Market and Regulatory Data Feeds — Zinin M2M Hub

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

Annotations already indicate read-only and non-destructive behavior. The description adds useful context about how the tool operates (walks sitemap, visits each detail page) and pricing. Parameter descriptions further reveal behaviors like compensating for closed jobs and lack of server-side keyword search, going beyond the existing 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 main description is two concise sentences, effectively summarizing the tool's purpose, source, and output. Parameter descriptions are detailed but purposeful, with no filler. The pricing note is brief and useful. Overall, tightly structured and front-loaded.

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?

Despite having no output schema, the description specifies the row fields (title, company, location, posted date, link) and explains the data acquisition method. With 5 parameters thoroughly described and no required params, the tool is fully self-contained and complete for an agent to use correctly.

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%, but the description enriches each parameter with practical semantics: max_items explains target vs. guarantee, freshness_days explains the 'bump' behavior, keyword_filter clarifies client-side filtering, and fetch_full_description notes no extra request cost. This adds significant value 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's function: fetching job postings from Azerbaijan's boss.az. It specifies the data source (sitemap and structured job markup) and output fields (title, company, location, posted date, link), distinguishing it from other job-related siblings by region and site.

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 usage for accessing boss.az job postings but does not provide explicit guidance on when to use this tool versus alternative job listing tools (e.g., jobs-ch-swiss, xing-jobs). No exclusions or alternative recommendations are mentioned.

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 destructiveHint=false, so the description adds value by disclosing that it uses a public API (no login/browser/proxies) and the cost per call ($0.02). This goes beyond the annotations and gives the agent actionable behavioral knowledge.

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 covering the core function and one key behavioral detail (pricing). Every sentence earns its place with no redundancy or fluff. The pricing line is a useful extra, not a distraction.

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 input schema is fully covered, but there is no output schema and the description does not hint at the structure of the returned listings. The agent knows what it gets ('live classified ad listings') but not the fields or format. For a tool with no output schema, a bit more detail on the return value would improve completeness.

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% – both parameters (`items` and `maxConcurrency`) are well-documented in the schema with format, examples, and constraints. The tool description does not add new semantic meaning beyond what the schema already provides, so the baseline score of 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 uses a specific verb 'Pull' and clearly identifies the resource ('live classified ad listings from Chotot's public JSON API') and the dimensions ('by region and category'). It also distinguishes the tool from siblings by specifying the platform (Chotot Vietnam) and method (no login/browser/proxies).

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 states the tool's scope (Chotot Vietnam, region/category) but does not explicitly tell when to use it versus alternatives. It lacks comparative guidance with sibling tools like `rightmove-london` or `otodom-warsaw`. The scope is implied by the name and description, but no 'when not to use' or alternative suggestions are provided.

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 destructiveHint=false, so the safety profile is clear. The description adds significant behavioral detail: it uses the official ClinicalTrials.gov API v2, is free with no login needed, costs $0.02/call, and provides real-time updates with sorting by most recent. This fully leverages the provided context.

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 sentence with precise details: what is watched, output fields, sorting, data source, pricing, and authentication. Every word adds value with no redundancy. Front-loaded with the core purpose.

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 the tool has 4 parameters with 100% schema coverage, readOnlyHint and openWorldHint annotations, and no output schema, the description is complete. It clarifies the output format (NCT id, status, phase, sponsor, URL), data source, cost, and free access model. No missing information for an agent to select or invoke this tool correctly.

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 each parameter is already described in the schema. The description adds context that the queries are for 'conditions, drugs or sponsors' and that the tool returns 'one or more matching trial rows per query', which clarifies the array nature of results beyond schema details. However, it does not explain the behavior of 'maxConcurrency' 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 monitors new and updated clinical trials for specified conditions, drugs, or sponsors, and lists the output fields (NCT id, status, phase, sponsor, study URL). This is specific and distinct from sibling tools like 'fda-approval-feed' or 'drug-adverse-events', which focus on approvals or adverse events.

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 monitoring of clinical trials with explicit output fields and sorting, but does not mention when to use it versus alternatives like 'fda-approval-feed' (which covers approvals) or 'sec-edgar-watcher' (financial filings). It implies use for clinical trial tracking without excluding other contexts.

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 destructiveHint=false, so the agent knows it's a safe read operation. The description adds cost per call and the exact output fields (title, company, location, URL, posted-when), which are behavioral traits beyond the annotations. It does not mention rate limits or authentication, but the cost disclosure is valuable.

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 sentence plus a cost note, with zero wasted words. It front-loads the action, scope, and output, making it easy to scan. Every sentence 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 tool with no output schema and only two parameters, the description is fairly complete: it explains the purpose, scope, output fields, and cost. It does not mention pagination, result limits, or error handling, but the schema's maxItems and prefill provide additional context. The description is sufficient for an agent to use the tool correctly.

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 parameters. The description adds the supported country codes and re-emphasizes the query format, but this largely echoes the schema's description and prefill. The baseline of 3 is appropriate because the description adds marginal value 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 verb 'Search', the resource 'Computrabajo job listings', and scope (5 LatAm countries). It lists the output fields, making the purpose unambiguous. The tool name itself is specific to a platform, naturally distinguishing it from siblings like 'job-postings-aggregator' or 'xing-jobs'.

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 lists the countries and mentions keyword search, which implies the intended use case. It does not provide explicit 'when not to use' or contrast with sibling tools, but the specificity of the platform and region makes the context clear enough for an agent to decide.

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 destructiveHint=false, so safety is covered. The description adds beyond annotations by disclosing the output as 'structured rows' with specific fields, and mentions the $0.03/call cost and x402 payment mechanism—useful behavioral context. 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 a single sentence that efficiently conveys purpose and output, followed by pricing. No filler words, clearly front-loaded, and every phrase 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?

With no output schema, the description compensates by listing the output fields and indicating structured rows. It also includes pricing, which is relevant for agent decision-making. Minor gaps include no mention of result ordering or handling of empty results, but the description is complete enough for a straightforward search scraper with well-annotated safe behavior.

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 each parameter (query, max_items, max_pages) already has a meaningful description. The tool description does not add extra parameter semantics, matching the baseline for high schema coverage.

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 a specific verb ('Search') and resource ('Detik news'), and enumerates the exact fields returned (headlines, excerpts, timestamps, sections, images, canonical article URLs). This clearly distinguishes it from sibling scrapers targeting other sites or data types.

