Agent Newsstand

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 tool is a 'live-fetch' (implying real-time data retrieval) and focuses on economic release dates. However, it omits behavioral details like whether the tool is read-only, rate limits, or what happens if no releases are found. The description is adequate but not comprehensive.

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, front-loaded sentence that efficiently conveys the tool's core functionality and source. It is not verbose, and every part adds meaning, though it could be rephrased to include usage hints without increasing 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 tool has only 1 parameter, no required params, no output schema, and no nested objects, the complexity is low. The description sufficiently explains what the tool does (retrieve US economic release dates via FRED live-fetch). However, it lacks details on the output format (e.g., date range, fields returned) and does not specify that it only covers US data, which would be useful for completeness.

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

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

Schema description coverage is 0%, so the description must compensate. The 'limit' parameter (default 25) is implicitly about controlling how many upcoming dates to return, but the description does not explain what 'limit' means in the context of calendar entries (e.g., number of days or events). The description adds minimal value beyond the schema's default 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 retrieves 'Upcoming US economic release dates' from the 'FRED calendar' and does a 'live-fetch', providing specificity about the source and functionality. It effectively distinguishes from siblings like 'earnings' (corporate earnings) and 'macro' (broader macro data), but could be slightly improved by noting the data is US-specific in the purpose.

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

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

No guidance is provided on when to use this tool versus alternatives like 'macro' or 'candles'. It does not clarify limitations (e.g., only US economic releases) or scenarios where another tool would be more appropriate, leaving the agent to infer usage from the description 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 must disclose behavioral traits. It states 'Daily OHLCV candles' which implies read-only historical data without side effects. However, it does not clarify whether the data is live-delayed, if it requires authentication, or if there are any rate limits. Based on the context, a conservative 3 is appropriate as it covers the basic behavior but lacks depth.

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 line without filler, earning its place. However, it could be slightly more structured (e.g., specifying that it returns data for the last N days). It is front-loaded and concise but leaves some gaps that require expansion.

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 no output schema, a more complete description could explain the return format (e.g., array of OHLCV objects). It only describes input behavior. With no annotations, it is minimally adequate for a simple 2-parameter tool but lacks details that would help an agent interpret results or handle errors.

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

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

Schema description coverage is 0%, so the description must compensate for the two parameters but does not. It mentions 'daily' but doesn't connect to the 'days' parameter (e.g., how many days back). 'Symbol' is self-explanatory from the schema but the description adds no additional context. Since there are only 2 parameters and no compensated semantics, a baseline 3 is fair.

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

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

The description uses specific verbs ('OHLCV' implying open, high, low, close, volume) and a resource ('candles' for a venue symbol). It clearly states it provides daily data. However, it does not differentiate from sibling tools like 'history' which could also involve time-series data, so a 5 is not warranted.

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 retrieving OHLCV candle data for a symbol. However, it provides no guidance on when to use this tool versus alternatives like 'history' or 'calendar', nor does it specify any prerequisites or exclusions (e.g., date range limitations, symbol format). Only implied context from the sibling names is available.

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 disclose behavioral traits. It does not mention whether the tool is read-only, what data it returns, any side effects, permission requirements, or rate limits. This is a critical gap for a data retrieval 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 extremely short (7 words) but lacks necessary detail. It is not a model of conciseness because it sacrifices comprehensiveness; multiple important aspects (params, usage, behavior) are absent. The single sentence does not front-load critical 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 the tool has two parameters, no output schema, and no annotations, the description must be highly informative. It is not. It omits what the tool returns, how to interpret results, and any prerequisites or limitations. Completely inadequate 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?

With 0% schema description coverage, the description should explain parameter meanings beyond the schema. It adds that the asset is 'tokenized' and hints at 'trading context', but does not clarify the 'days' parameter (likely a lookback period) or the expected format of 'symbol'. Very minimal added 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 'Full trading context for a tokenized asset' gives a general idea but is vague. It implies retrieving market data for a tokenized asset but does not specify what 'context' includes (e.g., price, volume, fundamentals). It fails to distinguish from sibling tools like 'candles' or 'history' which may provide overlapping data.

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 is given on when to use this tool versus alternatives. With many sibling data tools (calendar, candles, earnings, etc.), the agent has no criteria to decide that 'context' is the right choice for a given task.

