Market and Regulatory Data Feeds — Zinin M2M Hub

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

With no annotations, the description partially covers behavior: it explains the sitemap walking, potential closed jobs, approximate freshness, and client-side filtering. However, it lacks details on rate limits, authentication needs, or whether the tool is read-only.

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 (two sentences) and includes essential information like data sources and output format. However, it could be more structured with bullet points for clarity, but overall no superfluous 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 description explains the output fields but omits details on the 'full_description' field controlled by a parameter. No output schema exists, so the description should cover all possible output fields. Missing information on error behavior or edge cases.

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 baseline is 3. The description does not add significant meaning beyond the schema descriptions; it only provides high-level context. Parameter details are already well-documented in 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 it scrapes job postings from boss.az using sitemap and structured markup, and lists output fields. However, it does not differentiate from sibling tools like 'tap-az-baku' or 'krisha-kz', so it lacks explicit distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives. The pricing is mentioned, but there is no advice on scenarios, limitations, or comparison with sibling tools. Users must infer usage from the name alone.

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

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

No annotations are provided, so the description carries the burden. It discloses useful traits: 'public JSON API', 'No login, no browser, no proxies', and cost ($0.02/call). However, it does not mention rate limits, pagination, response format, or data freshness limitations, leaving gaps in behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, compact sentence that front-loads the core action ('Pull live classified ad listings') and includes essential caveats like 'No login, no browser, no proxies' and cost as a concise aside. No redundant words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 2-parameter tool with no output schema, the description covers the primary context: what data is returned, source (Chotot API), and constraints (region/category, no login). It lacks mention of return structure or limits, but given the tool's simplicity, it is 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?

The input schema already provides comprehensive descriptions for both parameters (items and maxConcurrency) with examples and defaults, covering 100% of parameter semantics. The tool description adds minimal extra value by mentioning 'by region and category' but does not go 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 'pulls live classified ad listings' from Chotot's public JSON API, with specific verb, resource, and scope ('by region and category'). It distinguishes itself from sibling tools that target other platforms or data sources.

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 by specifying 'by region and category' and noting 'No login, no browser, no proxies', but it does not explicitly compare to alternative tools or state when to use or not use this tool. The use case is clear but not contrasted with siblings.

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

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

No annotations, so description carries full burden. It discloses cost ($0.02/call, x402/USDC), lack of API key/login, official source, and output behavior (sorted by recency). Does not mention rate limits or explicit read-only nature, but 'watch' implies read.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no fluff. Front-loaded with the key purpose, then output details, then cost/source. Every clause adds value.

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 lists the main return fields (NCT id, status, phase, sponsor, URL) and sorting behavior. It also provides provenance and cost context. Minor gaps like no-match behavior or error cases, but overall sufficient for a monitoring 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 descriptions for all 4 parameters. The description adds minimal param nuance beyond the schema (e.g., 'conditions, drugs or sponsors' maps to queries), 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?

Clear verb 'watch' with resource (clinical trials) and scope (conditions, drugs, sponsors). Lists specific output fields (NCT id, status, phase, sponsor, URL), distinguishing it from sibling monitoring 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?

Implies usage through 'Watch conditions, drugs or sponsors for new and updated clinical trials' and mentions official ClinicalTrials.gov API. But does not explicitly state when to use this over siblings (e.g., fda-approval-feed) or provide 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?

No annotations are provided, so the description carries the full burden. It does add useful context: the tool accesses 'public' listings (implying no auth) and discloses a $0.02/call cost with payment method. However, it does not mention pagination, rate limits, data freshness, or error behavior, leaving significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that front-loads the action and scope, followed by a compact pricing note. Every word earns its place with no redundancy.

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, no output schema, and no annotations, the description adequately covers the return fields and geographic scope. It omits potential details like result limits and pagination, but for a straightforward search tool, the provided information is 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% for both parameters, as the schema already explains the 'cc:query' format and maxConcurrency defaults. The description adds no extra semantic meaning beyond what the schema provides, so the baseline 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 states the action ('Search'), the resource ('Computrabajo'), the geographic scope (Mexico, Colombia, Chile, Argentina, Peru), and the output fields (title, company, location, URL, posted-when). This specificity distinguishes it from sibling job tools 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 provides no guidance on when to use this tool versus the many sibling job search tools. There are no alternatives mentioned, no exclusions, and no context about the ideal use case.

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

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

No annotations are present, so the description must carry the behavioral burden. It discloses the read-only search behavior, output format, and cost per call, but it does not mention rate limits, pagination consequences, auth requirements, or failure behavior. It is not misleading, but gaps remain.

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 front-loads the action and enumerates return fields, followed by a concise billing note. There is no repetition, filler, or unnecessary information relative to its length.

