gateway

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

No annotations provided, so the description carries full burden. It discloses '(read-only)' but lacks details on authentication, rate limits, error behavior, or what happens if the order is not found.

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

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

Single sentence with no waste. It conveys purpose and safety in minimal characters, earning its place efficiently.

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

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

Given no output schema, no annotations, and a simple parameter, the description is thin. It does not explain what the response contains, error handling, or any access requirements, leaving gaps for an 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 coverage is 100% for the single parameter, with a clear description in the schema. The tool description adds no extra meaning beyond what the schema already provides, so baseline 3 applies.

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

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

Description clearly states the verb 'look up' and resource 'delivery status of an Amazon order', and adds '(read-only)' for safety. This distinguishes it from siblings like grubhub__order_track by vendor prefix and specific resource.

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 or not use this tool versus alternatives. There is no mention of prerequisites, limitations, or when to prefer sibling tools like grubhub__order_track.

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 only states 'Read' and includes a risk:medium tag, but does not disclose behavioral traits such as whether it's read-only, required permissions, or what happens if no data is available. The description is minimal and insufficient for 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 very concise, consisting of a single phrase with a risk tag. It is front-loaded with the core purpose. No wasted words, but it could include more structure 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?

For a simple read tool with two optional date parameters and no output schema, the description is minimal but somewhat adequate. It lacks details on return value format, error behavior, or data range constraints, which would improve completeness. However, given the simplicity, it is moderately complete.

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

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

Schema description coverage is 100%, so both parameters (start and end) have descriptions in the schema. The tool description adds no additional meaning beyond what 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 clearly states 'Read heart-rate data from Apple Health', specifying the verb (Read) and resource (heart-rate data). It distinguishes from sibling tools like applehealth__sleep_read and applehealth__steps_read, which cover different health metrics. However, it does not elaborate on what the data includes (e.g., samples, averages), so slightly less than perfect.

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 reading heart rate data, and given sibling tools, it's clear when to use this tool versus others. However, there is no explicit guidance on when to use it, when not to, or what alternatives exist beyond the context of sibling tool names. Usage is implied but not articulated.

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 only says 'Read', which implies non-destructive behavior, but does not disclose other traits like data freshness, error handling, or rate limits. The 'risk:medium' tag is present but not explained.

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 with no superfluous content. It is efficient but lacks depth. The risk tag could be considered noise, but overall it is concise.

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

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

Given the absence of an output schema and the simplicity of parameters, the description should provide more context about what the sleep-analysis data includes (e.g., duration, stages). It does not, leaving the agent with incomplete understanding of the tool's output.

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

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

Schema description coverage is 100%, so the schema already documents both parameters. The description adds no additional meaning beyond what is in the schema. 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 verb 'Read' and the specific resource 'sleep-analysis data from Apple Health'. This immediately distinguishes it from sibling tools like 'applehealth__heart_rate_read' and 'applehealth__steps_read' by resource type.

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 prerequisites, typical use cases, or exclusions. The agent is left to 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?

The description does not disclose behavioral traits beyond the basic read operation. With no annotations, the description carries the full burden but omits details like return format, error handling, or permissions.

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, consisting of a single sentence and a prefix. It avoids fluff, but it is perhaps too minimal.

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 simplicity of the tool (2 optional parameters, no output schema), the description is minimal but might be sufficient for an agent to use it, though it lacks details on output structure.

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

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

Schema description coverage is 100%, so the schema already documents both parameters adequately. The description adds no additional meaning beyond what the schema provides.

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

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

The description clearly states the action ('Read') and the specific resource ('step-count data from Apple Health'), distinguishing it from sibling tools like applehealth__heart_rate_read or applehealth__sleep_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 explicit guidance is provided on when to use this tool versus alternatives. The name implies it's for step data, but there's no mention of context or exclusions.

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

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

The description adds value by stating that the tool is read-only, low-risk, and requires no authentication. It also describes the return format. However, it does not mention potential rate limits, caching behavior, or possible errors, which are minor gaps given the tool's simplicity.

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, consisting of two sentences that front-load the action and then provide return and auth details. Every sentence serves a purpose with no unnecessary words.

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

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

Given the tool has no parameters and no output schema, the description adequately covers the return values (topic names, display labels, links) and authentication requirements. It provides all necessary context for an AI agent to use the tool correctly.

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

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

The tool has zero parameters, and the schema coverage is 100% trivially. According to the guidelines, a baseline score of 4 is appropriate since there are no parameters to describe, and the description does not need to add further information.

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 'Fetch the current trending topics on Bluesky' and specifies the resource (trending topics) and the return values (topic names, display labels, links). It distinguishes itself from sibling tools as the only Bluesky-specific tool, leaving no ambiguity about its purpose.

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

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

The description explicitly states that no account or API key is required, implying ease of use. However, it does not provide guidance on when to use this tool vs alternatives like hackernews__stories_top or twitter__tweets_search, nor does it state when not to use it. Given the absence of similar Bluesky tools, the omission is minor.

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 provided, so description must disclose behavior. Only mentions 'read-only' and risk level. Does not address authentication, rate limits, or error behaviors (e.g., invalid account).

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 risk tag upfront. No redundant information. Every word serves a purpose.

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

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

Adequate for a simple read operation with one optional parameter. Lacks return format or examples, but no output schema exists. Room for improvement in explaining result structure.

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

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

Schema coverage is 100% with description for the single parameter. Description adds 'defaults to primary' but attribute already implied. No significant value added 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?

Clearly states verb 'read' and resource 'current balance of a Chase account'. Read-only nature is explicit, distinguishing it from write operations. No sibling tool duplicates this function.

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?

Implied usage for checking account balance, but no explicit guidance on when to use vs alternatives (e.g., other balance sources). No exclusions or prerequisites 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?

No annotations are provided, so the description carries the full burden. The description mentions a risk of 'low' in the bracket prefix but does not disclose behavioral traits such as required permissions, rate limits, or consequences of invalid queries. This is insufficient.

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 conveys the core functionality without any wasted words. It is appropriately front-loaded 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?

There is no output schema, so the description could have explained the return format or pagination behavior. It does not. However, given the tool's simplicity (3 parameters, read-only nature implied by name), the description is minimally adequate.