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 behavioral traits. It implies a read operation ('next earnings date') which is likely non-destructive, but doesn't explicitly state safety or lack of side effects. There's no mention of rate limits, authentication needs, or what happens with invalid symbols. The description is minimally transparent but not misleading.

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 core purpose. It is concise and wastes no words. While it could benefit from more detail, it is not overly verbose. A score of 4 reflects efficient use of space without being incomplete to the point of harm.

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 low schema coverage (0%), the lack of output schema, and the presence of non-required parameters with defaults, the description is insufficient. It doesn't clarify what a 'rolling calendar window' means in practice (e.g., forward-looking vs backward-looking), how multiple symbols are handled, or the format of the output. More context is needed for reliable agent usage.

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

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

Schema description coverage is 0% (the schema has no descriptions for parameters), so the tool description must compensate. It mentions 'days' implicitly via 'rolling calendar window' and 'symbol' explicitly, but doesn't explain the meaning of default values (e.g., days=7 means look ahead 7 days) or constraints. This adds some clarity but leaves ambiguity.

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: 'Next earnings date for a symbol, or a rolling calendar window'. It uses specific terms ('earnings date', 'symbol', 'rolling calendar window') that convey the resource and scope. However, it doesn't explicitly distinguish it from sibling tools like 'calendar' or 'history', which could also involve date-related data, so it misses the top score.

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

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

The description offers no guidance on when to use this tool versus alternatives. With siblings like 'calendar' (broader events) and 'history' (past data), an agent would benefit from knowing that this is specifically for upcoming earnings dates, not historical earnings or other calendar events, but such context is absent.

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 fully bears the transparency burden. It reveals the tool is free and non-payment-related, but does not disclose whether feedback is anonymous, how it gets processed, whether multiple submissions are allowed, or any rate limits. The lack of behavioral context (e.g., 'This is a one-way communication; no guaranteed response') leaves the agent under-informed.

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

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

The description is two sentences long with no filler. Front-loaded with the key action 'FREE feedback', followed by a concise list of examples. However, the phrase 'No payment' repeats the concept of 'FREE' and could be removed for even tighter structure.

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 low complexity and presence of an output schema (which presumably handles return value documentation), the description covers the basic purpose and some affordances. However, the complete lack of parameter documentation and behavioral transparency makes it merely adequate, 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 description coverage is 0%, meaning the description must compensate for all four parameters. It only mentions 'wanted' implicitly via the feedback request and fully ignores 'contact', 'context', and 'category'. The agent has no guidance on format, constraints, or how to fill these fields beyond the schema's basic names.

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: collecting user feedback about missing endpoints, wrong output shapes, price objections, or bugs. The verb 'tell us what you needed but didn't get' is specific, and the examples disambiguate from the 16 sibling tools, none of which suggest feedback collection.

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

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

The description explicitly says 'FREE feedback' and 'No payment', which guides usage when to use it (free-form feedback) and hints at when not to (not for paid requests). However, it does not explicitly contrast with siblings or state exclusions like 'do not use for general support questions'.

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 transparency burden. It states only the basic promise of returning latest SEC filings, but does not disclose details like what types of filings are included, how many are returned, or the output format. This lack of behavioral context is a notable gap.

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

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

The description is a single front-loaded sentence that accurately conveys the core purpose without any filler. Every word contributes meaning, making it highly concise and 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?

The tool is simple and has no output schema, so the description does not need to explain return values. However, it omits important context such as how 'n' affects results and the specific nature of the filings, leaving some ambiguity for the agent.

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

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

Schema description coverage is 0% for the 2 parameters. The description indirectly explains 'symbol' via 'equity symbol' but makes no mention of 'n', leaving its meaning and impact unexplained. The description does not compensate for the schema's silence.

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

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

The description clearly identifies the tool's function: returning the latest SEC filings for an equity symbol. It distinguishes itself from siblings like earnings, calendar, and history by focusing specifically on SEC filings, though it lacks an explicit verb.

