Spot

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds one useful behavioral signal — that only public data is returned — and hints that join instructions are included, but it says nothing about failure modes (invalid ID, private/cancelled event) or result size, which is the kind of context annotations cannot supply.

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 tightly packed sentence with the payload (what you get) front-loaded, followed by the one operational hint needed to call it. Zero filler and no 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 and only one parameter, the description correctly takes on the job of describing the return payload by listing the event facets the caller will receive, which is exactly the right compensation. The remaining gap is error/empty-result behavior for a missing or non-public event, which an agent would want before calling.

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% and the single parameter already documents both the full URL form and the bare ID form with a concrete example. The description's 'pass its link or the part after /e/' largely restates the schema, adding only the mild clarification that the trailing path segment after /e/ is the accepted ID. Baseline 3 is appropriate when the schema carries the semantics.

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+resource combo (fetch everything public about one Spot event) and enumerates the returned facets: time, location, price, host, attendance count, and join instructions. It is instantly distinguishable from a list/search operation, though it never names the sibling tools search or pricing to make the boundary explicit.

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 rather than stated: 'one Spot event' plus an identifier argument tells the agent this is a direct-lookup tool, while search and pricing are presumably for discovery and cost questions. There is no explicit when-to-use/when-not-to-use sentence, no guidance on first using search to obtain an identifier, and no mention of behavior for an unknown/expired event.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is known. The description adds the content scope of the pricing information but does not mention freshness, currency, auth, or output format.

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 sentence with a colon and semicolon list, front-loaded with the pricing purpose and no filler.

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 zero-parameter, read-only informational tool without an output schema, the description covers the main pricing categories an agent would expect. It stops short of specifying exact return contents, freshness, or currency.

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 has zero parameters, so there is no parameter meaning for the description to add; the baseline for zero parameters is 4.

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 identifies a pricing resource and enumerates the cost areas: free event joining, host and company plans, and Spot's cut of ticket sales. It is clear what information the tool surfaces, though it does not explicitly contrast itself with get_event or search.

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: call it when a user asks what Spot costs or how event, host, or company pricing works. There is no explicit when-to-use statement, no exclusions, and no named alternative for pricing questions.

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?

Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds one genuinely useful behavioral fact — that it parses full sentences rather than keywords — but says nothing about result counts, ranking, or how multiple entity types are combined in the response.

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?

Two sentences, both load-bearing: the first scopes the searchable entities, the second demonstrates the query style. Minor waste in the slightly awkward opener "Search Spot in plain words" which partly echoes the title.

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 single-parameter, read-only, non-open-world search with no output schema, this covers what an agent needs: what can be searched and in what input style. Return shape is outside the description's remit since no output schema exists and annotations confirm the safety profile.

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%, so the baseline is 3, but the description earns an extra point by demonstrating the expected input shape with two concrete natural-language examples rather than restating "what to look for." It makes clear the query should be free-form phrasing, not a structured filter string.

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 gives a specific verb and resource ("Search Spot") and enumerates the entity types it covers — events, cities, hosts, companies, venues, speakers, sponsors — which makes the breadth clear. It implicitly separates itself from get_event and pricing by being a broad discovery entry point, though it never names those siblings explicitly.

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 conveyed only by example ("AI events in Copenhagen this weekend", "free hackathons next month"), which strongly implies natural-language queries but never states when to prefer this over get_event for a known event or pricing for cost lookups. No exclusions or prerequisites are given.

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