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

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

Schema coverage is 100%, with each parameter having a description in the schema. The tool description adds 'over a time range' which is already implied by the from/to parameters. It does not provide additional semantic insight 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 states 'Search and read logs from Datadog over a time range', which clearly identifies the verb (search/read) and resource (logs). It is sufficiently distinct from sibling tools that cover different domains like package tracking, health data, etc.

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 searching logs over a time range but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it. No sibling tool directly competes, so a score of 3 is fair.

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 convey behavioral traits. It includes a 'risk:low' tag but does not state that the operation is read-only, nor does it disclose potential side effects or error conditions.

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

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

The description is a single sentence, making it concise. The prefix '[delta · risk:low]' is somewhat non-standard but does not detract heavily. Every part provides necessary information 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?

The description adequately conveys the basic purpose but lacks details about the output format (e.g., image, text) and error handling. Given the tool's simplicity, this is minimally acceptable but not fully informative.

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

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

The input schema covers 100% of parameters with descriptions, so the description adds no additional meaning. The baseline score of 3 is appropriate as the schema already provides adequate semantic information.

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 a boarding pass for a Delta flight, using a specific verb and resource. However, it does not explicitly differentiate from the sibling tool 'wallet__boardingpass_show', which likely serves a similar purpose for other airlines.

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, nor are any prerequisites or limitations mentioned. The description lacks context for 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?

No annotations provided, so description must carry burden. It discloses read-only behavior ('look up'), data returned, and lack of authentication. However, it does not mention potential rate limits, data freshness, or source of the data, which would strengthen 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?

Two sentences, no filler, front-loaded with purpose. 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 simple, single-parameter tool with no output schema, the description fully covers what the tool does and returns. Sufficient for an agent to select and invoke correctly.

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

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

Schema has 100% coverage with a single parameter described. Description adds concrete examples ('express', '@types/node'), adding value beyond the schema definition. Baseline 3, elevated for helpful examples.

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?

Clearly states 'look up the latest version, description, license, and dependencies of an npm package', specifying the resource (npm package) and the exact data returned. Distinguishes from sibling tools like duvera__dev_pypi_package which is for Python packages.

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?

Mentions that it works for scoped packages and requires no account, but does not explicitly guide when to use this tool over alternatives or exclude scenarios. Implied usage is clear but no when-not or alternatives listed.

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 full burden. It explains what the tool does but lacks details on error handling, rate limits, or response format. While adequate for a simple lookup, more transparency 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?

The description is concise and well-structured: a risk tag, a clear purpose statement, and an additional note on accessibility. Every sentence adds value 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?

Given the tool's simplicity (one parameter, no output schema), the description covers the essential aspects. It could mention error behavior or return format, but overall it is 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?

The input schema has 100% description coverage for the single parameter 'package'. The description adds concrete examples ('e.g. "requests" or "fastapi"'), enhancing clarity beyond the schema's description alone.

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

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

The description clearly states the verb 'Look up' and the resource 'Python package on PyPI', specifying the exact data returned (version, summary, license, homepage). It distinguishes from sibling tools like duvera__dev_npm_package, which serves a similar role for npm packages.

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 notes 'No account required,' which implies ease of use and no authentication barrier. However, it does not explicitly contrast with siblings (e.g., npm equivalent) or mention when not to use this tool.

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

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

With no annotations provided, the description carries the full burden. It includes risk level ('risk:low'), states no account is needed, and describes the output (top 5 by relevance with title, link, score, answer status). This is good coverage for a simple read search tool, but it could mention rate limits or data source reliability.

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

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

The description is extremely concise: only two sentences. The first sentence states the purpose and risk level, and the second provides key output details and the no-account requirement. Every sentence 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 the tool's simplicity (one required parameter, no output schema), the description covers everything needed: purpose, input format, output structure (fields and count), and access constraints (no account). It is fully informative for selection and invocation.

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

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

The input schema already has 100% coverage with a clear description of the required 'query' parameter, including examples. The tool description does not add additional parameter semantics beyond what the schema provides, so it meets the 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 explicitly states 'Search Stack Overflow questions by keyword,' which clearly identifies the tool's purpose. It also distinguishes itself from sibling tools by specifying Stack Overflow, a unique domain. The mention of returning top 5 results with specific fields adds further clarity.

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 ('Search Stack Overflow questions by keyword') and notes that no account is required, which helps the agent decide when to use it. However, it does not explicitly mention when not to use this tool or suggest alternatives among the many 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 provided, so description carries the full burden. It states the tool is read-only and requires no account, which covers safety and access. It does not disclose rate limits or data freshness, but the simplicity of the tool makes this 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?

Description is a single front-loaded sentence with no unnecessary words. It packs purpose, usage context, and risk level efficiently.

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

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

No output schema exists, but description omits return format details. While the tool is simple and likely returns a standard object, explicitly stating the output structure would improve completeness. However, given the well-known API, the current description is mostly 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 coverage is 100%, so baseline is 3. Description adds value by giving an example for 'ids' and noting default 'usd' for 'vs_currencies', which aids understanding beyond the 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?

Description clearly states it retrieves current spot prices for cryptocurrencies using CoinGecko IDs, with optional fiat currency. It explicitly mentions the resource (cryptocurrency prices) and the source (CoinGecko ids), distinguishing it from sibling tools like duvera__finance_exchange_rates for fiat pairs.

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 indicates it provides read-only market data with no account required, clearly defining when to use. It does not explicitly state alternatives, but the sibling list includes duvera__finance_exchange_rates for fiat exchange rates, providing implicit 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?

With no annotations, the description correctly identifies the tool as read-only and requiring no account. It does not detail output format, update frequency, or list of currencies, leaving some behavioral aspects unspecified.

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 with a leading tag, no unnecessary words. It front-loads the key 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 zero-parameter tool, the description covers purpose, safety, and authentication. However, it lacks details about the output structure and the specific currencies included, which could be useful for an 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?

There are no parameters, so the schema coverage is effectively 100%. The description adds no parameter details, which is acceptable as the schema is empty.

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

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

The description clearly states it provides live USD exchange rates against major currencies. The verb 'Live' and resource 'exchange rates' are specific. It implicitly distinguishes from siblings like duvera__finance_crypto_price by focusing on fiat currencies.

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 'Read-only, no account required,' which implies it's safe to call without prerequisites. However, it does not explicitly state when to prefer this tool over alternatives or provide exclusion criteria.