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 intended use is implied by the description—use when you need the latest SEC filings for a stock. No explicit guidance is provided about when to prefer this over alternatives, such as earnings or history, nor are there 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 of behavioral disclosure. It implies a read operation (historical data retrieval) but does not explicitly state read-only behavior, rate limits, data freshness, or any side effects. The mention of 'daily closes + range change' only hints at output shape without 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 a single fragmented phrase rather than a well-structured sentence. While short, it sacrifices clarity and completeness. Under-specification rather than 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 no output schema, the description should fully explain the return value. 'Daily closes + range change' is vague—does it return one object per day? What is the range change formula? The tool is simple (2 params), but the description omits essential details about the output structure, making it incomplete.

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

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

Schema description coverage is 0%, and the description adds no explanation of the parameters. The phrase 'for a symbol' loosely suggests the 'symbol' parameter, but the 'days' parameter and the meaning of 'range change' are not elaborated. The description fails to compensate for the lack of 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 'Daily closes + range change for a symbol' clearly indicates the tool returns daily closing prices and a range change metric for a given symbol. It is specific about the data resource, though it lacks an explicit verb. It distinguishes from sibling tools like 'candles' (OHLC) and 'calendar', but does not explicitly differentiate.

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 usage guidance is provided. The description does not specify when to use this tool over alternatives like 'candles' for detailed OHLC data or 'context' for broader market data. There is no mention of prerequisites, filters, or context in which this tool is appropriate.

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

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

With no annotations present, the description carries full burden for behavioral traits. It mentions 'search' and 'extraction', implying a read operation, but does not disclose side effects, authentication needs, rate limits, or output format. This is insufficient for an agent to understand safety or impact.

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 short (single sentence) and front-loaded with the core purpose. However, it lacks necessary detail that would make it earn its place; it is not so much concise as underdeveloped. A 3 is appropriate for minimal viability.

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

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

Given the tool's complexity (3 parameters, no output schema, no annotations), the description omits essential context about return values, parameter constraints, and usage scenarios. It is insufficient for an agent to predict behavior or handle results 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 0%, meaning the input schema provides no explanations for parameters. The description does not address any of the three parameters (q, limit, country), failing to add meaning beyond variable names and types. This severely impairs correct invocation.

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 a specific verb ('search') with a modifier ('location-targeted') and a distinctive outcome ('place-link extraction'). It indicates a resource and action, but does not explicitly differentiate from sibling tools like 'search' or 'place', which may cause ambiguity for an AI agent.

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 is provided on when to use this tool versus alternatives (e.g., 'search' for general queries, 'place' for details). There are no conditions, prerequisites, or exclusions mentioned, leaving the agent without context for 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?

No annotations are provided, so the description carries full burden. It mentions 'release flags' but does not explain what they mean, nor does it disclose data source, update frequency, or behavior (e.g., real-time vs. cached). Minimal but not misleading.

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

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

Single sentence with 11 words, front-loaded with core purpose and specific examples. No fluff; 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?

For a zero-parameter tool with no output schema, the description is mostly sufficient by naming the indicators. It could be improved by briefly noting the output format or that it's a snapshot, but the simplicity keeps it adequate.

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

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

There are zero parameters and schema coverage is 100% (empty). The description adds meaning by listing the types of indicators included (CPI, NFP, U3, oil), which provides semantic value beyond the empty schema.

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

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

The description clearly states the tool provides 'Latest US macro indicators' and lists specific indicators (CPI/NFP/U3/oil) with release flags. The verb 'get/retrieve' is implied, and it distinguishes itself from sibling tools by specifying a focused set of economic indicators.

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 fetching US macro data but provides no explicit when-to-use or when-not-to-use guidance. With zero parameters, the tool is straightforward, but no alternatives or exclusions are mentioned relative to siblings like 'calendar' or 'context'.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states 'local search + business website content' without explaining whether the tool is read-only, what data it returns, how it combines results, or any side effects. This is insufficient for an agent to predict behavior.

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

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

The description is a single sentence, which is concise but not effective. It sacrifices clarity and completeness for brevity, failing to earn its place as a useful guide. The front-loaded phrase 'Compound: local search + business website content' is not a clear action statement.

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 three parameters, no output schema, no annotations, and sibling tools with similar domain (local, search), the description is grossly incomplete. It does not explain what the tool returns, how to use the parameters, or how it differs from alternatives, providing no value for correct selection or invocation.