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 use case is implied by 'Search Detik news' and the listed output fields, but the description does not explicitly say when to use this tool versus alternatives or provide exclusions. No comparison to sibling tools is offered, leaving the agent to infer fit from the name and purpose.

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 destructiveHint=false; the description adds value beyond this by noting 'No login, no browser, no proxies' and mentioning the $0.02/call cost. This provides auth and operational context not present in 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 a concise two-sentence summary, front-loaded with the core action and resource. Every clause adds value: live data, source, scope, access method, and cost. No unnecessary 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?

Given the rich schema (5 params, full descriptions), read-only annotations, and clear description of source/scope/access, the tool is fully specified for selection and invocation. No output schema exists, but the purpose of returning listings is unambiguous.

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?

Input schema covers 100% of parameters with detailed descriptions. The tool description only echoes 'by deal type (sale/rent) and property type,' adding no new meaning beyond what the schema already provides. 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 clearly states the tool pulls live apartment/housing listings from Emlakjet.com for Istanbul, naming the specific portal and city. It distinguishes from sibling real-estate tools, which target other portals/cities.

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 clear context for when to use it (Istanbul listings from Emlakjet, no login/browser/proxies) but does not explicitly mention when not to use it or name alternatives. It implies the appropriate use case without exclusion 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 readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: free and no login required, official openFDA data, and cost ($0.02/call in USDC on Base). This goes beyond the annotations by disclosing pricing and authentication requirements.

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: three sentences plus a cost note. It front-loads the core purpose ('Watch drugs or companies...') and wastes no words. Every sentence provides essential information (what it does, data source, return details, cost).

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 the absence of an output schema and the tool's moderate complexity (4 parameters with full schema coverage), the description adequately covers the tool's capabilities. It details the types of information returned (application status, sponsor, latest submission, recall details) and adds pricing. However, it lacks guidance on how the 'watch' behavior works (e.g., polling frequency, whether results are incremental) and doesn't mention potential rate limits or pagination.

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% with all parameters having descriptions. The tool description does not add any additional meaning beyond what the schema already provides for parameters like `queries`, `limit`, `dataset`, or `maxConcurrency`. Baseline score of 3 is appropriate since the description adds no value here.

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 starts with a specific verb ('watch') and clearly identifies the resource (drugs or companies for FDA approvals and recalls). It distinguishes from sibling tools like clinical-trials-monitor by focusing on FDA regulatory actions rather than clinical trials. The scope (new approvals and recalls) and data source (openFDA) are 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?

The description implies usage for monitoring FDA approvals and recalls but provides no explicit guidance on when to use this tool versus alternatives (e.g., clinical-trials-monitor for clinical trial data, or sec-edgar-watcher for SEC filings). It also doesn't mention when not to use it.

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 annotations, the description discloses important behavioral details: it is an 'Unofficial, independent Actor; not affiliated with or endorsed by any named source publisher' and states pricing as '$0.05/call, x402 (USDC on base).' This adds meaningful context about cost and trust, complementing 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 exceptionally concise, leading with the core purpose in one sentence, followed by a brief disclaimer and pricing. No wasted words; it is appropriately front-loaded and scannable.

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?

Although the description is brief, it is supplemented by a rich input schema that describes output as 'one whole paid batch of 20–40 explainable buyer-agency demand signals.' Together they provide adequate context for selecting and invoking the tool, though the description alone lacks usage-alternative guidance.

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% — every parameter has a detailed description with examples, defaults, and constraints. The tool description itself adds no parameter-specific semantics, so the baseline score of 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?

The description clearly specifies the tool's function: 'Convert official PPS contract aggregates into buyer-agency demand priorities.' It names the resource (PPS contract aggregates) and the output (demand priorities), making it distinct from generic tender alerts, though it does not explicitly contrast with sibling tools.

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 no explicit guidance on when to use this tool versus alternatives, nor any exclusions or conditions. The implied use case for Korean public procurement demand analysis comes from the tool title and schema context, not the description 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 already declare readOnlyHint=true and openWorldHint=true. The description adds value by noting 'No API key, no browser — public TED search API only' and the cost ($0.02/call, x402 USDC). No contradictions with annotations. It could mention rate limits or result ordering, but overall it enriches the behavioral profile.

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 three sentences, each with distinct purpose: purpose + returns, ease of use, cost. Front-loaded, no wasted words, and easy to parse. Perfectly concise for the tool's complexity.

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 4 parameters with 100% schema coverage, no output schema, and no nested objects, the description effectively covers the tool's purpose, return fields, key constraints, and cost. It could add details about result ordering or pagination, but the overall picture is complete enough for an agent to use the tool correctly.

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 baseline is 3. The description reinforces the schema by mentioning 'keyword or CPV code' (mapping to queries) and 'filtered by buyer country' (mapping to country). It does not add new syntactic or semantic details beyond the schema's own 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 the tool searches EU public-sector tenders on TED Europa by keyword or CPV code, with optional country filter. It specifies the return fields (title, buyer, country, etc.). However, it does not explicitly differentiate from sibling tools like 'tender-alert' or 'uk-public-tender-lead-alert', leaving the agent to infer scope differences.

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 context (EU tenders, public TED API, no auth) but does not explicitly state when to use this tool vs. alternatives. Usage is implied by the scope 'EU public-sector tenders', but no when-not guidance or sibling tool comparisons 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 readOnlyHint and destructiveHint, and the description adds useful behavioral details like 'No login, no browser, no proxies' and 'live' listings. It also mentions cost, which is beyond structured annotations, but does not detail output structure or pagination behavior.

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, front-loaded with the core purpose, followed by concise value propositions. Every sentence serves a purpose, and it is compact.

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?

Despite no output schema, the description clearly states it returns listings, and the schema defines pagination and count parameters. It is largely complete for a read-only scraping tool, though it lacks details about returned fields.

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 parameters are fully documented in the schema. The description's mention of 'deal type, property type and city' adds no meaning beyond existing parameter descriptions. Baseline of 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 clearly states the tool pulls live apartment and house listings from Imovirtual.com, a specific resource, and identifies key filters (deal type, property type, city). This distinguishes it from sibling tools focused on other real estate portals/countries.

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 clear context that this is for Imovirtual.com, Portugal's real estate portal, implying its use case. It does not mention explicit alternatives or exclusions, but the context is unambiguous given the title and description.