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 behavioral traits. It mentions 'No account required' and the prefix '[duvera · risk:low]' indicates low risk, but it does not explicitly state that the operation is read-only, nor does it discuss error handling, rate limits, or pagination. The description adds some context but lacks 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: one sentence plus a short note on account requirements. Every sentence provides essential information without waste. The prefix '[duvera · risk:low]' is part of the naming convention and is not excessive.

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 (single parameter, no output schema), the description is fairly complete. It explains the input, the output fields, and the requirement of no account. It does not mention if results are a list, matching behavior, or format details, but for a basic search tool, it provides sufficient context for an AI 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 coverage is 100% with the 'query' parameter already having a description. The tool's description adds contextual examples and clarifies the parameter's usage, which adds value beyond the schema. However, no additional parameters are discussed, and the schema already provides adequate definition.

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: search recipes by dish name. It provides examples and lists the returned fields (ingredients, instructions, category, cuisine). The sibling tool 'duvera__food_restaurant_search' is distinguishable by name, and the description reinforces this by focusing on recipes rather than restaurants.

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 searching recipes by dish name, but it does not explicitly state when to use this tool over alternatives like 'duvera__food_restaurant_search' or provide conditions for when not to use it. No guidance on limitations or exclusion criteria 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?

With no annotations provided, the description carries full burden. It discloses key behavioral traits: 'Read-only, no account required' and the data source. However, it does not mention rate limits, pagination, or output format, which would enhance 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 with two sentences, front-loads the risk tag, and contains no fluff. Every word 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?

For a simple search tool with one parameter and no output schema, the description covers the purpose, data source, and safety. It could mention the type of results (e.g., list of places) but is largely complete.

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

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

Schema coverage is 100% for the single parameter, and the schema description already provides examples. The tool description adds value by specifying 'by name or location', which clarifies the query intent beyond the schema.

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

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

The description clearly states the verb 'Search', the resource 'restaurants and food places', and the data source 'using OpenStreetMap'. This distinguishes it from sibling tools like duvera__food_recipe_search and duvera__geo_geocode.

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 implicit context (read-only, no account needed) but does not explicitly state when to use this tool versus alternatives like duvera__food_recipe_search or duvera__geo_geocode. No usage exclusions or comparisons are given.

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

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

With no annotations, the description carries full burden. It discloses return fields (lat/lng, country, timezone, population) and mentions no authentication needed. While it doesn't explicitly state read-only behavior, that is implied by the operation. The risk:low tag adds context. Missing details about error handling or rate limits, but sufficient for typical use.

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 short sentences plus a tag, all front-loaded with the tool's purpose and usage guidance. Every sentence adds value: the first states the core function and outputs, the second provides usage context. 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?

Despite no output schema, the description explicitly lists the return fields (lat/lng, country, timezone, population) and the usage scenario. It is complete for an agent to understand what the tool does and when to invoke it. No critical missing 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 coverage is 100% with a well-described 'query' parameter. The description adds examples ('Berlin', 'Springfield, Illinois') reinforcing the schema description but does not add new constraints or formatting details. Given high coverage, a score of 3 is appropriate as the description adds marginal value beyond the schema.

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

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

The description clearly states the tool's function: converting a city or place name to latitude/longitude, country, timezone, and population. It uses a specific verb 'Convert' and provides concrete examples like 'Berlin' and 'San Francisco'. Among siblings, it is distinct as a geocoding tool, not overlapping with weather or 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?

Explicitly instructs to use this tool before weather.current or weather.air-quality when only a place name is available, providing clear when-to-use guidance. Also notes 'No account required' to set expectations about prerequisites. Does not mention when not to use, but the positive guidance is strong.

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 clearly states it's a read operation, returns 404 for no releases, and requires no auth. It does not mention rate limits or API details, but for a simple tool this is sufficient. It explicitly says 'latest published release' to avoid confusion with drafts.

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 main action. The prefix '[duvera · risk:low]' is slightly extraneous but does not hinder clarity. Every sentence adds value, but the structure could be more streamlined without the prefix.

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

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

Given no output schema, the description lists the fields returned (tag, name, notes, date) and mentions the 404 edge case. It does not detail the response structure or error handling for invalid repos, but for a straightforward tool this is adequate. It covers the main usage context.

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

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

Schema description coverage is 100%, so baseline is 3. The description provides examples like 'Repository name, e.g. "express".' which mirrors the schema descriptions. It adds context by specifying 'public GitHub repository' but does not significantly enhance parameter 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 verb 'Get' and the resource 'latest published release of a public GitHub repository'. It specifies what is returned (tag, name, notes, date) and distinguishes itself from sibling tools like 'duvera__github_read_file' and 'duvera__github_search_repos' by focusing on releases.

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 indicates when to use the tool: for public GitHub repositories. It notes that it returns 404 for repos with no releases, which is a condition. 'No auth required' clarifies ease of use. However, it does not explicitly compare with alternatives or state when not to use it, but the context is 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?

Only mentions 'Read-only' and no annotations exist; does not disclose rate limits, authentication, or error handling for a GitHub API 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?

One line, front-loaded with risk tag, 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?

Simple tool but lacks mention of return value (file content) or error cases, though no output schema exists.

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

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

Schema already describes all parameters clearly; description adds no extra 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?

Clearly states 'Read a file from a public GitHub repository' with specific verb and resource, and distinguishes from sibling tools like duvera__github_search_repos.

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 for reading any file from public repos, but lacks explicit when/to-not-use compared to other GitHub 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 provided, the description carries the full behavioral burden. It discloses the result limit ('top 5') and that no authentication is required, which are important behavioral traits. It does not mention output format or error behavior, but it provides useful transparency for a simple search 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 concise: one sentence plus a parenthetical clause. Every part adds value—the tool's purpose, risk label, result behavior, and authentication requirement. 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 the tool's simplicity (one parameter, no output schema) and absence of annotations, the description is fairly complete. It covers purpose, result limit, and auth. Missing details like output fields, but acceptable for a straightforward search 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?

The schema covers 100% of the single parameter 'query' with a description that includes examples. The tool description adds no additional meaning beyond the schema, meeting the baseline for high schema coverage.

