CarHunt

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

Annotations already indicate readOnlyHint=true, confirming no side effects. The description adds that the tool returns aggregated statistics (median price, active ad count) and mentions segment parameters (year±1, mileage±20k). This provides moderate behavioral context beyond annotations, but does not detail rate limits or data freshness.

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 concise with two sentences, front-loading key information in English. The French sentence adds nuance without verbosity. It is efficient but could be slightly more structured (e.g., separating input from output).

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 only provides high-level output details (median price, volume, segment). It lacks specifics on response format, field names, or pagination. For a stats tool, this is adequate but not complete.

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 50% (year and mileage have descriptions). The description adds segment semantics (year±1, mileage±20k) which clarifies the optional parameters' role. However, make and model parameters receive no additional explanation beyond type, and the description does not fully compensate for the missing schema descriptions.

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 states it provides market statistics (median price, volume) for a used car model in France. The verb 'statistics' and specific output metrics make the purpose distinct. However, it does not explicitly differentiate from sibling tools like estimate_car_price or search_used_cars, so it falls short of a 5.

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 guidance on when to use this tool versus alternatives such as estimate_car_price or pro_market_position. The description lacks any mention of prerequisites, limitations, or context for appropriate use.

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 indicate readOnlyHint=true, so no destructive behavior. The description adds behavioral details: output includes quartiles (Q1, median, Q3), confidence index, and similar ads. It also mentions rate limits per IP and authentication tiers. No contradictions 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 short: two sentences with the core purpose and key behavioral notes (outputs, limits). It is front-loaded with the English purpose. Could be slightly more concise by avoiding French duplication, but it's not overly verbose.

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?

The description explains the output structure (quartiles, confidence, similar ads) despite no output schema. It covers rate limits and authentication. Missing error handling or input validation details, but for a read-only estimation tool with clear inputs, it is sufficiently complete.

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 has 100% parameter description coverage, so the baseline is 3. The description provides general context (based on comparable market ads) but does not add specific meaning to individual parameters beyond what the schema already states.

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 states the tool estimates the market price of a used car in France, using comparable ads. It distinguishes itself from siblings like 'search_used_cars' or 'car_market_stats' by focusing on price estimation with quartiles and confidence indices.

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 usage context by specifying daily limits for free accounts (3/day) and paid plans (15/day or unlimited). It doesn't explicitly state when not to use it or list alternatives, but the purpose is clear enough to avoid confusion with siblings.

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 declare readOnlyHint=true, which the description supports by describing a read-only feed. The description adds behavioral details: sorting by deal-score, default score threshold (60), incremental polling (since parameter), and mention of scraping activity. These go beyond annotations without contradiction.

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 concise: one English sentence stating purpose, followed by a brief French explanation of the deal feed and scoring. It is front-loaded and contains no superfluous information, earning its space efficiently.

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 20 parameters, no required fields, and no output schema, the description is incomplete. It does not explain the return structure or pagination details beyond page/limit. It covers the core concept but lacks comprehensive context for full usage.

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 90%, so most parameters are documented in the schema. The description adds limited extra meaning, e.g., model family expansion and incremental polling for 'since'. It does not significantly enhance understanding 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 states the tool provides an underpriced car deals feed sorted by deal-score. It distinguishes itself from siblings like pro_search by focusing on a specific feed of underpriced deals, and includes context about the default min_deal_score.

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 mentions a prerequisite (Business API key) and implies use for finding underpriced deals, but lacks explicit guidance on when to use this tool versus alternatives like pro_search or search_used_cars. No exclusions or when-not-to-use instructions are given.

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 as read-only (readOnlyHint=true). The description adds context about output (segment median, savings) but does not detail exact response fields or formatting. This is adequate but not rich.

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 front-loaded with purpose and outputs, but the bilingual repetition adds slight redundancy. Overall, it is concise enough and wastes little space.

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-param tool with read-only annotations and no output schema, the description covers the key aspects: what it returns, how to get the input. It could be more precise on output structure, but is largely complete.

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 0% schema description coverage, the description fully compensates by explaining that listing_id comes from pro_search/pro_deals results, providing critical context the schema lacks.

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 states the tool provides market position (segment median, savings vs. market) for a specific listing, distinguishing it from sibling tools like pro_search or car_market_stats.

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 explicitly maps listing_id to the 'id' field from pro_search/pro_deals results, giving clear sourcing guidance. It lacks explicit when-not-to-use or alternatives, but the context of sibling tools implies differentiation.

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, so the tool's read-only nature is known. The description adds context about quota consumption, incremental polling, and pagination, which are beyond the annotations and helpful for the agent.

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 concise, with three sentences that front-load key features (deal-score, pagination, polling) and include important constraints (API key, quota). No unnecessary words.

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 complex tool with 21 parameters and no output schema, the description covers main behaviors: filters, sorting, incremental polling, and quota. It is adequate though could mention the output structure briefly.

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 high at 86% with most parameters described. The description adds meaning beyond the schema by explaining concepts like 'deal-score de sous-cote' and 'polling incrémental (since),' enhancing understanding.