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 destructiveHint=false, so the tool is safe. The description adds value by noting it's free and uses official SEC EDGAR data, and transparently mentions the cost ($0.01/call) and currency (USDC on Base). It does not describe pagination or the exact format of the return value, but given that there is no output schema, this is a minor 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 fairly concise at two sentences plus pricing info. It is front-loaded with the core purpose. The only minor inefficiency is the redundant mention of 'free' and 'no API key or login' which could be streamlined, but overall it's well-structured.

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 covers the tool's core purpose and constraints (free, no login), and the schema fully documents parameters. However, it lacks details about the output format (is it a list of filing documents? a summary table?) and pagination behavior. Without an output schema, the description should provide more information on what the response contains to be considered 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 description coverage is 100%, so the baseline is 3. The description adds value by summarizing the output 'Get filing counts, an at-a-glance activity signal (none/low/high) and direct document links per company', which clarifies what data the `tickers` parameter will return. However, the description does not add new constraints or semantics beyond what the schema already provides for each parameter.

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 verb 'Track', the resource 'insider stock trades — SEC Form 3/4/5 filings', and the scope 'for any list of tickers'. It explicitly differentiates from siblings like 'sec-edgar-watcher' (which likely monitors filings in general) and 'thirteen-f-tracker' (which tracks 13F institutional holdings) by specifying Form 3/4/5 insider filings and providing specific output elements (filing counts, activity signal, direct document links).

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 clear context for when to use this tool: to get an at-a-glance signal of insider trading activity (none/low/high) and filing counts per company. It mentions using official SEC EDGAR data with no API key or login needed, which sets expectations. However, it lacks explicit guidance on when NOT to use it or what alternatives (e.g., 'thirteen-f-tracker' for institutional, not insider, holdings) would be more appropriate.

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 discloses stateful behavior (creates a baseline on first run, returns only postings since previous check) and adds pricing/token details. Annotations already indicate idempotency and open-world traits, so the description adds contextual specifics beyond the structured fields.

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 only two sentences plus a billing note, front-loading the core function, covering the key edge case, and ending with cost/token info. Every sentence serves a purpose with 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?

The description explains the primary behavior and an important edge case (first run 'says so'), and includes pricing. While there is no output schema and the return structure is not detailed, the comprehensive input schema and clear behavioral summary make it adequately complete for a stateful alert 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?

Schema coverage is 100% with rich descriptions for each parameter. The tool description itself does not add parameter-specific meaning, relying entirely on the schema's detailed field descriptions, which meets the baseline but does not exceed it.

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 a specific verb ('watches'/'returns') and a clear resource ('job board') with scoping ('saved filter' and 'new postings'). It distinguishes from sibling job board scrapers by emphasizing the alert/comparison behavior rather than simple listing.

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 use case (monitoring a board for new postings) and notes the first-run baseline behavior, which provides initial guidance. However, it does not explicitly compare to alternatives like directly using the board's own Actor, nor does it state when not to use it.

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, destructiveHint=false, and openWorldHint=true. The description adds behavioral value beyond annotations: it confirms no login/scraping/proxies required, hints at cost behavior ($0.02/call), and implies normalization (extracting fields). There is no contradiction with annotations. Slight gap: doesn't explain what happens if a company slug is invalid or an ATS provider fails, but the concurrency parameter and maxItems limit mitigate risk.

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 plus a pricing tag. Every word adds value: the first sentence states the action and output fields, the second clarifies the absence of login/scraping/proxies. The price and payment detail are front-loaded in the same concise block. No filler, no repetition of schema info.

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 the tool's complexity (aggregator with varying ATS providers, concurrency settings, and normalized output), the description covers the core workflow, provider support, and cost. There is no output schema, so the description compensates by listing the output fields. It doesn't mention error handling (e.g., invalid slugs or rate limits), but the concurrency parameter and example prefills provide some guidance. Slight gap for full completeness.

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%. The description adds minimal parameter semantics beyond the schema, but the schema itself is rich: for 'items', it explains the 'provider:company' format with URL examples and allowed providers; for 'maxConcurrency', it gives defaults and bounds. The overall description normalizes the output fields but doesn't detail them in the parameter section—output schema is absent, so the description of normalized fields (title, location, etc.) partially compensates, earning a 4 instead of baseline 3.

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 the tool pulls open roles from ATS systems (Greenhouse, Lever, Ashby) and normalizes them into structured rows. It distinguishes itself from siblings like 'xing-jobs' or 'computrabajo-jobs' by specifying the exact providers and the action of normalizing. The verb 'Pull' and resource 'open role from a company's public applicant-tracking system' are specific and 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?

The description clearly states when to use this tool ('Pull every open role from a company's public applicant-tracking system') and provides explicit capabilities ('No login, no scraping, no proxies.'). It implicitly sets expectations against alternatives by naming its provider scope, and the pricing note adds context for cost-sensitive selection. While it doesn't name specific sibling tools to avoid, the scope is well-defined enough.

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 adds useful behavioral context: it retrieves 'public job listings' (no auth implied) and discloses the per-call cost ('$0.02/call, x402 (USDC on base)'). It does not contradict annotations and offers more than a bare statement of the operation, though it omits details like rate limits or anti-scraping behavior.

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 tight sentence that packs the core purpose, target site, geographic scope, and return fields, followed by a cost/payment note. There is no filler, redundancies, or repetition of schema content. Every clause 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?

Given the absence of an output schema, the description compensates by listing the returned data fields (title, company, location, employment type, posted date, URL). It also covers cost and the public nature of the data. It is not exhaustive – e.g., it doesn't state that scraping may be slow or that lives results depend on website availability – but for a read-only scraper with strong annotations, this is broadly sufficient.

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 input schema provides complete descriptions for all 5 parameters, so the description does not need to restate them. The description's mention of 'by keyword' aligns with the 'keywords' parameter and the listed output fields add meaning, but it does not clarify the optional location, max_items, max_pages, or fetch_full_description semantics beyond the schema. With 100% schema coverage, the 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 opens with 'Search jobs.ch (Switzerland) by keyword' – a specific verb ('search'), a clear target resource ('jobs.ch'), and geographic scope ('Switzerland'). It also enumerates the output fields (title, company, location, employment type, posted date, URL), which unambiguously distinguishes this from sibling scrapers targeting other platforms or countries.

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 the tool: when you need public job listings from jobs.ch in Switzerland. It does not explicitly name alternative tools or state 'when not to use,' but the country/platform scope provides clear contextual guidance. A direct exclusionary note would strengthen this, but it is not misleading.

