Garden Route Specialist

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

With no annotations, the description carries the full disclosure burden and does well: it states ordering constraints (west to east), no-repeat activities, walkable clustering, rainy-day hub fallback, month-dependent picks/prices/whale season, ZAR currency, and that times and fares are estimates. It omits whether the tool has side effects (e.g. that it books nothing) and any auth/rate-limit context, which keeps it from a 5.

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-loaded with the core purpose, then rule/behavior details, then currency and estimation caveats. Four tight sentences with little waste, though the month instruction partially restates the schema's month description.

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 an 11-parameter generator with no output schema, the description conveys what the output contains (per-day plans, costs, budget check, dietary verification, safety notes, transport estimates) and how warnings work. It does not specify the output structure (e.g. JSON shape), but an agent has enough to call it and interpret results.

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 already 100%, so the baseline is 3; the description adds meaning beyond the schema by explaining cross-parameter behavior: month changes activity picks, hostel prices and whale watching; budget is all-in per day; rainy days trigger hub trips; dietary drives verified/NOT verified marking. A few statements (month handling, budget definition) duplicate schema text, so it is not a full 5.

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?

Starts with a specific verb and resource ('Build a day-by-day Garden Route itinerary') and immediately names the defining constraints: west-to-east, no repeated activities, with per-day costs, budget check, dietary verification, safety notes and transport estimates. This is unmistakably different from the sibling tools get_knowledge and get_stats, which are read-only data lookups.

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?

Gives explicit operational guidance: ask the traveller for their travel month first and note that the current month is assumed and flagged if omitted. It also describes the fallback when a town has nothing open (rain → nearest hub trip). It does not provide when-not-to-use guidance, but the sibling tools are unrelated enough that explicit alternatives are not necessary.

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

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

No annotations are provided, so the description carries the full burden, and it does reasonably well: the 'get'/'Local knowledge' framing implies a non-mutating lookup, and enumerating returned content (booking links, NSRI links, dorm prices) substitutes for a missing output schema. It omits any note on caching, freshness, or failure behavior for an unsupported town.

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?

A single front-loaded sentence with no filler; scope comes first and the content inventory follows. Every element earns its place.

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 one-parameter lookup with no output schema, the description is nearly sufficient because it inventories the return contents. Only the response format and behavior for an out-of-list town are unaddressed.

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% — the single town parameter already lists every valid value plus alias handling ('plett', 'brenton-on-sea'). The description only restates 'one Garden Route town', adding no format or matching details beyond the schema, so baseline 3 applies.

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 resource and scope: 'Local knowledge for one Garden Route town', then enumerates exactly what kinds of content come back (activities, hidden gems, dorm prices, evenings, safety tips, NSRI links). The weak verb 'get' is offset by the concrete content list, and the town-level scope distinguishes it from get_stats and generate_itinerary without naming them.

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?

Usage is implied by the content inventory — an agent can infer this is the reference-lookup tool for a single town versus itinerary planning or statistics. However, it never states when to prefer it over generate_itinerary, nor any preconditions or exclusions.

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

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses little beyond the payload contents. It never states that the call is read-only and side-effect free, nor does it describe time window, aggregation granularity, or response shape — all of which matter for a statistics endpoint.

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?

A single front-loaded sentence with the resource first and the concrete contents in a compact parenthetical. There is no filler, hedging, or restatement of the tool name.

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?

With no output schema, the description is the only place a caller can learn what comes back, and it gives only two examples ('call counts, recent calls') without structure, time window, or granularity. It is adequate for a zero-parameter low-risk call but leaves meaningful gaps about the return value.

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 tool takes zero parameters, which is the baseline-4 case per the rubric. The description's parenthetical does confirm that the metrics are implicitly scoped (call counts, recent calls) rather than requiring arguments, which is consistent with the empty schema.

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 names a specific verb ('usage statistics') and enumerates the concrete data returned (call counts, recent calls), so the agent knows exactly what resource this surfaces. It offers no differentiation from sibling tools, but the siblings (generate_itinerary, get_knowledge) are unrelated, so the cost of that omission is low.

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?

There is no statement of when to reach for get_stats versus the sibling tools, no prerequisites, and no exclusions. The agent must infer entirely from the name that this is a diagnostics/introspection call rather than, say, content retrieval.

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