The Leos studio

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

With no annotations, the description carries the full burden. It does disclose real behavioral constraints — 30-minute slot length, Milan timezone, weekday-only availability, and coarse granularity (start times only) — but says nothing about how many slots come back, whether results are live, or how far ahead the window extends.

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 short sentences, front-loaded with the resource and scope, and the granularity caveat is kept to a compact clause. Nothing is redundant or padded.

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 tool with no output schema, the description should convey the return shape, and it only partly does ('slot start times only'). It clarifies timezone and weekday filtering but leaves the number of returned slots and the response format to inference.

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, so there is nothing for the description to disambiguate; baseline 4 applies. The description's constraints (weekday, Milan time) are fixed behavior, not argument 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 states the specific resource and scope: the next open 30-minute call slots with the studio, constrained to Milan time and weekdays. That is enough to tell it apart from the booking sibling request_call and from list_services, though it never says the verb outright ('returns'/'lists').

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: an agent can infer this is the pre-booking lookup that precedes request_call. The parenthetical 'Coarse: slot start times only' acts as a mild exclusion hint (don't use it if you need slot details), but no sibling is named and no when-not condition is spelled out.

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?

With no annotations, the description carries the full behavioral burden. It usefully discloses currency (EUR), tax (plus IVA), what is included (photo and video), and that final quotes are confirmed by a person. It does not describe whether the tool is read-only, rate limits, authentication, or response structure, leaving some gaps for a simple lookup.

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 short sentences with no wasted words, and the key pricing context is front-loaded. The parenthetical handles inclusions efficiently. It is appropriately sized for a simple tool.

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 low-complexity tool with one optional enum parameter and no output schema, the description covers return value context (starting prices, currency, tax, inclusions) and the human-confirmation caveat. It omits what happens when the service parameter is omitted and does not explain the enum values, leaving gaps an agent must resolve from the schema.

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 description coverage is 0%, so the description must compensate for the single service parameter. It never mentions the service parameter or its enum values (event-half, event-full, studio-day). An agent must infer that 'rate card' relates to these service tiers without explicit mapping.

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 indicates the tool provides starting prices from the rate card, including currency and inclusions. It does not use an explicit verb, but the resource and purpose are understandable. It does not explicitly distinguish itself from siblings like list_services or check_availability.

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 implies the tool is for getting initial price estimates and notes that final quotes require human confirmation. However, it gives no explicit when-to-use guidance, no exclusions, and no routing to alternatives such as check_availability or list_services.

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 of disclosing behavior. It states the topical scope of the information but does not say whether the tool is read-only, what form the response takes, or how complete the listing is. For a zero-parameter listing tool this is a moderate but meaningful gap.

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 compact sentence with no obvious filler. Its structure is somewhat awkward because it begins with a noun clause rather than an action, but it remains concise and readable.

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 tool with no output schema and no annotations, the description gives useful topical context about what is covered. However, it does not explain the return format or how the tool differs from list_work, so an agent still lacks important routing and output expectations.

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 semantics to explain beyond the schema. The description does not need to compensate for missing parameter documentation, and the baseline score for a no-parameter tool 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?

The description identifies the subject matter as The Leos' offerings, including what the studio makes, who it serves, and its rentable daylight studio. However, it is phrased as a noun phrase rather than a clear verb/resource statement, and it does not explicitly say that the tool lists services. It also overlaps with the sibling list_work without distinguishing between 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?

There is no explicit guidance about when to use this tool versus list_work or the other sibling tools. The content implies a general overview use case, but the description leaves the agent to infer the selection criteria.

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 supplied, so the description carries the full burden; it does add one real behavioral fact — only 'published' projects are returned, which is not expressed anywhere in the schema. It stays silent on ordering, pagination, and result volume, which for a listing tool with zero annotation coverage are meaningful gaps.

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 filters after; every clause carries information and there is 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 simple two-parameter read tool this is close to sufficient, and the filter semantics are covered. With neither annotations nor an output schema, however, the agent learns nothing about the shape or size of the returned project list, which the description could cheaply have supplied.

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 description coverage is 0%, so the description must compensate; it does so partly by glossing the kind enum and, more valuably, giving concrete free-text examples for 'query' ('eyewear', 'jewellery', 'fashion week'). It never states whether kind and query combine as AND, nor how matching behaves, leaving the interaction of the two filters undefined.

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 resource ('the studio's published projects') and its filter axes, so an agent can tell it retrieves a portfolio listing. It does not explicitly distinguish itself from the sibling list_services, which an agent must infer from 'projects' vs. services.