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 destructiveHint=false. The description adds valuable context beyond annotations: 'No login, no browser, no proxies' discloses authentication requirements, and '$0.02/call, x402 (USDC on base)' reveals pricing and payment method—useful operational details not present in 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, each with distinct value: the first states purpose and filters, the second adds operational details (no auth, cost). It is front-loaded, free of fluff, and every clause contributes meaning.

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 listings fetch tool with four params and no output schema, the description covers the data source, filter scope, access prerequisites, and cost. The agent has enough context to decide whether to invoke it and what to pass, matching the completeness bar for a filtered-list 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?

Schema coverage is 100%, with each parameter having a detailed description (e.g., queries format 'sale:apartment:almaty'). The description echoes filter dimensions (deal type, property type, city) but adds no new parameter-specific information, so it meets the baseline without exceeding it.

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 the verb 'Pull' and specifies the resource: 'live apartment and house listings straight from Krisha.kz' with filters for deal type, property type, and city. It clearly distinguishes itself from sibling real-estate tools by naming the specific portal and location (Kazakhstan).

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 the tool is for Kazakhstan real estate data by naming the country and the portal, and notes operational ease ('No login, no browser, no proxies'). However, it does not explicitly state when not to use it or name alternative tools, so it falls short of the highest bar.

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, openWorldHint=true, and destructiveHint=false, so the description only needs to add value beyond that. It does so by stating it uses DexScreener's public API and costs $0.01/call via x402 (USDC on base). Some behavioral traits are missing: e.g., what happens if a token isn't found, rate limiting, or response structure. But the safety/destructive profile is fully covered by annotations, and the cost/API backend is useful additional context. 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 extremely concise—three short sentences that front-load the core purpose and data returned, then the 'keyless' benefit, then the cost model. Every sentence serves a distinct purpose, there is no wasted text, and the information is structured for quick scanning.

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 the tool's simplicity (3 parameters, no output schema, read-only), the description covers the essential use case well. It lacks details on error handling (e.g., what if a token address is invalid) or response format, but for a live price oracle with good annotations and a clear pricing model, the description is sufficiently complete for an AI agent to use it correctly. A perfect score would require mentioning response shape or fallback behavior.

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 baseline is 3. The description adds value by clarifying the tokens parameter accepts contract addresses, tickers, or search terms, and that chainId restricts to one EVM chain. The maxConcurrency parameter's purpose is already clear from its schema description. The description does not add meaning to maxConcurrency beyond the schema, but overall it provides helpful semantic context that makes usage intuitive.

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 the verb ('get current USD price') and resource ('any token by contract address or ticker'), along with the data returned (24h change, liquidity, volume, best DEX pair). It clearly distinguishes itself from siblings, none of which are price oracles, making its unique role obvious.

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 strong guidance: 'Keyless, no wallet, no RPC node — DexScreener's public API. Built to be called cheaply by AI agents that just need the number.' This explicitly tells the agent when to use it (when a cheap, simple price lookup is needed) and implies when not to use it (if detailed on-chain data or authentication is required). The pricing note ($0.01/call) adds further usage context. Alternatives are implicitly clear given the sibling names, which focus on jobs, listings, tenders, etc.

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=false, openWorldHint=true, idempotentHint=false, destructiveHint=false. The description adds useful context: it is 'Unofficial, independent Actor; not affiliated with or endorsed by any named source publisher,' and cites a per-call cost. However, it does not clarify what 'action evidence' entails or whether any state changes occur beyond what annotations imply.

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 long and front-loaded with the core purpose, followed by cost and independence disclaimer. Every sentence carries relevant information without unnecessary verbosity.

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 the tool's complexity (7 parameters, nested watches array, no output schema), the description is too sparse to orient an agent. It leaves 'action evidence' undefined, does not explain what the tool returns, and omits limitations or operational details. While the schema covers parameters, the high-level description should provide more context for a tool of this sophistication.

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 input schema provides 100% description coverage for all 7 parameters, including detailed explanations for watches, keywords, matchMode, categories, reviewWindowDays, requestId, maxSignals, lookbackDays, maxDocuments, publicationDate, and maxTotalChargeUsd. The tool description adds no parameter-specific details, so the baseline of 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 clearly states the tool's core function: 'Turn today’s allowed official publications into watchlist-linked action evidence.' The verb 'turn' and the specific resource (Resmî Gazete official publications) make the purpose evident, and the 'watchlist-linked action evidence' angle distinguishes it from sibling job/property/tender trackers.

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 no guidance on when to use this tool versus alternatives. It omits exclusions, prerequisites, or comparisons to sibling tools. The only extra information is the independence disclaimer and cost, which are not usage guidelines.

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 read-only and non-destructive behavior. The description adds useful behavioral details: 'live' fetching, no authentication/proxy setup, and the $0.02/call fee with x402 payment rail. These go beyond the structured annotations and help the agent understand operational and cost implications.

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: the first sentence identifies the resource and filters, and the second adds access and pricing. Every clause earns its place with no filler. The em-dash structure is slightly informal but does not hurt readability.

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 tool has no output schema, so the description should hint at what returned listing rows contain. It says 'live apartment and house listings' but does not specify fields like price, URL, or number of rooms. While the input parameters are thoroughly documented, the absence of any return-format description leaves a notable gap for a scraping 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?

Schema description coverage is 100%, so the baseline is 3. The description mentions deal type, property type, and city, but this merely echoes the schema fields. It does not add new semantic meaning for max_items, max_pages, or the exact path format that the schema already explains.

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 ('Pull') and resource ('Otodom.pl — Poland's biggest real-estate classifieds portal') with clear scope (by deal type, property type, and city). It immediately distinguishes itself from sibling real-estate tools by naming the exact source and country.

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 clear context for when to use this tool: it is the tool for Polish Otodom.pl listings, highlighted by 'Poland's biggest real-estate classifieds portal'. It also notes 'No login, no browser, no proxies' as practical advantages. However, it does not explicitly mention when not to use it or name alternatives, so it misses the top tier.

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, destructiveHint=false, and openWorldHint=false. The description adds behavioral context beyond annotations by stating the tool lists paid tool prices and addresses, and that it's free to call. No annotation contradiction exists. Minor deduction for not mentioning pagination or result format, but with no output schema and 0 parameters, the description covers essential behavior well.

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 sentence of 23 words, efficiently packed with purpose, output content, and usage guidance. No filler words or redundant phrases. Every part serves a clear function.