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 strong schema coverage and the absence of an output schema, the description adequately states what is searched, what is returned, and cost. It does not discuss empty-result handling or errors, but for a simple search tool this is largely covered by the parameter schema and clear return-field list.

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 already provides 100% coverage with detailed descriptions for all three parameters (query, max_items, max_pages). The main description adds no parameter-specific meaning beyond the keyword concept, 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 uses a specific verb and resource ('Search Detik news by keyword') and explicitly lists the returned data fields (headlines, excerpts, timestamps, sections, images, canonical URLs), making the tool's purpose unambiguous and distinguishing it from the sibling domain-specific search 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 context is clear for searching Indonesian news on Detik, but there is no explicit guidance on when to choose this tool over alternatives or when not to use it. Usage is implied rather than stated.

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

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

With no annotations provided, the description should disclose behavioral traits like side effects, rate limits, or safety. It only mentions 'live' listings and cost, lacking details on what happens with API limits or whether it modifies any state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words. Front-loaded with purpose, then cost/pricing info. Efficient and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, and the description does not mention return format or pagination behavior. However, for a simple listing pull tool with well-documented parameters, it is minimally adequate but could be improved with output details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds no extra parameter context beyond what is already in the schema (e.g., deal_type and property_type are clear from schema). The cost info is not parameter-specific.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it pulls live apartment/housing listings from Emlakjet.com for Istanbul, specifying deal type and property type. It distinguishes from sibling tools which cover different domains like jobs or tenders.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions no login/browser/proxies and cost, but does not explicitly state when to use this tool vs alternatives or when not to use it. Usage context is implied but not fully 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?

No annotations are provided, so the description carries the burden. It discloses that the tool uses official openFDA data, requires no API key or login, charges a per-call fee, and provides specific output details (application status, sponsor, latest submission, recall details). It also implies read-only monitoring via the verb 'watch.' This adds substantial behavioral context beyond the schema.

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 concise sentences with a pricing footnote. It front-loads the primary purpose, then provides key behavioral details, and ends with cost. Every sentence earns its place with no fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description covers the essential context: purpose, data source, authentication needs, cost, and the type of data returned. It does not explain update frequency or output formatting, but the schema fully covers parameters. For a monitoring tool, this is 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 coverage is 100%, so the baseline is 3. The description adds minimal parameter-specific meaning beyond what the schema already provides. It mentions 'drugs or companies' which aligns with the 'queries' parameter, but does not clarify limits, datasets, or concurrency beyond schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Watch drugs or companies for new FDA approvals and recalls.' This clearly states what the tool does and distinguishes it from sibling tools like clinical-trials-monitor or job alerts. The scope is 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 a clear use case: monitoring drugs or companies for FDA approvals/recalls. It does not explicitly name alternatives or exclusions, but the context is evident, and no sibling tool offers overlapping FDA functionality. It provides enough guidance for an agent to know when to invoke 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?

With no annotations, the description carries the transparency burden. It discloses the return fields (title, buyer, country, CPV codes, deadline, URL), access constraints (no API key/browser, public TED API only), and cost ($0.02/call). It does not mention rate limits or error behavior, but for a read-only search tool this is adequate.

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 concise sentences plus a cost note, front-loaded with the core action and immediately followed by return format and constraints. Every sentence delivers value, zero 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?

Despite no output schema and no annotations, the description covers the essential context: what it searches, what it returns, access method, and cost. It lacks details on pagination or error handling, but for a straightforward search tool with well-documented schema parameters, this is 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 coverage is 100% and each parameter already has detailed descriptions (queries explains expert-query expressions, country explains ISO code, limit/concurrency explain bounds). The description only restates high-level capabilities (keyword/CPV, country filter) without adding new semantic detail, 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 searches EU public-sector tenders on TED Europa by keyword or CPV code, with optional country filtering. It specific verb 'Search' and resource 'EU public-sector tenders (TED Europa)' and distinguishes from sibling tools like tender-alert by its EU/TED scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on scope (EU public-sector tenders), access method (public TED search API), and constraints (no API key, no browser). However, it does not explicitly name alternatives or exclusions, so it stops short of full guidance on when to use vs. not 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?

No annotations are provided, so the description must fully convey behavior. It mentions 'no login, no browser, no proxies' and pricing, but fails to disclose whether the tool is read-only, any rate limits, or what the output contains. This is insufficient for a tool that retrieves data.

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 followed by a pricing tagline. It is concise and front-loaded with the core purpose. Every sentence adds value (purpose, no-proxy, cost). However, it could be slightly more structured, e.g., listing filters explicitly.

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 5 parameters and no output schema, the description should explain what is returned (e.g., listing details, pagination behavior). It does not. The pricing and 'no login' notes are helpful, but the lack of return value description leaves the agent uninformed about what data to expect.

