BidSurvivor

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

The description goes well beyond the annotations by explaining costs, lack of account/card requirement, automatic site reading, per-day/domain limits, future-date restrictions, and the risk of being outbid later. These are exactly the behavioral traits an agent needs to know, and nothing in the description contradicts the annotations.

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 well-structured and front-loaded with the core action, then expands to cost, constraints, and consequences. It is slightly wordy in places, such as 'so any amount takes it, zero included' and the closing 'nothing was lost with it,' but every sentence contributes useful context.

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 write operation with no output schema, the description covers cost, authentication, time constraints, rate limits, and failure consequences — enough for an agent to decide whether and how to invoke it. The main gap is the lack of any indication of what the tool returns on success, though the absence of an output schema makes this less critical.

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 100%, so the parameter schema already documents url, name, dayKey, tagline, category, and slotIndex thoroughly. The tool description adds no parameter-specific detail beyond the schema; it enriches the overall context but does not add meaning to individual parameters.

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-plus-resource construction: 'Put a product on the board in a slot nobody holds.' It clearly identifies the action, the target resource, and the key condition (free/unclaimed slot), and it is obviously distinct from the read-only sibling tools like get_board and get_slot_price.

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 clearly states when this tool is appropriate: for free claims, with no account or card, limited to today or tomorrow, and one claim per registrable domain per day. It also hints at the alternative path for further-ahead bookings ('booking further ahead is for bidders on the site'), though it does not explicitly name a sibling tool as the alternative.

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 mark this as read-only and non-destructive, so the description's job is to add context. It adds meaningful behavioral detail: the board is live, has exactly 2 slots of 12 hours, and includes slot holders and prices. It also explains the meaning of isFree true and connects to claim_free_slot, giving practical behavior beyond annotations.

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, no filler. The core board structure and contents are front-loaded, and the note about claim_free_slot is placed as an actionable follow-up. Every word contributes to understanding the 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 simple zero-parameter read-only tool, the description is complete: it explains what the board shows, how slots are organized, what isFree means, and the associated claiming action. No output schema exists, but the description sufficiently describes the returned information.

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 are no parameter semantics to document. The description correctly focuses on what the board contains rather than inputs. This matches the baseline for a parameterless tool.

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 resource ('the current board'), then explains exactly what the board contains: 2 slots a day of 12 hours each, showing held status, holder, price, and availability. This clearly differentiates it from siblings like get_stats or list_winners.

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 clearly implies when to use get_board: to inspect the live advertising board and slot availability. It also points to claim_free_slot when a slot is free, which helps an agent decide next action. However, it does not explicitly exclude alternatives or state when not to use this tool.

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 mark the tool as read-only and non-destructive. The description adds useful context beyond that by stating the figures are 'published' and 'the same figures anyone can read on the site,' clarifying that no special access or hidden behavior is involved. No contradiction with annotations.

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 filler. It front-loads the key concept ('published numbers for one brand'), then lists the exact metrics returned, and closes with a useful public-data qualifier.

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 one-parameter, read-only tool, the description is fully adequate: it names the data returned, the scope, and the public nature of the data. The absence of an output schema is acceptable because the description enumerates the main result components clearly.

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 description does not need to compensate for missing parameter documentation. The brandId parameter is already described as coming from get_board or claim_free_slot, and the description's 'one brand' framing aligns with that parameter without adding new semantic detail.

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 identifies the tool's purpose: retrieving published numbers for one brand, specifically slots held, card opens, and click-throughs. It states the resource scope ('one brand') and lists concrete metrics, though it does not explicitly distinguish itself from the sibling get_stats tool.

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 enough context to infer this is for a single brand's public stats, but it gives no explicit when-to-use/when-not-to-use guidance or mention of alternatives such as get_stats. The usage is implied rather than directly stated.

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 mark the tool as readOnly and non-destructive. The description goes beyond annotations by explaining the actual pricing rule: zero if unheld, otherwise the minimum bid threshold. This gives the agent meaningful behavioral information about the returned value without contradicting the annotations.

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?

One tightly written sentence conveys the essential pricing rule without waste. The most important information is front-loaded, and every phrase contributes to understanding what the tool returns.

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-only tool with complete schema coverage, the description covers the return semantics clearly enough. It could be more complete by stating the output format or units or by naming sibling tools, but the annotations and schema cover the remaining operational context.