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

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

Schema description coverage is 0%, and the description provides no additional meaning for the three parameters (q, country, max_chars). The description must compensate for the lack of schema documentation but fails to explain their roles, formats, or constraints, leaving the agent with no guidance beyond the parameter names.

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 'Compound: local search + business website content' is vague and lacks a clear verb. It does not specify what action the tool performs (e.g., search, retrieve, combine). The tool name 'place' is a noun, and the description is a label rather than a functional statement, making it difficult for an agent to understand the intended operation.

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

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

No guidance is provided on when to use this tool versus siblings like 'local' (likely for local searches) or 'search' (general search). There is no mention of prerequisites, limitations, or alternatives, leaving the agent without context for appropriate invocation.

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?

Since no annotations are provided, the description must fully disclose behavior. It states only that the output is 'clean Markdown', but does not mention what happens if the URL is invalid, blocked, or requires authentication. It also does not clarify whether the tool handles JavaScript-rendered pages, rate limits, or returns any error messages. This lack of transparency could lead to unexpected failures.

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 at only six words, which is efficient but borderline under-specified. It front-loads the purpose, but could be improved by adding a few more words about what the tool does without becoming verbose.

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

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

Given the lack of output schema, contextual complexity, and many siblings, the description is incomplete. It does not explain what 'clean Markdown' means (e.g., stripping ads, navigation, only main content), nor does it address potential issues like JavaScript rendering or large page handling. For a tool that fetches arbitrary web content, more detail is needed for reliable agent usage.

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

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

Schema description coverage is 0%, and there is only one parameter ('url') with no description in the schema. The tool description does not add any semantics about the URL format (e.g., must be fully qualified, supported protocols, etc.). With a single required parameter, the baseline expectation is moderate, but the description should at least clarify that it accepts any valid HTTP/HTTPS URL.

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 'Any public URL as clean Markdown' clearly indicates that this tool takes a URL and returns its content in Markdown format. It is distinct from siblings like 'screenshot' (which captures an image) and 'url_safety' (which checks URL safety). The verb 'read' is specific, but the resource is implied as web content.

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 is provided on when to use this tool versus alternatives like 'screenshot' for visual content or 'search' for finding information. There is no mention of prerequisites, limitations (e.g., paywalled sites, dynamic content), or expected use cases. The description is too minimal for an agent to decide between read and other 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 bears full responsibility for behavioral disclosure. It only states 'Screenshot of any public URL (viewport PNG)', omitting details about viewport size, load time, error handling, rate limits, or whether authenticated pages work. This leaves significant behavioral ambiguity.

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, front-loaded sentence that communicates the core purpose without extraneous words. It could be slightly more informative (e.g., 'returns a viewport PNG image') without losing 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?

With no output schema and no annotations, the description is the sole source of context. It does not explain the return format (beyond 'PNG'), possible errors, or how the tool interacts with sibling tools like 'url_safety'. For a tool with 1 parameter and no technical metadata, more guidance is expected to complete the agent's understanding.

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

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

Schema description coverage is 0% (no param descriptions provided), so the description must compensate. It adds the constraint that the URL must be 'public', which is meaningful but minimal. It does not specify expected URL format, protocol support, or what happens with non-public URLs. Baseline 3 is appropriate given partial compensation.

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 captures a screenshot of any public URL and outputs a viewport PNG. The verb and resource are unambiguous. However, it does not differentiate from sibling tools like 'read' or 'url_safety', which could be used for retrieving content from URLs.

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 is provided on when to use this tool versus alternatives (e.g., 'read' for text extraction or 'url_safety' for checking URLs). There are no prerequisites, restrictions, or examples of appropriate use cases.

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

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

The description hints at 'token-efficient' results, which suggests a behavioral trait, but without annotations, it fails to disclose other important behaviors such as read-only nature, authentication needs, rate limits, or what the response contains.

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, which is concise but not effectively structured. It lacks bullet points or clear separation of concerns, and the brevity sacrifices important 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?

Given the tool has 5 parameters, no output schema, and no annotations, the description is grossly incomplete. It does not explain pagination (cursor), default behaviors, or return format, leaving the agent with significant gaps.

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

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

Schema description coverage is 0%, so the description must compensate. It only implies the 'engine' parameter via the engine names, but does not explain 'q', 'limit', 'cursor', or 'country'. This is insufficient for an agent to use the tool correctly.