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 five parameters have descriptions in the input schema, achieving 100% schema coverage. The tool description text does not add any additional 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 clearly states it pulls live apartment and house listings from Imovirtual.com, a specific real-estate portal. The verb 'pull' combined with 'listings' and the platform name makes the tool's purpose unambiguous. It also distinguishes from sibling tools by specifying the portal and location.

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 Imovirtual listings with filters by deal type, property type, and city. However, it does not explicitly state when to use this tool versus alternatives (e.g., other real estate tools for different countries). No when-not or exclusion criteria 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?

With no annotations provided, the description carries the full burden. It discloses the data source ('Official SEC EDGAR data'), authentication requirements ('no API key or login'), pricing ('$0.01/call'), and output components ('filing counts, an at-a-glance activity signal ... and direct document links'). This is solid transparency, though it does not mention rate limits or error 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 tightly written sentences that front-load the purpose, then list key outputs and cost. Every phrase earns its place: data source, authentication, output summary, and pricing. No filler or duplication of schema details.

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 explains what the tool returns: filing counts, an activity signal, and document links. It also covers the data source and cost. Slight gaps exist around processing details or edge cases, but the essential information for selecting and using the tool is present.

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 three parameters are fully described in the schema (100% coverage), so the baseline is 3. The description does not add param-specific details beyond what the schema already provides; it only repeats 'list of tickers' and mentions 'per company' which aligns with the schema's 'One row per ticker'.

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: 'Track insider stock trades — SEC Form 3/4/5 filings — for any list of tickers.' This names the specific resource (insider trading filings) and the scope (any tickers), distinguishing it from broader SEC-sibling tools like 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 provides clear context for when to use it (checking insider trading activity for given tickers) and the input type ('for any list of tickers'). It does not explicitly name alternatives or exclusions, but the specificity of Form 3/4/5 implies the intended use case.

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

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

With no annotations, the description covers key behavior (incremental returns, first-run baseline) and pricing, but omits details like state persistence, error handling, or auth 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?

Two concise sentences plus pricing info, no filler, directly communicates the core 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?

Covers core functionality but lacks output format details, lifecycle management (e.g., how to stop a watch), and error states. Adequate for a simple tool but not complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions already cover all parameters well; the tool description adds only minor context about baseline creation and pricing, not adding significant meaning beyond 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 watches a job board with a saved filter and returns only new postings since last check, distinctly different from sibling tools like job-postings-aggregator that do not do incremental watching.

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 job boards incrementally and mentions pricing, but does not explicitly advise when to use this vs. alternatives or mention 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?

With no annotations, the description carries the full burden. It discloses that the tool uses public ATS data without scraping or login, and includes pricing per call. However, it doesn't discuss potential rate limits, error handling, or what happens when a company has no postings. This is moderate behavioral disclosure beyond the basic operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero waste. The description is front-loaded with the core function, followed by constraints and pricing. Every part adds value, making it highly concise and 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?

For a fairly simple list tool with a rich schema, the description is quite complete. It explains the output format (one row per posting with specified fields), the supported ATS providers, and the cost. It lacks information on edge cases like empty results or error handling, but this is a minor gap given the tool's simplicity.

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 parameters (items and maxConcurrency) are already fully documented in the schema. The description adds the output fields (title, location, department, URL, posted date) but doesn't add meaning to the parameters themselves. Baseline of 3 is appropriate since the schema does the heavy lifting.

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: pulling every open role from a company's ATS (Greenhouse, Lever, Ashby) and normalizing into rows. The verb 'Pull' is specific and the resource is well-defined. It doesn't explicitly differentiate from sibling tools like 'job-alert' or 'xing-jobs', but the ATS-specific aggregation is distinctive enough.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs. alternatives. The description implies usage for fetching job postings from supported ATS platforms, but doesn't mention exclusions or when another tool might be more appropriate. The 'No login, no scraping, no proxies' note hints at a method constraint but doesn't serve as clear usage 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?

No annotations are provided, so the description should disclose behavioral traits. It mentions the cost and the effect of 'fetch_full_description' on speed, but does not cover rate limits, authentication needs, or error behavior. This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that front-loads the action and key output fields, followed by a pricing note. Every part adds value with no redundancy.

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 5 parameters, 100% schema coverage, and no output schema, the description lists the output fields effectively. It does not explain pagination or error handling, but the parameters cover most configuration needs. The description is sufficiently complete for a straightforward 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 baseline is 3. The description adds context by stating the tool searches by keyword and lists returned fields, which helps understand the purpose of parameters. It also clarifies the optional location and the speed impact of fetch_full_description, adding marginal value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches jobs.ch in Switzerland by keyword and returns specific fields (title, company, etc.). It distinguishes from sibling tools by specifying the geographic scope, which is unique among the job scrapers.