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

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

The description clearly states the tool searches public GitHub repositories by keyword and specifies it returns the top 5 results by stars. This distinguishes it from sibling tools like duvera__github_latest_release and duvera__github_read_file that perform different GitHub-related tasks.

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 searching public repos by keyword. It does not explicitly say when to avoid this tool or mention alternatives, but the context of sibling tools provides implicit guidance. Lacks explicit exclusions.

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

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

With no annotations, the description provides useful behavioral details: it is a read-only operation (no account required), returns specific fields, and mentions risk level. However, it does not disclose rate limits or pagination behavior.

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

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

The description is a single front-loaded sentence that efficiently conveys the tool's purpose, risk level, and return fields with 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 the single parameter and absence of output schema, the description is sufficiently complete. It covers what the tool does, what it returns, and account requirements. Minor gaps include potential result limits or error handling.

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 the description adds value by explaining that results are ranked by relevance and providing example search terms, which goes beyond the schema's simple 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 it searches Hacker News stories by keyword, ranked by relevance. It implicitly distinguishes from sibling tools like 'duvera__news_top_stories' through the verb 'search', 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?

The description implies usage for keyword-based search on Hacker News but does not explicitly state when to use this tool versus alternatives (e.g., for top stories) or provide any when-not conditions.

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

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

Description correctly asserts read-only behavior and no account requirement, but does not disclose other traits like rate limits, caching, or response format. With no annotations, this is minimally 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?

Description is very short and front-loaded with the risk tag. However, it is not a complete sentence and lacks a clear verb, slightly reducing clarity.

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

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

Given no parameters or output schema, the description is minimal. It does not explain what 'top stories' means (e.g., recency, points) or the expected response structure.

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

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

Tool has no parameters, and schema coverage is 100%. Description adds context that it returns 'top stories', which is sufficient for a parameterless tool.

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

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

Description clearly states the tool retrieves top stories from Hacker News and is read-only. However, sibling 'hackernews__stories_top' likely provides the same data, and no differentiation is made.

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 like 'hackernews__stories_top'. The description does not mention use cases or exclusion criteria.

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 provided, so description must fully disclose behavior. It specifies low risk and no auth needed, which is helpful. But it omits details like handling of unknown words, rate limits, or return format, which are important for a tool with no annotations.

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

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

Single sentence efficiently communicates purpose and key constraints. No extraneous text; the bracketed risk tag adds value. Perfectly front-loaded and concise.

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 lookup tool with one parameter and no output schema, the description covers the essentials: what it does and that no account is required. It lacks details on output structure or error behavior, but given the tool's low complexity, it is sufficiently complete.

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

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

Schema coverage is 100% with a clear description of the 'word' parameter. The description adds minimal extra value beyond the schema, noting that it returns phonetics, part of speech, and examples, but that pertains to output. Parameter semantics are adequately covered by 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?

Description clearly states the tool provides definitions, phonetics, part of speech, and examples for an English word. This is a specific verb-resource pair that distinguishes it from sibling tools, which are mostly non-dictionary references.

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?

Mentions 'No account required,' providing a usage prerequisite. However, lacks explicit guidance on when to use this tool over alternatives like wiki_search, which could also define words. The context makes it fairly clear, but an explicit differentiator would improve it.

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

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

With no annotations, the description carries full burden. It mentions 'No account required' and includes a risk:low prefix. However, it does not disclose rate limits, pagination, or any side effects. For a simple read tool, this is adequate but not exceptional.

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

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

The description is a single sentence that efficiently conveys purpose, input, output, and access requirements. Every phrase 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?

For a tool with two simple parameters and no output schema, the description covers essential points: input format, output content (national/regional holidays with dates and names), and access (no account). It could mention that the result is likely a list, but overall it is sufficiently complete.

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

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

Schema description coverage is 100%, so baseline is 3. The description provides an example ('2026 + US') that reinforces the schema's parameter descriptions but does not add new semantic meaning beyond the already clear 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 that the tool returns public holidays for a given year and ISO country code. It specifies what is included (national and regional holidays with dates and names), making the purpose unambiguous. No sibling tool overlaps with this function.

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 (need public holidays for a year and country) but provides no explicit guidance on when not to use or alternatives. Given the sibling list includes other reference tools, some exclusion would be helpful, but it meets a minimal threshold.

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 states 'No account required,' which is helpful, but it does not disclose any rate limits, caching behavior, or side effects. The tool is a simple read operation, so the lack of detail is not critical but still a 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, concise sentence that front-loads the purpose and includes additional details. Every part is informative and necessary, with 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 the simple nature of the tool (1 required parameter, no output schema, no nested objects), the description is fairly complete. It specifies the input (IANA timezone), the output components (date, time, day of week, DST status), and the lack of authentication. It could mention the format of the returned date/time but is otherwise 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 coverage is 100% with a well-described 'timezone' parameter. The description only provides examples that are already present in the schema definition, adding no new semantic information 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 returns the current date and time for a given IANA timezone, including day of week and DST status. It uniquely identifies this tool among siblings, which include weather, news, and other data retrieval tools but no other time-related tool.

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

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

The description mentions 'No account required' as a positive note, but does not provide explicit guidance on when to use this tool versus alternatives. Since there are no sibling tools with overlapping functionality, the implicit usage is sufficient, but explicit guidance is lacking.

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 behavioral traits. It discloses the risk level ('risk:low'), the return fields (callsign, altitude, speed, position), and notes that no account is required, offering good transparency despite the lack of structured annotations.

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

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

The description is highly concise, consisting of four short sentences that front-load the core purpose and then add essential context (prerequisite, output, auth). No words are wasted, and the structure is easy to parse.

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 list tool with three parameters and no output schema, the description covers all key aspects: purpose, data source, prerequisite, return fields, risk level, and authentication. It provides sufficient context for an AI agent to select and invoke the tool correctly.

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

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

The input schema has 100% coverage with clear descriptions already (e.g., latitude example, radius range). The tool description adds minimal new semantic information beyond restating the purpose, so it meets the baseline but does not significantly enhance parameter understanding.