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 'Full professional search with deal-score, 50 results/page, incremental polling,' clearly specifying the tool's purpose and distinguishing it from siblings like search_used_cars and pro_deals.

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 mentions that the tool requires a CarHunt Pro API key and consumes monthly vehicle quotas, but it does not explicitly state when to use this tool versus alternatives. However, it implies professional use with advanced features.

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 (safe read). The description adds that it returns specific fields (quota, consumed, remaining, extra credits), which is useful context beyond annotations. No contradiction.

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 short and front-loaded, but repeats the same information in English and French, which adds slight redundancy. Still concise overall.

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 no output schema, the description lists the returned fields adequately. However, it could mention data types or structure. Still sufficiently complete for a simple zero-parameter tool.

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?

No parameters, so the description doesn't need to explain parameter usage. Baseline of 4 is appropriate as the description adds no param info, but none is needed.

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 specifies the resource (current month API usage) with a list of data elements (quota, consumed, remaining, extra credits). This distinguishes it from sibling tools like car_market_stats or pro_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?

No explicit guidance on when to use this tool versus alternatives. The context implies it's for checking API consumption, but there's no mention of when not to use it or what other conditions apply.

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 description adds significant behavioral context beyond annotations: it discloses the write scope requirement, the ~10 min push frequency, and the quota deduction for delivered vehicles. This aligns with readOnlyHint=false and openWorldHint=false with no contradictions.

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 extremely concise—two sentences in English and two in French—with no filler. Each sentence provides distinct value: function, webhook detail, requirements. Front-loaded with the key action.

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 17 parameters, no output schema, and 65% schema coverage, the description explains the webhook behavior but does not mention return values or complete parameter documentation. It is adequate for the core function but leaves gaps for an agent to infer details.

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 description does not add any parameter-level meaning beyond the existing schema descriptions. With 65% schema coverage, several parameters (name, finition, motorization) remain under-documented, and the description does not compensate for this gap. Baseline of 3 is lowered due to missed opportunity.

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 states the tool creates a watchlist that pushes matching listings to a webhook. It distinguishes itself from sibling tools like pro_watchlist_delete and pro_watchlist_list by focusing on creation, and from search tools by its persistent nature.

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 specifies that an API key with write scope is required, which is a clear usage guideline. It implies when to use (to set up an alert with webhook) but does not explicitly exclude alternatives or provide when-not guidance. Sibling tools provide some context.

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?

Description states 'delete' which implies a destructive write, but annotations set destructiveHint to false, creating a direct contradiction. Score 1 per guidelines for contradiction.

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, front-loaded with the core action. The French repetition is slightly redundant but concise overall.

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 simple delete tool with one parameter and no output schema; description conveys basic action but omits important context like irreversibility or error behavior. Adequate but not thorough.

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 one parameter (watchlist_id) with no schema description (0% coverage). Description adds minimal context ('by id') but no format or example, insufficient for a parameter with no schema documentation.

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?

Clear verb ('Delete') and resource ('watchlist by id'), distinct from sibling tools like pro_watchlist_create and pro_watchlist_list.

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?

No guidance on when or when not to use, no prerequisites or alternatives mentioned. Only states the action itself.

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 declare readOnlyHint=true, matching the list operation. The description adds useful context: watchlists are real-time alerts with ~10 min delay and delivery methods (email, Discord, webhook JSON). No contradiction.

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 wasted words. Purpose is front-loaded and immediately actionable.

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?

No output schema exists, and the description does not specify what fields the list returns (e.g., names, IDs). This is a gap for a listing tool.

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 no parameters, so schema coverage is 100%. Per guidelines, baseline for 0 parameters is 4; the description adds no param info but does not need to.

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 explicitly states 'List the organization's watchlists', using a clear verb-resource structure. It distinguishes from sibling tools like pro_watchlist_create and pro_watchlist_delete.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies it is for listing watchlists, but does not mention prerequisites 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?

Annotations already declare readOnlyHint=true, and the description adds behavioral details: result limits by key, deal_score availability, and that source_url is always included and must be cited. This information goes beyond the annotations, though it does not cover all potential behaviors like rate limiting.

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 moderately concise at 4 sentences, front-loading the core purpose. It mixes English and French but remains clear. No unnecessary repetition; every sentence adds value. Slightly longer than necessary but acceptable.

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 14 parameters, high schema coverage, and no output schema, the description adequately covers the key tier behavior and source_url requirement. It does not detail return format or pagination, but for a search tool with these details, it is fairly complete. Missing differentiation from sibling tools reduces completeness slightly.

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 93% (13/14 parameters described), so the description adds limited parameter-level value. However, the free-text description complements by explaining authentication impact on 'limit' and 'sort' parameters (e.g., deal_score requires key). This extra context justifies a score above 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 clearly states 'Search used cars for sale in France across all major marketplaces' and lists specific marketplaces. While the purpose is very clear, it does not explicitly distinguish from the sibling 'pro_search' tool, which may cause ambiguity.

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 explains tiered access (free vs. Premium/Pro key) and result limits, providing some guidance. However, it lacks explicit instructions on when to use this tool versus alternatives like 'pro_search' or other sibling tools, and no exclusion criteria are mentioned.

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