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 0-parameter, no-output-schema tool with good annotation coverage, the description is mostly complete. It states what's listed (paid tools, price, payTo, network) and when to use it. Lacks mention of output size limits, but the list of bundled tools is likely manageable. The description's brevity is reasonable for a simple informational 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 0 parameters and schema description coverage is 100%, so the schema is trivially complete. The description adds value by explaining what the output will contain (price, payTo address, network for each paid tool in the bundle), which compensates for the lack of output schema. No parameter-specific info is needed since there are no params.

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 lists paid tools in the 'market-data' bundle with price, payTo address, and network. While the verb 'list' is appropriate and the resource is specific, the tool name 'pricing_info' is generic, and the title 'Pricing — Market & Regulatory Data Feeds' is broad. It distinguishes from siblings (e.g., live-price-oracle) by focusing on bundle pricing, not real-time quotes.

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 says 'Call this first if you don't have a wallet ready yet', providing a clear when-to-use directive that orients the agent before other wallet-related tools. No explicit when-not-to-use is needed given the tool's introductory purpose, and the sibling list contains many diverse tools that are obviously distinct.

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 destructiveHint=false; the description adds valuable context beyond this: 'No login, no browser, no proxies' and a per-call cost. It also references robots.txt and sitemap usage in the emirate parameter, giving insight into compliance and technical approach, though it does not describe failure modes or return formats.

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 concise sentences: the first covers the core function and filters; the second covers logistics (no login, cost). No filler, front-loaded with the most relevant action. Every clause adds information.

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 tool with five optional parameters and no output schema, the description provides a complete high-level picture: what data is fetched, the source, sorting, and operational constraints. The parameter descriptions flesh out the details. It does not describe the response structure, but that is often acceptable when listing rows are predictable and no output schema exists.

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 each parameter has a detailed description with enums and constraints. The main description adds no new parameter semantics beyond naming deal type and emirate, which is already covered. Baseline 3 is appropriate since the schema carries the burden.

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 specific verbs and resources: 'Pull live apartment, villa, penthouse and townhouse listings straight from PropertyFinder.ae', and identifies the portal as the UAE's biggest real-estate portal. It clearly distinguishes from sibling real-estate tools by geographic scope and portal, avoiding any 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 implies usage for UAE real-estate listings but does not explicitly state when to use this tool over alternatives, nor does it exclude other tools. It lacks explicit 'when to use' or 'when not to use' guidance that would rank higher.

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 destructiveHint=false. The description adds value by noting the live data source, the absence of login/browser/proxy requirements, and the per-call cost. These are useful behavioral traits beyond the annotations, though pagination behavior and result format are not disclosed.

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, front-loaded with the core purpose, and includes only essential extras (access method and cost). Every word earns its place; no noise.

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 listing-retrieval tool with fully documented parameters, the description gives enough context to select it appropriately. However, there is no output schema and the description does not describe the shape or contents of the returned listings, leaving a minor gap in completeness.

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 input schema provides detailed descriptions for all 5 parameters (100% coverage), so the baseline is 3. The description only references the filter dimensions (deal type, property type, region) without adding semantic detail beyond what the schema already provides.

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 pulls live apartment and house listings from Realitica.com, specifies the geographic scope (Montenegro, Croatia, Serbia), and lists the filtering dimensions (deal type, property type, region). This specific verb+resource+scope uniquely distinguishes it from sibling real-estate tools.

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 it: when you need real estate listings from the Adriatic region via Realitica.com. It also adds practical usage context (no login, no browser, no proxies, $0.02/call). However, it does not explicitly contrast with alternative portals or mention when not to use it.

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 discloses the stateful behavior of the tool: 'The first run on a new filter creates the baseline and says so,' which is critical for understanding its operation. It also adds pricing context ($0.05/call, x402 on base) that annotations do not cover. Annotations indicate non-read-only and non-idempotent behavior, and the description complements this 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 composed of only two sentences, front-loading the core purpose and adding baseline and cost details efficiently. Every sentence contributes value, and there is no redundant or filler content.

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 tool has a nested filter object and no output schema, but the description explains the core behavioral contract: it returns only new listings since the previous check and handles baseline creation. It does not detail the output structure or how to reset the baseline, but the schema's baseline_key description addresses watch management, making it adequate for moderate complexity.

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?

All four parameters (filter, portal, max_items, baseline_key) have detailed descriptions in the input schema, achieving 100% schema coverage. The tool description does not add additional parameter-level meaning beyond what the schema already provides, so it relies on the schema for parameter 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 clearly states the tool watches a property portal for a saved filter and returns only listings that appeared since the previous check, giving it a specific verb and resource. This distinguishes it from sibling portal-specific scrapers (e.g., krisha-kz, rightmove-london) by emphasizing its monitoring/alert role. The first-run baseline behavior further clarifies its purpose.

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 periodic monitoring ('since the previous check') and mentions the first run creates a baseline, but it does not explicitly state when to use this tool over the underlying portal scrapers or other alert tools. No alternatives or exclusions are provided, so usage guidance remains implicit rather than explicit.

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 destructiveHint=false, so safety is covered. The description adds meaningful extra context: 'No login, no browser, no proxies' explains auth/execution requirements, and '$0.02/call' provides cost transparency not in 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 one compact sentence with a brief cost note appended; it front-loads the core action and scope. Every segment adds value (source, scope, execution mode, cost), with no fluff.

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 tool is a straightforward read-only listing fetcher; annotations and complete schema parameters cover safety and inputs. The description lacks an explicit return-format statement (no output schema exists), but 'property listings' plus the schema's pagination parameters give enough context for selection and invocation.

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%, with detailed explanations for location_identifier, deal_type, max_items, and max_pages. The description adds no new parameter detail beyond what the schema already provides, so 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 uses the specific verb 'Pull' and identifies the resource as 'live for-sale and to-rent property listings straight from Rightmove.co.uk', clearly distinguishing it from sibling country-portal tools. It also states the scope ('London or any other Rightmove location code').

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 clear context: the tool is for Rightmove UK listings and requires no login/browser/proxies, implying direct API access. It does not explicitly name alternatives or exclusions, but the Rightmove-specific scope and sibling names make the intended use obvious.

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 indicate readOnlyHint, openWorldHint, and non-destructive behavior. The description adds valuable behavioral traits: data sources (honeypot.is + DexScreener), no external dependencies required ('No wallet, no RPC key, no browser'), pricing ($0.01/call via x402), and its heuristic nature. This goes beyond the annotations to inform the agent about cost, setup, and reliability.