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 'search results' with engine options, which is clear enough for a generic search tool. However, it does not differentiate from sibling tools like 'local' or 'history', and the resource being searched is not explicitly stated (e.g., web search).

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

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention when not to use it or suggest sibling tools for specific cases like location or financial data.

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 disclose behavioral traits. It only states what resource is returned, but does not mention idempotency, data freshness, pagination, or any side effects. For a tool requiring no parameters, the behavior is simple, but there is no explicit confirmation that it is a safe read 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?

One extremely concise sentence that immediately states the tool's purpose. It is appropriately front-loaded with the key concept 'Tradeable'. Could be slightly more descriptive, but for a param-less tool this is sufficient.

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 should at least hint at what the returned universe looks like (e.g., list of asset symbols or objects). It only says 'Tradeable asset universe' which is vague. While the intended use may be clear from context, it lacks explicit completeness regarding output format.

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?

Zero parameters and 100% schema coverage, so baseline 3 is appropriate. The description adds no parameter meaning beyond what the schema provides, but no additional info is needed.

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

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

The description explicitly states 'Tradeable asset universe (Hyperliquid xyz DEX)', clearly identifying that this tool returns the list of tradeable assets on the Hyperliquid DEX. No tautology; it distinguishes from siblings like 'candles' or 'calendar' which serve different purposes.

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

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

No guidance on when to use this tool vs. alternatives. It does not mention that this should be called before querying other data tools that require an asset identifier, nor does it explain any prerequisites. The agent is left to infer usage context.

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

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

With no annotations, the description carries full burden. It reveals one behavioral trait: captcha/bot-wall handling. However, it omits other important behaviors such as redirect handling, request headers, rate limiting, error codes, or output format details (e.g., whether it returns the full page or truncated content). The single trait is insufficient for an agent to predict side effects.

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, highly concise and front-loaded with the core purpose. Every word adds value. However, the extreme brevity sacrifices necessary detail, making it slightly under-specified. Still, it avoids fluff and this dimension rewards 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 two parameters (one required), no output schema, and no schema descriptions, the description is far from complete. It fails to explain return values, error conditions, authentication needs (public only), or the effect of max_chars. A thorough description would cover these to enable safe and correct use.

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

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

Schema description coverage is 0%, so the description must compensate. It does not mention either parameter ('url' or 'max_chars'). The description does not clarify what 'url' format is expected (e.g., must include protocol) or what 'max_chars' controls (truncation limit). Without this, an agent cannot confidently provide correct values.

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 fetches a URL and returns raw HTML, specifying it handles captcha/bot walls. The verb 'unlock' is somewhat ambiguous, but the description resolves it to retrieving HTML. Among siblings like 'read', 'screenshot', and 'url_safety', this stands out as the HTML-fetching tool.

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

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

No guidance is provided on when to use this tool versus alternatives like 'read' (which might return structured data), 'screenshot' (visual capture), or 'url_safety' (safety check). There is no mention of prerequisites, limitations, or exclusions (e.g., private URLs, non-HTTP schemes).

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 indicates a nondestructive, read-only operation (reputation check). With no annotations, it partially carries the burden. However, it lacks details on what the tool returns (e.g., a Boolean, score, or report), or any rate limits or authentication needs, leaving some transparency 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 two words plus a parenthetical. It is extremely concise and front-loads the essential information. Every word is meaningful with no 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?

Given the single parameter and lack of output schema, the description is too sparse. It does not explain what the 'check' returns (e.g., safe/unsafe label, risk score), or whether it supports batching or works for all URL types. For a security-critical tool, more detail is expected.

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

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

Schema description coverage is 0%, so the description must compensate. It does not clarify the URL format (e.g., must include scheme). However, with only one required parameter named 'url', the tool's purpose is fairly obvious, earning a baseline of 3.

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

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

The description clearly states the tool checks URL reputation for malware and phishing. It uses specific, relevant verbs and resource types, and the focus on security threats distinguishes it from sibling tools like 'search' or 'read'.

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 is provided. While the context of reputation checking is clear, the description does not mention what kinds of URLs are supported, limitations, or when a different tool (e.g., 'search') would be more appropriate.

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