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 100%, so the schema already documents dayKey and slotIndex sufficiently. The description adds the concept of 'specific slot' and 'cost to take' but does not add parameter-level detail beyond the 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 clearly identifies the tool's purpose: returning the current price to take a specific slot, including the zero-price case and the amount a bid must beat. It is specific and useful, though it does not explicitly contrast itself with sibling tools like claim_free_slot or get_board.

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 phrase 'right now' and 'a bid has to beat' imply the tool is for checking current pricing before claiming or bidding on a slot. However, there is no explicit guidance on when to choose this tool over siblings, nor any exclusion such as 'use get_board for an overview' or 'use claim_free_lot to claim a slot.'

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?

The annotations already declare this read-only and non-destructive, so the description is not responsible for that burden. It adds helpful context about what metrics are included, but does not disclose operational behavior such as exact units, time ranges, or any limitations. There is no contradiction with the annotations.

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 first sentence is tight and informative, front-loading the key metrics. The second sentence is largely tone-setting and could be trimmed, but it does not create real noise. Overall the description is short 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 read-only tool, the description supplies enough to know what the call returns: visitors, page views, and click-throughs. Precise units and response shape are not specified, but with no output schema and only this scope, that is a minor gap.

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?

There are zero parameters, so the input schema carries no burden and the description does not need to explain parameter meaning. The description's metric list adds useful output expectations beyond the empty schema, which keeps this above the baseline.

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 specific deliverable — the board's public traffic numbers — and spells out the concrete metrics: visitors, page views, and click-throughs to brands. This clearly distinguishes it from sibling tools like get_board and get_brand_stats, which concern different aspects of the board. The title reinforces the same resource and scope.

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 wording strongly implies this tool is for board-level traffic metrics rather than brand-specific or board-detail queries, but it never explicitly states when to prefer it over get_brand_stats or get_board. The context is clear enough to infer the use case, but it stops short of naming alternatives 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?

Beyond the readOnly/openWorld annotations, the description discloses meaningful behavior: it returns both bid and free placements, includes card opens and click-throughs, orders by 'newest attention first,' and can be filtered to one category. This gives a clear picture of what the agent will receive without relying solely on annotations.

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 compact and front-loaded: it states the core purpose first, then the row contents, then the intended downstream use. Each sentence adds necessary information, and there is minimal filler or repetition.

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?

Even without an output schema, the description communicates the main return fields (card opens, click-throughs, bid vs free placement, brandId) and the ordering behavior. It also names the primary downstream consumer, making it fully actionable for an agent deciding whether and how to call it.

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 100%, so the schema already documents both limit and category. The description adds context for category by calling it optional and mentioning filtering, and it implies limit affects result count, but it does not add significant meaning beyond the schema. 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 names a specific verb and resource — listing brands tied to advertising slot history — and clearly distinguishes itself from siblings like get_brand_stats by stating 'Use this to find a brandId for get_brand_stats.' It also clarifies the exact scope: brands that held or contested a twelve-hour advertising slot.

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 gives a clear primary use case: retrieving a brandId for get_brand_stats. It also explains optional category filtering and the sort order. However, it does not explicitly state when to avoid this tool or name alternatives such as list_winners, so it stops short of full when-to-use-versus-alternatives guidance.

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 the tool read-only and non-destructive, and the description adds meaningful behavioral context: what set of brands is included, how they are ranked, and the supported time windows. It does not disclose output structure or pagination, but those are not critical given the read-only, list-style nature.

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, well-structured sentence that front-loads the core result set and ranking logic. Every part adds relevant information without redundancy or 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 read-only list tool with three optional parameters and no output schema, the description covers the essential semantics: what is returned, how it is ranked, which periods are supported, and the optional category filter. It does not describe the exact response shape, but the absence of an output schema and the simple list nature make this less critical.

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?

With schema coverage at 67%, the description partially compensates by explaining that period maps to 7 days/30 days/year and that category is an optional filter. The limit parameter is not mentioned in the description, but the schema already documents its default and bounds.

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 identifies the resource (brands that held a slot when it closed plus the current live-slot leader) and the specific action (list them ranked by what they paid). It also distinguishes the tool from siblings like get_board and get_stats by describing a winners-oriented read operation.

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 when to use the tool: when you need past and live slot winners over a chosen period, optionally filtered by category. However, it gives no explicit guidance about when not to use it or how it compares to sibling tools such as get_stats or get_brand_stats.

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