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 (approximately three sentences) and front-loaded with the main purpose. It efficiently communicates key aspects: purpose, data sources, detection capabilities, caveat, and pricing. Minor redundancy (e.g., 'Detects honeypots...' partially repeats 'score rug-pull risk'), but overall it earns its space without verbosity.

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 3 parameters and no output schema, the description covers data sources, pricing, dependencies, and heuristic nature. However, it does not describe the output format (e.g., numeric score, label, risk level) or how results are presented per token. This gap leaves the agent uncertain about what the tool returns. For a heuristic signal tool, additional context on output would improve completeness.

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 baseline is 3. The description does not add extra parameter-level meaning beyond what the schema already provides. The schema descriptions for tokens, chainId, and maxConcurrency are clear and complete. The tool description's mention of data sources provides general context but does not enhance parameter 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 clearly states the tool's function: scoring ERC-20/BEP-20 token rug-pull risk using specific data sources (honeypot.is, DexScreener). It explicitly lists what it detects (honeypots, high taxes, thin liquidity, new pairs), distinguishing it from sibling tools like token-launch-radar or live-price-oracle. The verb 'score' and resource 'rug-pull risk' are specific and unambiguous.

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 usage context (assess token risk) but lacks explicit guidance on when to use this tool versus alternatives. It provides a caveat ('Heuristic signal, not financial advice'), which indirectly advises against using it for financial decisions. However, no exclusions or comparisons to sibling tools (e.g., when to use token-launch-radar instead) 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 readOnlyHint=true and destructiveHint=false, establishing this as a safe read tool. The description adds value by disclosing the fee structure ('$0.01/call, x402 (USDC on base)'), explaining the returned data includes 'form, filing date and a direct document URL', and referencing the SEC EDGAR rate limit ('10 requests/second'). This goes beyond annotations by adding cost and output context, though it could mention pagination or result limits if applicable.

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 long (one for purpose, one for filtering and output details) plus a cost line. Every phrase is essential: the verb 'Watch', the supported forms, the data source, the cost/payment info are all front-loaded. There is no fluff or repetition of the tool name, making it a model of conciseness.

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 filtered-list tool with 100% schema coverage and clear annotations (readOnlyHint, destructiveHint), the description is nearly complete. It covers inputs (tickers, form types, lookback), outputs (form, filing date, document URL), cost, and constraints. It loses one point because there is no output schema, so the description's mention of returned fields is essential but could be slightly more precise (e.g., example of the direct document URL format). Still, it is adequate for an agent to invoke correctly.

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%, with each parameter having a detailed description (e.g., 'Stock tickers to watch for new SEC filings', 'Only include these SEC form types', maxItems constraints). The tool-level description reinforces usage by listing key parameters (form type, lookback window) and the returned fields. Since the schema already explains all parameters well, the description adds value by summarizing the overall flow, but does not significantly deepen parameter understanding beyond the schema. Baseline 4 for complete schema coverage with some additional context.

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 starts with a specific verb ('Watch') and clearly identifies the resource (stock tickers for new SEC filings). It lists supported form types (10-K, 10-Q, 8-K, S-1) and distinguishes itself from the many job/real-estate/listing siblings by focusing on SEC EDGAR financial data, which is a unique domain among siblings. The phrase 'Official SEC EDGAR data, free, no API key or login' further clarifies its scope and accessibility.

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 clear context for when to use this tool (to watch stock tickers for SEC filings) and lists key constraints ('free, no API key or login', rate limit reference). It implies it's for financial/ticker monitoring, which distinguishes it from job, real estate, or tender alert siblings. However, it does not explicitly state when NOT to use it (e.g., for non-US filings, or for real-time stock prices) or name a specific alternative sibling, so it gets a 4 rather than a 5.

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 destructiveHint=false. The description adds valuable non-obvious behavior: no authentication required, no browser automation, no proxy needs, and per-call pricing ($0.02). It also clarifies that currency is seller-set (GEL or USD), going beyond basic read-only framing.

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 only two sentences, yet it packs the core purpose, source, scope, currency behavior, access constraints, and pricing. Every clause earns its place; it is front-loaded with the primary function and includes 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?

Given the rich schema and annotations, the description provides enough context for an agent to select and invoke the tool. It lacks a description of the output shape (since no output schema exists), but the phrase 'real-estate listings' combined with known parameters like price and city gives reasonable expectations. A brief mention of returned fields would make it more 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 description coverage is 100%, with all four parameters (city_id, deal_type, max_items, max_pages) already documented in detail. The description only mentions 'by city' and currency, which partially overlaps with the schema but adds no new parameter-specific meaning beyond what the schema provides.

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's function with a specific verb ('Pull'), the exact resource ('SS.ge'), and geographic scope ('Georgia's biggest real-estate classifieds portal'). It distinguishes itself from siblings by naming the unique site and location, making it unmistakable which tool to use for Georgian listings.

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 clear context: it pulls live listings by city with seller-set currency, and explicitly notes 'No login, no browser, no proxies.' While it doesn't name alternative tools for other countries, the strong SS.ge branding makes the intended use obvious, though an explicit 'use for Georgia' comparison would improve it.

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 destructiveHint=false, so the safe read-only nature is known. The description adds value beyond annotations by stating 'No login, no browser, no proxies' (indicating direct API access without auth or scraping overhead) and the pricing model ($0.02/call, x402 on USDC base), which are not disclosed elsewhere. 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, front-loaded with a clear purpose and resource, followed by essential trait highlights (no login/browser/proxies) and pricing. Every sentence serves a purpose, with no redundant filler or repetition of required fields.

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 filtered-list tool without an output schema, the description covers the core function, filters, and a key behavioral trait (no auth needed). It doesn't describe the return format or pagination behavior, but the schema hints at pagination via max_pages. The lack of explicit response fields is a minor gap, but the tool's purpose is sufficiently clear for an agent to select and invoke it correctly.

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 baseline is 3. The description mentions filtering by deal type, property type, and city, which aligns with the schema, but it doesn't add any syntax, format, or additional meaning beyond what the parameter descriptions already provide. The schema's enum and title fields offer sufficient 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 states the verb 'Pull' and the resource 'Storia.ro', specifying the scope as 'apartment and house listings' filtered by deal type, property type, and city. It differentiates this tool from sibling real-estate listing tools by explicitly naming Romania's biggest real-estate portal, making it distinct from alternatives like otodom-warsaw or rightmove-london.