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 use for Swiss job listings via the mention of 'jobs.ch (Switzerland)'. It does not explicitly state when not to use or name alternatives, but the context of sibling tools makes the intended use clear.

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

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

With no annotations, the description carries the burden. It mentions cost and simplicity but lacks disclosure on rate limits, data freshness, error handling, or pagination behavior beyond schema parameters.

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 very concise (one sentence plus cost note). However, it is a single run-on sentence; breaking it into separate statements would improve structure slightly.

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 purpose and basic usage with an example in the schema prefill. For a multi-query scraping tool, additional details on output format or behavior would be helpful but not critically missing.

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 parameters have schema descriptions (100% coverage). The tool description adds useful context by explaining the query format 'deal:type:city' and the overall purpose, enhancing understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pulls live apartment and house listings from Krisha.kz, specifying the dimensions (deal type, property type, city). It distinguishes from siblings by focusing on Kazakhstan real estate.

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 ease of use with 'No login, no browser, no proxies' but does not explicitly state when to use this tool versus alternatives or 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?

With no annotations, the description carries the full burden. It discloses key behavioral traits: 'Keyless, no wallet, no RPC node' indicates no authentication setup, and 'DexScreener's public API' reveals the external dependency. It also states the cost and payment method ($0.01/call via x402), providing operational transparency. It doesn't cover failure modes or rate limits, but the core behavioral context is well addressed.

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, information-dense sentence that front-loads the primary purpose. Every clause earns its place: what it does, what it returns, key characteristics, and cost. No filler or redundancy.

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 adequately covers return values by listing the data fields. It explains the use case, external API, and cost model, providing enough context for an agent to decide to call it. It omits error handling or invalid-token behavior, but for a simple lookup tool the context is 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?

Schema description coverage is 100%, so the baseline is 3. The description partially reinforces the 'tokens' parameter by mentioning 'contract address or ticker,' but it adds no new meaning to 'chainId' or 'maxConcurrency' beyond what the schema already says. The description focuses on outputs rather than parameter nuances.

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: 'Current USD price for any token by contract address or ticker.' It also lists the specific data points returned (24h change, liquidity, volume, best DEX pair), making the purpose distinct and concrete. The 'oracle' title and reference to DexScreener's public API further differentiate it from siblings.

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 on when to use this tool: 'Built to be called cheaply by AI agents that just need the number.' It explicitly notes it is keyless and requires no wallet or RPC node, implying it's ideal for lightweight price lookups. It doesn't name alternatives or exclusions, but the usage scenario is well-defined.

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

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

No annotations are provided, so the description must cover behavior. It mentions cost and that no login is needed, but lacks details on error handling, rate limits, or result format. The 'no proxies' claim is positive but incomplete for full transparency.

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 that cover purpose, source, parameters, and cost. Every word adds value, with no redundancy.

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 does not explain the return format or default behavior. With no output schema, this leaves gaps for an agent. Parameter descriptions are good, but overall completeness is average.

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 clear description. The tool description summarizes the parameter categories but adds no new meaning beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pulls live listings from Otodom.pl by deal type, property type, and city. It uses a specific verb 'Pull' and identifies the resource, distinguishing it from sibling tools targeting other regions.

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 real estate searches in Poland but does not explicitly state when to use this tool versus alternatives like 'rightmove-london' or 'emlakjet-istanbul'. No when-not-to-use or alternative guidance is 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?

With no annotations provided, the description carries the burden of disclosing behavior. It notes 'Free' (cost-related), and the action 'list' implies read-only, with no side effects. It does not disclose pagination or response format, but for a simple zero-parameter list tool, this is adequate.

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 front-loads 'Free' and then states the action and context. Every word serves a purpose, with no wasted text.

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 (zero parameters, no output schema), the description fully covers what it does, what it returns, and when to call it. It is complete for an agent to select and 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?

The tool has zero parameters, so the baseline is 4. No parameter documentation is needed, and the description adds relevant context about the output instead.

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 ('list') and clearly identifies the resource ('every paid tool in the 'market-data' bundle') along with the exact information returned (price, payTo address, network). This clearly distinguishes it from sibling tools, which are mostly job or real estate 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?

It provides an explicit usage context: 'Call this first if you don't have a wallet ready yet.' This is a clear when-to-use instruction, though it does not explicitly mention alternatives or 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?

With no annotations, the description must convey behavioral traits. It mentions 'no login, no browser, no proxies' and a cost per call, which are useful. However, it lacks details on rate limits, data freshness guarantees, error handling, or pagination behavior, leaving gaps for the agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, covering purpose, location, key parameters, unique selling points, and cost, with zero redundancy. Every word 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?

