encounter or tebra_get_encounter by focusing on status transitions.

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 explicit use context ('move encounters through the workflow') and lists the allowed statuses. However, it does not specify when not to use the tool, exclusion criteria, or alternatives, lacking complete guidance for an AI agent to decide confidently when this tool is inappropriate.

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