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

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

The description clearly states the specific action ('List aircraft currently airborne within a radius of a point') and identifies the resource (aircraft) and data source (adsb.lol). This provides a precise, unambiguous purpose that distinguishes it from generic 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 description advises using geo.geocode first to obtain coordinates, providing clear context for when to invoke this tool. While it does not explicitly mention alternatives or when not to use it, the prerequisite guidance is helpful for proper 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It indicates the tool is read-only ('Current air quality') and low risk ('[duvera · risk:low]'). It does not mention any destructive behavior or side effects, which is appropriate for a read operation. The description adds context about the metrics returned, enhancing 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, with three sentences that each serve a purpose: risk indication, core functionality, usage guidance, and prerequisite info. No extra words, well front-loaded with the risk tag.

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 (2 required params, no output schema), the description covers all essential aspects: input format, output content, prerequisite tool usage, and account requirements. It is complete for an agent to use correctly without additional 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?

The input schema has 100% coverage with meaningful descriptions (e.g., 'Latitude of the location (e.g. 37.77 for San Francisco).'). The description does not add extra parameter-level meaning beyond the schema; it only describes the output metrics. Baseline 3 is appropriate since schema coverage is high.

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: retrieving current air quality (US AQI, PM2.5, PM10, ozone) for a latitude/longitude. It uses specific verbs ('Current air quality') and resources ('latitude/longitude'), and while it doesn't explicitly distinguish from the sibling 'duvera__weather_current', the mention of specific metrics implies differentiation.

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 explicit guidance: 'Use geo.geocode first if you only have a place name.' This directs the agent to an appropriate sibling tool when needed. It also states 'No account required,' reducing uncertainty about prerequisites. However, it does not explicitly list conditions to avoid using this tool.

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

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

No annotations provided, so description carries burden. It discloses no account required, data source (Open-Meteo), and risk level (low). It implies read-only behavior and does not contradict schema. Lacks details on rate limits or error handling, but is adequate 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, no fluff. Information is front-loaded and each part adds value: tool name, purpose, input format, prerequisite, and authentication status.

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 simple tool with 2 required params, no output schema, and no annotations, the description covers purpose, inputs, and a key prerequisite. Could mention output units or error behavior, but is reasonably complete for typical 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 coverage is 100% with good descriptions for latitude and longitude. The description adds no extra parameter semantics beyond usage hints (e.g., geo.geocode). 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 specifies the tool retrieves 'current temperature, conditions, wind, and humidity' for a latitude/longitude, clearly distinguishing it from forecast or air quality siblings. It also mentions using geo.geocode first if only a city name, further clarifying 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?

Provides explicit guidance: use lat/lon directly, or geo.geocode if only city name. Mentions 'no account required' as a condition. Does not explicitly contrast with weather forecast or air quality tools, but the 'current' qualifier and sibling context make 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 provided, the description carries full burden. It notes 'risk:low' and 'No account required', indicating safety and accessibility. However, it does not disclose rate limits, pagination, or other constraints that might affect usage.

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 purpose, and includes a risk tag. Every sentence is essential and there is 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 explains what the tool returns, how to use the results with a sibling tool, and the permission requirement (no account needed). No output schema exists, but the description covers return value sufficiently.

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% as the query parameter has a description. The description's mention of 'keyword' does not add meaning beyond the schema's examples. Thus, 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 'Search Wikipedia articles by keyword', which is a specific verb and resource. It distinguishes from the sibling duvera__wiki_summary by mentioning that results can be used with that tool.

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

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

The description explains that the tool returns matching page titles, keys, and excerpts, and instructs to pass a result's key to wiki.summary for the full article. This gives clear guidance on when to use this tool versus the summary tool, but does not explicitly state when not to use it.

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

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

Although annotations are absent, the description provides risk level (low) and authentication info (no account required). It could mention potential limitations like maximum summary length, but is sufficient for a simple read 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?

Single sentence with essential context, no unnecessary words. Information is front-loaded efficiently.

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

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

For a tool with one required parameter, no output schema, and no annotations, the description covers purpose, prerequisite step, risk level, and authentication requirements completely.

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

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

The description enriches the title parameter with examples and origin (from wiki.search results), adding significant meaning beyond the schema's documentation. Schema coverage is 100%, and the description provides extra clarity.

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 gets the lead summary of a Wikipedia article by title, with a specific verb and resource. It distinguishes from sibling tools by recommending wiki.search first.

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?

Explicitly instructs to use wiki.search first to find the exact page key, and mentions no account required, providing clear when-to-use 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 must disclose behavioral traits. It only includes a risk label and vague action. It does not specify whether emails are marked as read, what 'recent' means, or any authentication or rate limit context.

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

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

The description is a single sentence, but includes a non-essential bracket label. It is front-loaded with the main action, though could be slightly more structured without the label.

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 an output schema, the description should explain what 'recent' entails or the format of returned emails. It does not provide enough context for an AI agent to fully understand what 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?

Schema description coverage is 100%, so baseline is 3. The description adds no new meaning beyond the parameter's own description of defaulting to INBOX. The tool description itself doesn't elaborate on the label parameter.

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

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

The description clearly states the verb 'Read' and the resource 'recent emails from the Gmail inbox'. It distinguishes from sibling tools like 'google_workspace__mail_search' by focusing on reading rather than searching, 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 guidance on when to use this tool vs alternatives. The description does not mention when not to use it, nor does it suggest alternatives like 'google_workspace__mail_search' for more specific queries.

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

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

No annotations exist, so the description must carry the full burden of behavioral disclosure. It only mentions a risk level ('risk:low') but does not explain what happens when no slots are found, how time zones are handled, or any other operational traits.

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, consisting of a single sentence. While it efficiently conveys the core purpose, it includes a non-standard risk tag that could be omitted. For a simple tool, this level of conciseness is acceptable.

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

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

With no output schema, the description should explain what the tool returns, but it does not mention the format of the results (e.g., list of time slots with start/end times). It also omits important context like time zone handling or maximum search window.

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

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

Schema description coverage is 100%, with all three parameters already having clear descriptions. The tool description adds no additional semantic value beyond what the schema provides.

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

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

The description clearly states the action (find) and resource (open time slots within a date range in Google Calendar), making the tool's purpose immediately understandable. No siblings have similar functionality, so differentiation is unnecessary.

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 over alternatives, nor does it mention any prerequisites or limitations. An agent would have to infer usage context from the tool's 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?

With no annotations, the description carries the full burden. It only states 'risk:low' in the prefix and 'governed by Duvera', which adds minimal behavioral insight. No details on side effects, authentication needs, rate limits, or return 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 very concise, one line with a structured prefix. It wastes no words, though it could benefit from a slightly more structured layout.