The description covers the core functionality but omits output schema details and does not address typical agent concerns like what fields are returned or error handling. With 5 parameters and moderate complexity, it is adequate but not 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 coverage is 100% with good per-parameter descriptions. The description adds contextual value by summarizing key parameters (deal type and emirate) and noting sort order, but does not significantly enhance understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pulls live listings from PropertyFinder.ae, specifying the resource (UAE real-estate portal), verb (Pull), and key parameters (by deal type and emirate, sorted freshest-first). It effectively distinguishes from sibling tools by targeting a specific geographic and functional niche.

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 property listings but provides no explicit guidance on when to use this tool versus its many siblings (e.g., rightmove-london for UK, otodom-warsaw for Poland). There is no mention of when not to use it or alternatives.

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

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

No annotations are provided, so the description carries the full burden. It describes the tool as 'pull live listings', which strongly suggests a read-only operation with no side effects. However, it does not explicitly confirm read-only behavior, rate limits, or other potential impacts. The pricing note is helpful but not behavioral.

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, using three sentences to convey purpose, ease of use, and pricing. Each sentence adds relevant information without redundancy. The structure is clear, though a bit dense; still well within acceptable limits.

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 5 parameters, no output schema, and no annotations, the description provides a solid overview. It explains the region coverage, deal type nuance, and that it returns live listings. It does not detail the output format or pagination behavior, but the schema covers pagination parameters. Overall, sufficient 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 description coverage is 100%, so baseline is 3. The description adds significant value by explaining the 'deal_type' enum values (prodaja vs najam) and mapping 'najam' to Realitica's 'Duži Najam' category, which clarifies a potential ambiguity. It also provides region path examples beyond the schema's description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pulls live apartment and house listings from Realitica.com, covering specific regions (Montenegro, Croatia, Serbia) and filterable by deal type, property type, and region. The verb 'pull' and resource 'listings' are specific, and the unique regional focus distinguishes it from sibling tools like 'otodom-warsaw' or 'imovirtual-lisbon'.

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 Realitica.com listings in the Adriatic region, contrasting with sibling tools targeting other geographic markets. It mentions 'no login, no browser, no proxies' indicating ease of use. However, it does not explicitly state when not to use it or suggest alternatives for other regions.

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?

Without annotations, the description carries full burden. It discloses key behaviors: first run creates baseline, returns only new listings, and pricing. Missing details like error handling or data retention, but overall transparent for a simple tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences plus pricing line. Core function first, then nuance, then cost. Every sentence serves a purpose. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description does not specify return format or structure. It mentions 'listings' but not what fields or how pagination works. Adequate for a simple tool but not comprehensive.

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 baseline is 3. The tool description adds context about baseline creation and first-run behavior, but the parameter descriptions in schema already provide detailed semantics. No significant extra value.

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 with a saved filter and returns only new listings since last check. This distinguishes it from sibling tools that are one-time scrapers or other alert 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 implicitly tells when to use (incremental monitoring vs full scrape) by explaining the incremental behavior and pricing. However, it does not explicitly contrast with sibling portal-specific actors or provide when-not-to-use scenarios.

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?

Discloses 'No login, no browser, no proxies' and 'live' data, which are useful behavioral traits. However, does not explain rate limits, error handling, data freshness beyond 'live', or output behavior. Since annotations are absent, more detail would be beneficial.

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?

Description is a short, front-loaded paragraph with no wasted words. Includes key action, source, and pricing. Could be slightly more structured, but highly efficient.

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 listing tool with no output schema, the description covers purpose and parameter usage adequately but does not describe output format or pagination details. Agent may need to infer return structure from context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline 3. Description adds value for location_identifier by explaining how to obtain the code from Rightmove's URL. Other parameters are already well-documented in schema, so marginal additional meaning.

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 property listings from Rightmove.co.uk, specifies for-sale and to-rent, and mentions London or any Rightmove location code. It distinguishes from sibling tools by naming the source (Rightmove) and location flexibility.

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 indicates use for UK property listings from Rightmove, but lacks explicit when-to-use vs when-not guidance or alternative tool comparisons. Pricing info is included but not directly tied to usage decisions.

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

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

No annotations are provided, so the description carries the full burden. It discloses the heuristic nature ('Heuristic signal, not financial advice'), data sources, and infrastructure requirements ('No wallet, no RPC key, no browser'). However, it does not mention return format, error behavior, or rate limits, which would be expected for full transparency.

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 earning its place: purpose/data sources, detection capabilities, and practical caveats (heuristic, cost, no infra). It is front-loaded with the main verb and resource, making it immediately actionable and free of 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?

For a 3-parameter tool with no output schema and no annotations, the description covers purpose, data sources, detection scope, cost, and prerequisites. It lacks explicit return value details (e.g., score range) but conveys that it produces a risk score. The description is sufficiently complete for an agent to 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 does not add meaning beyond the schema; it mentions token types and detection categories but does not elaborate on specific parameters like chainId or maxConcurrency. The schema already describes these adequately.