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 word 'optionally' makes clear both filters are discretionary and that the unfiltered call is valid, which is useful invocation guidance. However, there is no statement of when to reach for this versus list_services or when a query word is preferable to a kind filter.

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?

With no annotations, the description carries the full burden, and 'The studio confirms it' is a genuinely useful disclosure that this is a request rather than a guaranteed booking. However, it says nothing about required permissions, what happens if the slot is taken in the meantime, or what the caller receives back.

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 short sentences with the prerequisite (slot from check_availability) and outcome (studio confirms) front-loaded; nothing is padded. The compressed phrasing 'for a brief you submitted' is slightly elliptical but still readable.

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?

There is no output schema and no annotations, so the description must cover behavior and results, and it only partially does so via the confirmation note. For a four-parameter mutation tool with three undocumented parameters, more detail is needed to call it confidently.

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 only 25%, with just 'slot' documented, so name, company, and contact are undocumented in both schema and description. The description hints that details are tied to a submitted brief but never explains what 'contact' should contain or whether name/company are optional identifiers.

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 ('Ask for a call') and ties the action to a slot returned by check_availability and a brief already submitted, which distinguishes it from browsing tools like list_services or list_work. It stops short of a crisp statement of what the call request actually is (e.g., a booking request pending studio approval), but the intent is clear.

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?

It states a concrete precondition: the slot must come from check_availability, and a brief must already exist. That routes the agent away from calling this first. There is no explicit when-not clause or mention of what to do if the preferred slot is unavailable.

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?

With no annotations, the description carries the full burden, and it does disclose meaningful traits: a human reviews the brief, a reply comes within one working day, and client contact info is mandatory. It omits what the caller receives back (no confirmation or reference number is mentioned), whether resubmission duplicates work, and any rate or size constraints.

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?

Three short sentences, front-loaded with what the tool does, then the turnaround expectation, then the one hard requirement. No filler or redundant 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?

A 10-parameter submission tool with no annotations and no output schema needs more: what the returned confirmation looks like, how the free-form fields (what, needs, references) should be shaped, and how this differs from the adjacent request_call tool. The current text covers the turnaround and contact requirement but not the bulk of the payload.

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?

Only 2 of 10 parameters have schema descriptions, so the description must compensate and largely does not. It reinforces 'contact' ('Include a way to reach the client') and gestures at 'on_behalf_of' ('on behalf of a client'), but leaves name, what, when, needs, where, budget, company, and references with no meaning added anywhere.

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 concrete verb and resource ('Send a project brief to the studio') plus the actor ('on behalf of a client'), which is enough to distinguish it from siblings like request_call or talk_to_the_studio. It never explicitly names those alternatives, but the action itself is specific.

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 choose this over the clearly related siblings (request_call, talk_to_the_studio, estimate_budget), nor any prerequisites or exclusions. The purpose implies a scenario, but the agent must infer selection criteria entirely.

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?

With no annotations present, the description carries the full burden and does substantial work: response style (studio's voice, one short line), the returned artifacts (brief so far, open call times, starting price, closest work, brief page), the confirmation-to-studio handoff, and a stated human response latency of one working day. It does not mention authentication, rate limits, or what happens to an unconfirmed brief, 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?

The core action is front-loaded in the first clause and the return/escalation details follow in a logical order. It is dense but somewhat run-on, with the continuation instruction and the working-day reply SLA packed into a single long second sentence. No sentence is clearly disposable.

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?

There is no output schema, so the description must explain return values, and it does list them. It also covers session continuity and the human handoff latency. What is missing is how the returned fields are shaped (e.g., whether open call times are formatted strings or objects) and any failure or ambiguity handling.

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 would be 3, but the description adds real meaning about message content — that the client can describe the project, ask questions, and name a call time in words rather than in a structured slot. It also reinforces the conversation_id continuation contract, which the schema states more tersely. on_behalf_of is not elaborated beyond its schema description.

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 concrete verb and resource — talking to The Leos' own agent in plain language — and enumerates the topics it handles (work, starting prices, studio rental and kit, the team) plus the call-time booking. That is far more specific than a tautology. It stops short of explicitly distinguishing itself from siblings like list_services, estimate_budget or request_call, whose subject matter it overlaps.

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?

It gives one explicit procedural rule — pass conversation_id from the last reply to continue the same brief — and describes the escalation path once a brief is confirmed. It never says when an agent should prefer this conversational tool over check_availability, estimate_budget or submit_brief, even though the described capabilities overlap all three, so routing must be inferred.

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