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 tool with one string parameter and no output schema, the description is minimally adequate. It lacks details about return format, query syntax support (e.g., Gmail search operators), or any limitations, leaving gaps 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?

The input schema covers 100% of the single parameter with a clear example, so the description adds no additional meaning. Baseline 3 is appropriate as the schema already documents the parameter well.

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 mail via Gmail, using the verb 'Search' and resource 'Mail'. However, it does not differentiate from sibling tools like gmail__mail_read or microsoft365__mail_search, relying solely on the name for 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 is provided on when to use this tool versus alternatives. The mention of 'governed by Duvera' is vague and does not help the agent decide 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?

No annotations are provided, and the description does not disclose behavioral traits such as read-only nature, authentication requirements, rate limits, or potential side effects. The prefix '[grubhub · risk:low]' hints at low risk but is non-standard and insufficient.

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, very concise. However, it includes a non-standard bracket prefix that adds noise. Front-loaded with the core 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?

No output schema is provided, and the description does not explain what the response contains (e.g., status text, ETA, timestamps). For a tracking tool, this leaves ambiguity about the return format. The description is minimal for the complexity.

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

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

Schema coverage is 100% for the single parameter order_id, which is already described in the schema. The description adds no additional meaning beyond repeating the resource domain. Baseline 3 due to high schema coverage.

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

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

The description states 'Check the live status and ETA of a Grubhub order', which is a specific verb+resource. It clearly indicates the function but does not differentiate from sibling tracking tools for other services like amazon__package_track.

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 does not mention prerequisites, context, or exclude usage 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?

With no annotations, the description fully discloses behavioral traits: it notes 'risk:low', that no account or API key is required, and that the endpoint is open and unmetered. This provides confidence in safety and access constraints.

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, with a single sentence that front-loads the risk label and directly states the action. Every phrase is necessary and informative, with 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 the tool has no parameters and no output schema, the description adequately covers what it does and what the response looks like. It mentions the open, unmetered nature, which addresses potential concerns. Minor missing info on error scenarios, but acceptable for such a simple 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?

Since there are no parameters, the description adds value by explaining the output format (array of item IDs) and how to use them (resolve via item endpoint). This compensates for the empty schema, exceeding the baseline of 3 for 100% schema coverage.

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

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

The description clearly states the tool's purpose: fetching the current list of top-story IDs from Hacker News. It specifies the verb ('Fetch'), the resource ('top-story ids on Hacker News'), and the result type ('array of item ids'), making it distinct from sibling tools which cover different services.

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 effectively guides usage by stating that the results are IDs that require further resolution via the item endpoint. It does not explicitly contrast with siblings, but given the tool's simple nature, the clarity of purpose and subsequent resolution hint is sufficient.

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 of behavioral disclosure. It only includes a risk:low tag but does not explain return format, pagination, authentication needs, or side effects. For a search tool, minimal behavioral context is 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 exceptionally concise, containing only one sentence. Every part (risk tag, action, resource) is necessary. 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?

For a simple search tool with no output schema, the description provides the core purpose but lacks detail on return values, search scoping, or behavior. It is minimally viable but could be improved with more 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?

The input schema has 100% coverage, with both parameters (query, store) already described adequately. The description adds no additional semantic meaning beyond the schema. Baseline 3 is appropriate when schema covers everything.

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

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

The description clearly specifies the action ('Search') and resource ('grocery items and stores in the Instacart app'). It uses a specific verb and resource, making the tool's purpose immediately clear. No sibling tools overlap with this domain, so differentiation is not required.

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 does not provide any guidance on when to use this tool versus alternatives or when to avoid it. While no sibling tools are similar, the lack of usage context still leaves ambiguity for an AI agent unfamiliar with the tool's role.

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 does not disclose behavioral traits such as permission requirements, error handling, or side effects (e.g., opening Apple Maps). The only extra context is a risk label in brackets, which is insufficient.

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 core purpose. No unnecessary words, though it could be slightly more informative 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?

Given the tool has only 2 parameters and no output schema, the description is complete enough for a simple action. However, it lacks details about expected behavior (e.g., whether it opens an app or sends a share sheet) and does not describe the return value.

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 both parameters have descriptive titles in the schema. The description adds no additional meaning beyond what is already in the input schema, so a 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 the action (share), the resource (estimated time of arrival), and the source (Apple Maps). It is specific and easily distinguishes from sibling tools, which cover unrelated 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?

No guidance on when to use this tool versus alternatives, nor are there any exclusions or prerequisites mentioned. For example, it does not indicate that an active trip must be in progress or what happens if the contact is not found.

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, and the description does not disclose any behavioral traits such as read-only nature, authentication requirements, rate limits, or side effects. The '[risk:low]' tag is present but undefined. The description fails to inform the agent about the behavior 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?

The description is extremely short (one sentence), but it lacks substance. While brevity can be a virtue, here it comes at the cost of missing critical information. The sentence does not provide enough context for an agent to use the tool effectively.

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 low complexity (1 optional parameter), the description should explain what the tool returns and any important context. It does not mention return format, pagination, or whether it lists all calendars or events in a calendar. Incomplete for the agent to understand the tool's full capability.

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% (one parameter described). The description adds no additional meaning beyond the schema's description 'Date range, e.g. 'this week'.' The schema already provides this, so the description does not enhance understanding of parameter syntax or constraints.

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 'List Calendar' which identifies the resource (calendar) and action (list), but it is ambiguous whether it lists calendar events or the calendar itself. The parameter 'range' suggests event listing, but not explicitly. There is no differentiation from sibling tools like googlecalendar__availability_find.

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. No mention of prerequisites, context, or exclusions. Sibling tools include other calendar-related tools like googlecalendar__availability_find and various Microsoft 365 tools, but the description provides no selection criteria.

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 mentions 'risk:low' but lacks details on authentication, return format, or scope. The description is insufficient for an agent to fully understand the tool's 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 concise, front-loaded with the name and risk level, and avoids unnecessary words. However, it sacrifices some completeness for brevity.

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 complexity (one parameter, no output schema), the description still lacks context on return values, authentication, and scope of search. It is incomplete for an agent to use effectively.