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 'Score' with a clear resource: 'ERC-20/BEP-20 token rug-pull risk' and defines data sources (honeypot.is simulation + DexScreener). This distinguishes it from siblings like token-launch-radar or live-price-oracle by focusing on risk assessment rather than price monitoring or launch tracking.

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 on when to use the tool (for assessing rug-pull risk of tokens) and what it detects (honeypots, high taxes, thin liquidity, new pairs). It also mentions practical constraints ('No wallet, no RPC key, no browser') and cost, but does not explicitly name alternatives or exclusions 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?

No annotations are present, so the description carries the full burden. It discloses that data is official, free, requires no API key/login, and costs $0.01/call. However, it does not disclose read-only behavior, rate limits, error handling, or return format specifics beyond the key 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 two sentences, front-loaded with the core purpose. The second sentence packs filtering, output, and pricing details efficiently, though the em-dash cost addendum is a minor distraction. Overall it is concise and 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?

Given the tool's moderate complexity and lack of an output schema, the description adequately explains what the user gets (form, filing date, document URL) and notes the data source. It could be more explicit about the response shape, but it covers the essential expectations for a watcher 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 all four parameters are already self-documented. The description adds no extra meaning beyond restating that you can filter by form type and lookback window, which is already in the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with a specific verb and object: 'Watch stock tickers for new SEC filings' and enumerates common form types (10-K, 10-Q, 8-K, S-1). This clearly distinguishes it from siblings like insider-trading-tracker or fda-approval-feed by focusing on general SEC filings via EDGAR.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when you need SEC filings for tickers) but provides no explicit comparison to alternatives or exclusions. It mentions filtering capability but does not say when not to use it or which sibling to choose instead.

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

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

With no annotations, the description carries full disclosure burden. It usefully notes that no login, browser, or proxies are needed, and shows pricing ($0.02/call). However, it omits details on error handling, rate limits, or response structure, leaving gaps in behavioral expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short (two sentences) and front-loaded with the core action. However, it includes marketing elements (pricing and token ticker) that are not strictly functional, slightly reducing 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?

Given the tool has 4 parameters, no output schema, and no annotations, the description provides moderate completeness. It explains what data is retrieved but does not describe the output format or how results are structured, which an agent would need for processing. The cost info is helpful context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so each parameter already has a description. The tool description adds only the mention of currency handling, which is not a parameter itself. It does not further clarify city_id, deal_type, max_items, or max_pages beyond what the schema provides, so it meets the baseline but adds little extra value.

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 that the tool pulls live real-estate listings from SS.ge, Georgia's largest classifieds portal. It specifies the capability to retrieve by city and preserve the original currency (GEL or USD), making it unambiguous and distinct from sibling tools which target different markets.

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 does not mention any conditions, prerequisites, or exclusions, nor does it compare to sibling tools like emlakjet-istanbul or imovirtual-lisbon. The agent must infer context solely from the portal name.

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

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

No annotations are provided, so the description carries the full burden. It mentions positive traits (no login/browser/proxies) and pricing, but lacks details on rate limits, failure modes, or potential side effects. The description is moderately transparent but incomplete.

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 plus pricing info. The description is front-loaded with the main purpose and requires no editing. Every phrase earns its place, with zero waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description does not specify the format of returned listings (e.g., price, bedrooms). For a listing tool, this is a gap. However, the agent can infer from the portal's typical output. Adequate but not thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%; the description adds value by explaining the Romanian terms for deal types and property types (e.g., 'vanzare' meaning sale) and clarifying the city path format. This goes beyond the schema by providing contextual translations.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it pulls listings from Storia.ro, a specific real-estate portal, with parameters for deal type, property type, and city. It distinguishes itself from siblings (e.g., otodom-warsaw, rightmove-london) by naming the unique portal and region (Romania).

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 ease of use ('No login, no browser, no proxies') but does not explicitly contrast with sibling tools or specify when to use this tool over alternatives. The context is clear (Romania), but no when-not or exclusion guidance is 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?

No annotations are provided, so the description carries full burden. It discloses that the tool pulls live data, costs $0.02/call, and has a verified limitation (only 'menziller' category). It does not cover error behavior, rate limits, idempotency, or side effects, leaving partial transparency.

