get_pas_gopc_avg_quota

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

No annotations are provided, so the description carries full burden. It only states what the tool gets but does not disclose behavioral details such as how averages are computed, data freshness, pagination behavior, or response structure. For a read operation, key expectations like return format are omitted, leaving the agent with limited understanding of side effects or edge cases.

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 a single, front-loaded sentence with no redundant words. It efficiently communicates the tool's core action, metric, time window, and scope.

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 simplicity (2 optional params, no required fields, output schema present), the description covers the essential context: what metric is returned, the time window, and geographic scope. It does not explain return value structure, but the output schema covers that. Minor gap: it does not clarify whether the average is per district or overall, though 'across 18 districts' suggests district-level data.

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 100%, with both parameters (lang, district) fully described in the schema. The tool description adds no parameter-specific meaning beyond what the schema already provides (e.g., it mentions '18 districts' but does not link to the district parameter explicitly). Baseline 3 is appropriate.

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 uses a specific verb ('Get') and clearly identifies the resource ('average number of general outpatient clinic quotas') with temporal and geographic scope (preceding 4 weeks, 18 districts in Hong Kong). This distinguishes it from sibling tools like get_aed_waiting_times and get_specialist_waiting_times.

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 context is clear: this tool is for average GOPC quotas over a 4-week period, which implies use when needing that specific metric. However, it does not explicitly state when not to use it or mention alternatives (e.g., 'use this instead of waiting times tools'). The absence of exclusions keeps it slightly below a 5.

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