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 a clear parameter description and example. The tool description adds no extra meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states the purpose: search mail via Outlook/Exchange. It uses a specific verb and resource. However, it does not differentiate from sibling tools like google_workspace__mail_search, though the name provides some 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 is provided on when to use this tool versus alternatives, prerequisites, or context. The description is minimal and offers no selection criteria.

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 includes a '[risk:low]' tag, indicating low risk, but does not explicitly state that the tool is read-only or disclose other behavioral traits. With no annotations provided, the description partially compensates but lacks details like return format or permissions.

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 efficiently conveys purpose and risk level. No unnecessary words; every part is useful.

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 search tool with one parameter and no output schema, the description covers the core functionality. However, it does not mention what the tool returns (e.g., list of matching notes) or any limitations, leaving some 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 coverage is 100%, and the description adds no new meaning beyond the schema's 'Search query string' for the query parameter. The tool description essentially restates the purpose, so no extra value for parameters.

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

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

Description clearly states the tool's function: search pages and notes in Notion by query. It uses a specific verb ('search') and resource ('pages and notes in Notion'), setting it apart from sibling tools like obsidian__notes_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 on when to use this tool versus alternatives (e.g., other search tools). The description lacks context for when-not to use or suggestions for more specific 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?

The description includes a risk label '[obsidian · risk:low]' indicating a level of safety, and the verb 'search' implies a read-only operation. However, no other behavioral traits (e.g., required permissions, result format, limitations) are disclosed. Without annotations, the description carries the full burden and only partially addresses it.

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) and front-loaded with the risk label. It is appropriate for a simple tool, though could be slightly more informative 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?

Given the tool's simplicity (one parameter, no output schema), the description minimally covers functionality. However, it omits details like whether results are full notes or snippets, which would aid 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 coverage is 100% with the query parameter described as 'Search query string'. The description adds no additional meaning beyond what the schema already provides, merely restating 'by query'.

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

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

The description clearly specifies the verb 'search', the resource 'notes in an Obsidian vault', and the mechanism 'by query'. It effectively distinguishes itself from sibling search tools (e.g., wiki search, tweet search) by naming the specific source.

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 vs alternatives, nor any when-not-to-use conditions. The description simply states the action without 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 the full burden. It indicates 'risk:low' but does not mention if the tool is read-only, any rate limits, data freshness, or whether it requires authentication. Behavioral traits beyond immediate purpose are absent.

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, using a single sentence with a risk tag. It front-loads the key information (current weather data, parameters, source). However, it could be restructured to start with an action verb like 'Retrieves' for clarity.

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

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

For a simple tool with two parameters and no output schema, the description is minimal. It specifies what data is returned (temperature, conditions, humidity, wind) but lacks details on units, response format, or any constraints. This leaves an agent insufficiently informed about what to expect from the output.

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 clear descriptions for both latitude and longitude parameters (100% coverage). The tool description adds no additional semantic meaning beyond what the schema states, 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 the tool retrieves current temperature, conditions, humidity, and wind for a given latitude/longitude from Open-Meteo. It is specific about what weather parameters are returned, but does not explicitly distinguish from similar sibling tools like duvera__weather_current.

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. There are multiple weather-related sibling tools (e.g., duvera__weather_current, duvera__weather_air_quality), but no comparisons or exclusion criteria are given.

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

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

With no annotations, the description carries full burden. It mentions 'live ADS-B feed' (indicating real-time, read-only) and includes a risk label. However, it omits important behavioral details like rate limits, authentication requirements, data freshness guarantees, or result format (e.g., pagination, max aircraft count). Basic transparency 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?

Single sentence with a prefix is extremely concise. Front-loads essential info (tool name, risk level). Every word serves a purpose; no waste. Ideal structure for an MCP description.

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 list tool with four well-documented parameters in the schema, the description is adequate but leaves out what the output contains (e.g., flight objects with fields) and any constraints (e.g., maximum bounding box size, refresh interval). Could be more complete with a brief output hint or usage note.

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 covers all 4 parameters with descriptions including example values (e.g., 'North edge of the box — maximum latitude (e.g. 40.9 for NYC).'). The description adds no additional semantic value beyond what the schema provides, just restates the box concept. Baseline 3 is appropriate given full schema coverage.

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

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

Description clearly states verb 'list', resource 'aircraft', and scope 'within a latitude/longitude box' from a specific source ('OpenSky's live ADS-B feed'). This uniquely identifies the tool's purpose and distinguishes it from all sibling tools, which cover unrelated domains like package tracking, weather, or finance.

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

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

The description implies the tool is for live aircraft in a geographic area but provides no explicit when-to-use or when-not-to-use guidance. However, given that sibling tools are all unrelated and no similar aircraft tracking tool exists, the context is clear enough. Lacks explicit exclusions or alternatives but sufficient for an agent.

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 full burden. It states the query is read-only and risk:low, but lacks details on error handling, connection behavior, result format, or authentication requirements. For a database tool, these are important missing aspects.

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—one sentence plus a lightweight tag—with no filler. It front-loads the tag and immediately states the tool's action, making it efficient for an agent to parse.

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 (2 required parameters, no output schema), the description is mostly complete but could benefit from noting that queries must be SELECT statements or that results are returned as text. Without annotations, some behavioral gaps remain.

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?

Both parameters have schema descriptions that cover their purpose (query is a read-only SQL, database is the target name). The tool description adds no additional meaning beyond the schema, so baseline of 3 is appropriate with high schema coverage.

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

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

The description clearly states the tool executes read-only SQL queries on a Postgres database, providing a specific verb (Execute), resource (read-only SQL query), and target (Postgres database). This distinctively separates it from sibling tools which handle different data sources like Apple Health, Bluesky, etc.

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 does not provide explicit guidance on when to use this tool versus its alternatives. It only describes the action, leaving the agent to infer based on the tool's name and siblings. Adding context like 'Use when you need to retrieve data from Postgres without modifications' would improve clarity.

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 carry the behavioral transparency burden. It only includes a risk label '[shazam · risk:low]' but fails to disclose important details such as whether microphone access is needed, what happens if no song is playing, or the format of the result.

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

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

The description is short and to the point, with no wasted words. It efficiently conveys the core purpose. However, it could be slightly more structured by separating the risk indicator from the main description.