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 immediately conveys the purpose, key benefits, and cost. Every phrase is purposeful, with no wasted words. It is front-loaded with the main action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 3 parameters and no output schema. The description covers the core purpose, cost, and a critical verified-category limitation. It does not detail output format, but given the simplicity (scraping listings), the description is sufficient for an agent to understand usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds value by explaining the category parameter as a URL path segment and including a caveat about unverified categories. For other parameters, the schema descriptions are sufficient, so the description provides meaningful extra context 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 specifies a clear action ('pull live apartment listings'), a specific resource ('Tap.az — Azerbaijan's biggest classifieds marketplace'), and scope ('by real-estate category'). It distinguishes itself from sibling tools by targeting a unique marketplace and 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 states when to use the tool (to get Tap.az listings), notes ease of use (no login/browser/proxies), and mentions cost. However, it does not explicitly state when not to use or directly compare to alternatives, but the sibling tools cover different regions/domains, making differentiation clear.

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

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

With no annotations, description carries full burden. It discloses first-run baseline creation, pricing, and that output is only changes. However, it doesn't explain the saved filter concept (input uses queries directly), output format, or rate limits. The mention of 'saved filter' is slightly inconsistent with the input schema.

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?

Very concise: one paragraph, four sentences. Front-loaded with purpose, followed by key behaviors and pricing. No 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?

Given no output schema and no annotations, description should explain return format and baseline concept more thoroughly. It mentions 'returns only what changed' but not the structure. Also doesn't cover prerequisites like TED query syntax or account requirements. Moderate completeness for a complex monitoring 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 baseline is 3. The description adds pricing context and scoping for baseline_key, but each parameter already has a detailed description in the schema. Minimal added value beyond 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?

Description clearly states the tool watches public tender feeds for a saved filter and returns only changes (new, closed, deadline changes). This distinguishes it from siblings like gov-tender-radar (full search) and job-alert (jobs). The verb 'watches' and resource 'public tender feeds' are specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description implies usage for monitoring changes rather than full data, but lacks explicit when-not-to-use or direct alternatives. The pricing and first-run behavior provide context, but no comparison to sibling tools like gov-tender-radar.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It honestly reveals official SEC data source, cost ($0.01/call), and no login requirement. However, it does not mention rate limits, error behavior, or return structure beyond listing fields, leaving some gaps in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main action and is composed of two sentences. The trailing pricing and payment detail ($0.01/call, x402) is somewhat distracting but adds minimal length. Overall, it is compact with no redundant wording.

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 data-fetching tool with no output schema, the description lists key return fields (form, filing date, accession, EDGAR link) and the parameter schema handles usage details. Edge cases like unmatched names are partially addressed in the manager parameter. The low complexity makes this sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and every parameter (managers, sinceDays, maxConcurrency) has a detailed description within the schema. The tool description itself adds no extra meaning about the parameters; the schema already carries the load, 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 purpose: tracking institutional managers by CIK or name and retrieving their 13F filings. It specifies the output (form, filing date, accession number, EDGAR link) and distinguishes itself from broader tools like sec-edgar-watcher by focusing specifically on 13F-HR filings.

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?

Provides clear context for when to use (tracking hedge funds/family offices) and mentions no API key/login as a convenience factor. However, it does not explicitly contrast with sibling tools or state exclusions, leaving some ambiguity about alternative choices.

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

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

No annotations exist, so the description carries full burden. It discloses the data source (DexScreener's public API), no credentials needed, cost ($0.01/call), payment method (x402 USDC on base), and a 'Not financial advice' disclaimer. It also mentions concurrency and age filtering behavior in schema, though it doesn't detail error handling or exact response structure.

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 that front-loads the core function, followed by useful execution details (API, cost, payment, disclaimer). Every sentence contributes value, though the cost and payment details could be seen as meta but are likely necessary context. It is compact and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, but the description lists expected return metrics (liquidity, 24h volume, pair age, quality score, risk flags), which is sufficient for a lookup tool. It also explains the pricing model and access requirements. It does not describe the response envelope (e.g., whether output is a list per token), but the parameter descriptions partially address selection logic (e.g., 'best pair' in minLiquidityUsd).

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 for parameters is 100%, so the schema already explains each parameter (tokens, maxAgeHours, maxConcurrency, minLiquidityUsd). The description adds context on cost and purpose but does not enhance parameter meaning beyond what the schema provides. The baseline of 3 applies because the schema fully covers 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 uses a specific verb ('Look up') with clear resources ('token contract address or ticker across DEXes') and enumerates the output (liquidity, 24h volume, pair age, 0-100 quality score, risk flags). This clearly distinguishes it from siblings like rug-pull-scorer (focused on risk only) or live-price-oracle (price only).

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 use when needing token metrics across DEXes and mentions the ability to 'hunt fresh launches' via the maxAgeHours parameter. It clarifies there's no key/wallet/node, making setup easy, but does not explicitly name alternatives or exclusion criteria 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?

With no annotations, the description carries full burden. It discloses behavioral traits including cost ($0.01/call via x402), reliance on user's Etherscan key and quota, support for keyless Blockscout chains, and its heuristic nature. It clearly sets expectations about limitations and payment, going beyond basic operation.