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 clear context: this is for pulling Romanian apartment/house listings from Storia.ro, and notes 'No login, no browser, no proxies', suggesting ease of use. It doesn't explicitly exclude alternatives or provide when-not-to-use guidance, but the regional and portal specificity strongly implies appropriate use cases for Romania-focused queries.

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 destructiveHint false. The description adds useful behavior context: it requires no login, no browser, and no proxies, and discloses the cost per call. This goes beyond the annotations without contradicting them.

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 just two sentences, front-loaded with the core purpose and followed by essential behavioral and cost details. Every sentence adds value, and there is no redundant or filler content.

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 tool has no output schema, so the description should convey what the returned data looks like. It mentions 'live apartment listings' but does not describe the fields or structure of each listing. For an agent selecting and using the tool, this is a notable gap, making the description only partially 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 description coverage is 100%, with each parameter already documented. The description only reinforces the category parameter by mentioning 'by real-estate category', adding no additional syntax or behavior details. Baseline 3 is appropriate when the schema handles parameter 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 clearly states the tool pulls live apartment listings from Tap.az, a specific resource, and mentions the real-estate category scope. It distinguishes itself from sibling tools by naming Tap.az and the Azerbaijan marketplace context, making the tool's purpose immediately 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?

The description includes 'No login, no browser, no proxies', implying easy access without authentication, and identifies the target marketplace. However, it does not explicitly state when not to use this tool or name alternatives among the sibling tools, so it lacks explicit 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 annotations, the description discloses stateful behavior (baseline creation on first run) and pricing ($0.05/call, USDC on base). Annotations are generic, so the description adds valuable context about side effects and cost. 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 two sentences plus a pricing note, front-loaded with the core functionality, followed by baseline behavior and cost. Every word earns its place, with no redundancy or fluff.

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 stateful, paid alert tool with 5 parameters and no output schema, the description covers the essential behavior (change detection), baseline mechanics, and pricing. It could mention return format or explicitly direct to alternatives, but the schema and annotations fill most gaps, making it reasonably 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 description coverage is 100%, so the baseline is 3. The description itself does not add parameter-specific details beyond the schema; it refers to a 'saved filter' but the schema already thoroughly explains queries, baseline_key, and limits. No extra semantic value is provided.

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 watches public tender feeds and returns only what changed since the previous check, listing specific change types (new, closed, changed deadlines). This is a specific verb-resource pair and distinguishes it from sibling search tools like gov-tender-radar.

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 makes clear this is for change monitoring rather than one-time searches ("only what changed since the previous check"), and mentions the baseline creation. However, it does not explicitly name alternatives or state when NOT to use it, so it lacks explicit exclusion 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?

The description and annotations consistently indicate a read-only, non-destructive operation (readOnlyHint: true, destructiveHint: false). The description adds value by detailing what data is retrieved (form, filing date, etc.) and emphasizing official, free, no-login-needed access, which aligns with openWorldHint.

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, using bullet-point-like dashes to front-load key features. Every word serves a purpose, from the core function to pricing and data source, without any fluff.

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 the moderate number of parameters and absence of an output schema, the description adequately covers the tool's function and parameters. It could be slightly more complete by noting that results are returned as a list of filings per manager, but this is a minor gap given the straightforward use case.

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 input schema covers all parameters with descriptions (100% coverage). The description adds context on how names are resolved and clarifies CIK vs. name usage, which enhances understanding beyond the schema. A perfect score is not given as the description could further detail the structure of the returned filings.

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 tracks institutional managers by SEC CIK or name and retrieves 13F filings. It uses specific verbs like 'track' and 'get' with a well-defined resource (13F-HR filings), effectively distinguishing it from sibling tools like 'insider-trading-tracker' or 'sec-edgar-watcher'.

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 implicitly distinguishes this tool from others (e.g., 'insider-trading-tracker') by focusing on 13F filings. However, it lacks explicit guidance on when not to use it or specific alternatives for different SEC data needs, providing only clear context for its intended 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 already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the description doesn't need to repeat that. It adds valuable context: cost per call ('$0.01/call, x402') and a disclaimer ('Not financial advice'). However, it could disclose rate limits or error handling for invalid addresses/tickers.

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 (3 sentences) and front-loads the core action and outputs. Every sentence adds value: outputs, source, prerequisites, cost, and disclaimer. Minor critique: the cost line could be integrated more naturally with the first sentence.

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 the absence of an output schema, the description compensates by listing key return fields (liquidity, 24h volume, pair age, quality score, risk flags). It also covers prerequisites and cost. However, for a tool with 100 max items and 4 parameters, additional context on pagination or output format limits would enrich completeness.

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 fully documents all four parameters. The description does not add new parameter-level semantics beyond listing outputs. Per guidelines, baseline 3 is appropriate since the schema covers everything, but the description could enhance usage examples (e.g., mixing addresses and tickers in one call).

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 specific verbs ('Look up', 'get liquidity, 24h volume...') paired with a clear resource ('token contract address or ticker across DEXes'). It also lists concrete outputs that distinguish it from sibling tools (e.g., rug-pull-scorer, live-price-oracle) by focusing on liquidity, volume, pair age, quality score, and risk flags.

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 context by stating the data source ('Powered by DexScreener's public API') and indicates constraints ('No key, no wallet, no on-chain node'). It does not explicitly mention when not to use it or name alternative sibling tools (e.g., for on-chain analysis), which would elevate the score to 5.

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 indicate readOnlyHint false, openWorldHint true, idempotentHint false, and destructiveHint false. The description adds that each call costs $0.05 and that it performs incremental delta detection, which are not encoded in annotations. It does not mention rate limits or per-run billing caps, but those are detailed in the input schema descriptions, and the annotation context lowers the bar.

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, focused sentence followed by a pricing tag. It front-loads the core purpose and avoids any filler or redundant information.

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?

Despite the tool's complexity (stateful watch, billing, rate limits, 9 parameters), the description covers the essential use case and cost. Critical caveats like first-run baseline, stateKey usage, and partial coverage are only in the schema descriptions, but the schema is extremely rich and available to the agent. No output schema exists, but the description clearly states the output is 'only the new ones', which is adequate.

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 baseline is 3. The description itself does not elaborate on any parameters, but the schema for each of the 9 fields is very detailed (e.g., prefix matching for CPV codes, best-effort region matching, stateKey purpose). No compensation needed from the 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?