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 and front-loaded with the core purpose, followed by important operational notes (BYOK, heuristic, cost). Each sentence earns its place, with no redundancy or filler. It fits in three sentences while covering purpose, limitations, and billing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description should explain return values. It states the final output (0-100 score) and implies profile details (age, tx activity, diversity) in the opening. It also covers chain support and cost. It does not explicitly enumerate the full response structure, but for a scoring tool this is 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?

Schema description coverage is 100%, and each parameter has a detailed description. The tool description adds no new parameter semantics beyond restating BYOK Etherscan and quota, which the schema already covers in the etherscanApiKey and maxConcurrency fields. 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 profiles a wallet on-chain and outputs a 0-100 airdrop-farming readiness score based on age, tx activity, and diversity. The verb 'Profile' and resource 'wallet on-chain' are specific, and it is distinct from all sibling tools which target jobs, real estate, or other domains.

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: it is a heuristic for airdrop farming readiness, and warns it is not a guarantee for specific airdrops. It also mentions BYOK Etherscan and billing, giving operational context. However, it does not explicitly name alternatives or state when not to use this tool, lacking exclusionary guidance for 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?

The description discloses that it uses Etherscan's multichain API with a user-provided key, has no RPC/wallet-connect/browser dependency, and charges $0.01 per call via x402. It also states the output includes balance, flagged transfers above the threshold, and recent token activity, providing good behavioral context given no annotations are provided.

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 dense sentence that front-loads the core purpose and then adds operational and cost details without fluff. Every clause provides meaningful 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 lack of output schema and annotations, the description explains what the tool returns (balance, flagged transfers, recent activity), the one-row-per-wallet structure, and the operational requirements (Etherscan API, payment, no RPC). This makes it sufficiently complete for a 5-parameter tool with rich schema descriptions.

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 already has a description. The tool description adds useful relationships by referencing 'flagged transfers above your ETH threshold' (minValueEth) and 'one row per wallet' (wallets array), and clarifying no external connection is needed (etherscanApiKey, chainId). This goes slightly beyond 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 states the tool tracks large native ETH and ERC-20 token movements for any wallet(s) via Etherscan's multichain API, and lists specific data returned (current balance, flagged transfers, recent token activity). This clearly distinguishes it from sibling tools like wallet-airdrop-profile or rug-pull-scorer.

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 on when to use it — for monitoring whale-like token movements without needing an RPC node or wallet connection — and mentions the external Etherscan API dependency and $0.01/call cost. It does not explicitly name alternative tools for exclusion, but the purpose is specific enough to guide selection.

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

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

With no annotations, the description carries full burden for behavioral disclosure. It mentions the action and pricing but omits important traits such as rate limits, idempotency, error modes, and that only 'wien' city is reliably supported. The schema covers parameter details, but behavior beyond that is missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core action. Every word earns its place. No redundant or verbose phrasing.

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 and no annotations, the description should cover what the tool returns and its behavior. It lacks any mention of output format, pagination behavior, or error handling, making it incomplete for an agent to fully understand the 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 baseline is 3. The main description adds minimal value beyond the schema; it mentions Vienna but does not provide syntax or context not already in the parameter 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?

Description explicitly states it pulls live apartment rental and sale listings from Willhaben.at for Vienna. This clearly identifies the resource and action, distinguishing it from siblings like rightmove-london or otodom-warsaw.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description mentions features like 'no login, no browser, no proxies' but does not specify prerequisites, limitations, or 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?

With no annotations, the description carries the full burden. It discloses pricing ($0.02/call), churn handling (HTTP 410 and compensation), and that keyword filtering is client-side. It does not mention rate limits or authentication, but the level of detail is above average for a scraping tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured paragraph that front-loads the key purpose and data fields. Including pricing and technical details adds some length, but each sentence serves a clear informative purpose without redundancy.

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?

Without an output schema, the description enumerates the return fields (title, company, location, etc.) and explains error behavior (HTTP 410 churn). It covers all essential aspects for an agent to understand what the tool returns and how it handles common issues.

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%, and the description adds significant value beyond the schema. For example, it explains why sitemap_override_url is advanced/diagnostic, that fetch_full_description costs no extra request, and how keyword_filter works (side effect: no server-side search).

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 action ('walk' and 'pull') and resource ('xing.com's own job sitemap'), and specifies the region (Germany/Austria/Switzerland) and data fields (title, company, etc.), distinguishing it from sibling tools focused on other job boards or regions.

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 the tool (for DACH job listings) and explains parameter behavior (e.g., keyword_filter is client-side only, freshness_days rarely filters). It does not explicitly state when not to use it or name alternatives, but the regional focus is evident among sibling tools.

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