Description uses specific verb 'Watch' plus resource 'UK Find a Tender' and clearly states the tool filters for 'public-sector tenders newly matching your keywords, CPV codes, value threshold or region'. It also distinguishes its delta behavior ('only the new ones since your last check') from simpler one-shot search tools, making it distinct from sibling tools like 'tender-alert' or 'gov-tender-radar'.

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 repeated monitoring usage with 'Watch' and 'since your last check', and its UK-specific scope clearly separates it from broader tender tools. However, it does not explicitly name alternatives or state when not to use it, relying on the reader to infer that other tools cover different regions or use cases.

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), openWorldHint=true (external data), and destructiveHint=false (no side effects). The description adds significant beyond-annotation value: it explicitly discloses the BYOK Etherscan model ('your key, your quota'), the $0.01/call x402 pricing on Base, and the heuristic nature of the score. This is rich behavioral context that annotations alone don't cover.

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 tight three sentences, each earning its place: the first explains the core function and scoring, the second explains the key BYOK model and caveats, the third summarizes pricing and payment method. No filler, perfectly front-loaded.

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 4 parameters, 100% schema coverage, readOnlyHint annotations, and no output schema, the description adequately explains the tool's function, constraints, and pricing. It's complete for a wallet profiling tool. Minor omission: doesn't specify if multiple wallets yield individual scores or an aggregate, but the schema's array type suggests individual. Still highly functional.

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 baseline is 3. The description adds value by explaining the BYOK trade-off: 'Leave empty to use a free keyless Blockscout explorer' vs providing your own key for higher rate limits. It also clarifies concurrency is 'kept low to respect your Etherscan rate limit'. This contextualizes the parameter purpose beyond the schema's technical definitions.

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 profiles a wallet on-chain using specific metrics (age, tx activity, contract & token diversity) and outputs a 0-100 airdrop-farming readiness score. This distinguishes it from sibling tools like 'rug-pull-scorer' or 'whale-wallet-tracker' which have different purposes.

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 includes a clear caveat 'Not a guarantee of eligibility for any specific airdrop -- a heuristic signal only' which sets expectations appropriately. However, it doesn't explicitly state when NOT to use this tool vs alternatives like 'rug-pull-scorer'. The BYOK model and pricing are mentioned but not compared to sibling tools.

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 convey readOnlyHint=true and destructiveHint=false. The description adds useful behavioral context: the call cost ($0.01/call), payment method (x402 on Base), and a warning about rate limits ('Keep this low on Etherscan's free tier to avoid rate-limit errors'). It does not contradict annotations. It could further disclose error handling or rate-limit behavior, but the added value is substantial.

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 paragraph of four sentences with no redundant words. It front-loads the core purpose and then efficiently covers output format, prerequisites, and cost. Every sentence adds value, making it concise without losing clarity.

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 explains what the tool returns: current balance, flagged transfers, and recent token transfers, one row per wallet. It also mentions the payment model and intended usage context. However, it lacks details on the exact format of the output (e.g., whether balances are numerical or structured) and does not address edge cases like empty results or API errors. Slightly more detail would make it fully 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 description coverage is 100%, so baseline is 3. The description adds meaning beyond the schema by explaining the purpose of 'minValueEth' ('Flag native transactions moving at least this much ETH') and giving usage guidance for 'maxConcurrency' ('Keep this low on Etherscan's free tier'). It also contextualizes the 'etherscanApiKey' parameter with 'bring your own key' vs keyless Blockscout. This elevates the 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 uses a specific verb ('Track') and clearly defines the resource ('large native ETH and ERC-20 token movements for any wallet(s)'). It distinguishes itself from siblings by listing what it does not require ('No RPC node, no wallet-connect, no browser') and mentions the API source (Etherscan multichain API). This makes the tool's purpose unambiguous and distinct among blockchain-related sibling tools.

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 states when to use the tool ('Track large native ETH and ERC-20 token movements') and the output format ('one row per wallet'). It implies the user needs an Etherscan API key or can use a keyless explorer. However, it does not explicitly contrast with sibling tools like 'wallet-airdrop-profile' or 'insider-trading-tracker', nor does it state when not to use this tool. The context is clear but lacking explicit 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 mark this read-only, and the description adds that it requires 'No login, no browser, no proxies' and costs '$0.02/call', which are operational behaviors not captured by annotations. However, it does not mention rate limits or error conditions.

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?

Single sentence with no filler. It front-loads the action and includes only additional operational facts (no login, no browser, cost).

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 query tool with no output schema, the description explains the input and the high-level output (listings) but doesn't specify the exact fields returned. Given the well-documented input schema, this is adequately complete, though it could mention output structure.

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 input schema has detailed descriptions for all four parameters (100% coverage), so the description adds little beyond mentioning 'rental and sale' which maps to deal_type and 'Vienna' to city. The baseline of 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?

Description uses specific verb 'Pull' to state it retrieves live apartment rental and sale listings from Willhaben.at for Vienna. It identifies the source portal (Willhaben.at) and city (Vienna), distinguishing it from other real estate listing tools.

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?

Description clearly scopes usage to Vienna real estate on Willhaben, but it does not mention when not to use it or name alternative tools. It gives context such as 'for Vienna' and 'Austria's biggest classifieds portal', but there are no explicit 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?

Annotation already sets readOnlyHint=true and destructiveHint=false, but the description adds valuable behavioral detail: the high churn rate of withdrawn jobs (HTTP 410), automatic compensation attempts, the fact that fetching full descriptions costs no extra request, and the lack of server-side keyword search. This goes well beyond 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 two sentences, front-loaded with the primary purpose and output fields, then adds behavioral context. The cost note ('$0.02/call, x402 (USDC on base)') is tangential to tool selection and invocation, preventing a perfect 5.

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 tool with 5 optional parameters and no output schema, the description covers the core behavior, source, output fields, and important caveats (410 churn, compensation, no server-side search). It lacks a precise return-structure description, which would be needed with no output schema, so it is not a 5.

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% with rich explanations for all 5 parameters (e.g., max_items explains the 410 churn, keyword_filter explains client-side filtering). The tool description itself adds no parameter-level detail beyond what the schema already provides, so the 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?

The description states a specific verb ('Walk xing.com's own job sitemap and pull...') with a clear resource (public job listings from DACH) and lists the output fields. It inherently differentiates from sibling job scrapers by naming XING and the DACH region.

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 clear context: it scrapes XING's public sitemap for DACH jobs and explicitly notes that XING's own job search is not used (requires a browser session). However, it does not explicitly name alternative tools or provide when-not-to-use guidance, so it falls just short of a 5.

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