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, the description should explain what the tool returns, but it does not. It also lacks any mention of error scenarios or prerequisites. For a simple tool, some additional context about the response format or failure conditions would improve completeness.

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

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

The input schema has one optional parameter with a clear description ('How long to listen before identifying, in milliseconds'). Since schema coverage is 100%, the description adds no additional parameter meaning, meeting the baseline expectation.

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: 'Identify the song currently playing using Shazam'. It uses a specific verb ('Identify') and resource ('song'), and the context is unambiguous. Among sibling tools, none deal with audio identification, so it stands out.

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 when a song is playing, but provides no explicit guidance on when to use or when not to use this tool versus alternatives. There are no exclusion criteria or context conditions mentioned beyond the risk label.

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 but only mentions 'risk:low'. It does not disclose behavioral traits such as authentication requirements, scope of channels searched, or definition of 'recent'. This leaves significant 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 very concise (one sentence) and front-loaded with the risk level. However, it could benefit from slight expansion without sacrificing brevity. It is not 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?

For a simple tool with one parameter and no output schema, the description gives a minimal viable understanding. But it lacks details like the meaning of 'recent' and channel visibility, which could affect correct 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 coverage is 100% with one parameter 'query' described as 'Search query string'. The description adds no further detail about the parameter (e.g., format, examples, constraints), so it meets the baseline but adds no 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 action ('Search') and resource ('recent messages across Slack channels'), distinguishing it from sibling tools that search other domains. However, the term 'recent' is vague and lacks time specificity.

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 over alternatives (e.g., other search tools). There is no mention of 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 provided, the description carries the full burden but only states basic purpose. It does not disclose whether the tool is read-only, any authentication requirements, rate limits, or potential 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 very concise, front-loading the airline and risk level. It is efficient, though slightly under-informative—every sentence earns its place.

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

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

There is no output schema, and the description does not explain what the tool returns (e.g., delays, gate numbers). Given the simplicity of the tool, but lacking annotations and return value info, completeness is low.

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

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

Schema description coverage is 100%; both parameters have descriptions in the schema. The tool description does not add any additional meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description states 'Check the status of a Southwest flight', clearly identifying the verb and resource. It distinguishes from siblings like united__flight_status by naming the airline, but does not elaborate on what specific status information is provided.

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. Siblings include other airline flight status tools, but the description does not indicate scenarios where this tool is preferred or when other tools might be better suited.

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 must fully disclose behavioral traits. It only mentions 'risk:low' and 'read recent messages' but does not specify whether messages are marked as read, how many are returned, pagination, authentication needs, or rate limits. This is insufficient for an agent to understand 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 extremely concise at one sentence, with a useful risk tag. Every word earns its place, though it could include more behavioral context without becoming verbose. The structure is front-loaded with the risk tag and tool name.

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 (one required parameter, no output schema), the description gives the minimum viable context: it reads recent messages. However, it omits important details like whether messages are returned in chronological order, if read receipts are sent, or the maximum time window considered. For a simple tool, it is adequate but could be more complete.

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

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

The input schema has 100% coverage for the single parameter 'chat', which is well-described. The description adds no additional meaning beyond the schema, so the baseline score of 3 is appropriate. No extra clarity or constraints are provided.

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

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

The description clearly states it reads recent messages from a Telegram chat, identifying the specific resource and action. It effectively distinguishes from sibling tools like slack__message_search by focusing on 'read' vs 'search'. However, it lacks specifics on what constitutes 'recent' (e.g., time window or count).

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 slack__message_search or gmail__mail_read. There is no mention of prerequisites, exclusions, or context for using this tool over others, leaving the agent without decision support.

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 behaviors. It mentions data handling ('Duvera never stores it') and implies read-only operation ('search'), but does not explicitly state absence of side effects, rate limits, or pagination behavior. Adequate but could be more explicit.

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?

Three sentences, front-loaded with the core purpose, followed by essential authentication info. No fluff or redundancy. Each sentence serves a clear purpose.

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

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

Given no output schema, the description could explain what the response contains (list of tweets, metadata). It covers authentication and API version but omits return format, pagination, or rate limits. Adequate for a simple 2-param tool 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%, so baseline is 3. The description mentions query types (keyword, hashtag, phrase) but does not add significant new meaning beyond the schema's parameter descriptions, which already include operator examples and default 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 action ('Search for recent tweets') and the resource ('Twitter v2 API'). It mentions specific query types (keyword, hashtag, phrase) and the platform name, which distinguishes it from sibling tools like duvera__wiki_search or duvera__news_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?

The description provides context on authentication (Bearer Token, header, where to get one) and implies usage for searching recent tweets. No explicit when-to-use vs alternatives, but no direct alternative Twitter tools exist among siblings, so the guidance is sufficient.

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 carry the burden. It implies a read-only operation ('estimate'), but lacks details on auth requirements, rate limits, or error handling. For a simple fare estimation, the minimal info is acceptable.

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 with no redundant information. The risk tag is minimal and does not detract from clarity.

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

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

The description is adequate for a simple tool with fully documented parameters, but it does not explain return values or provide examples. Given the lack of output schema, a brief note on expected result (e.g., estimated fare amount) would improve completeness.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds no additional parameter-level information beyond what the schema already provides.

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

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

The description clearly states the verb 'Estimate' and the resource 'fare for a trip in the Uber app', making the tool's purpose immediately understandable. It distinguishes itself from sibling tools which cover entirely different 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 clearly implies usage: when a fare estimate for an Uber trip is needed. Although no explicit alternatives or exclusions are given, the tool is unique among siblings, so the context is sufficient.

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 provided; description only notes 'risk:low' without explaining what it means. No mention of read-only, authentication, or data freshness. Minimal behavioral disclosure.

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 is concise and front-loaded with risk tag. However, it could be more informative 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?

No output schema and no description of return values. Lacks context on what status info is provided (delays, gates, etc.). Insufficient for a flight status 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 both parameters. Description adds no extra meaning beyond schema, so baseline score of 3 applies.

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

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

Verb 'check status' clearly identifies action, and 'United flight' specifies the resource. Siblings like 'southwest__flight_status' and 'delta__boardingpass_show' show clear differentiation by airline and function.

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 use for United flight status only, but no explicit when-to-use, alternatives, or exclusions. Agent must infer from name and 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 are provided, so the description bears full burden. It discloses that no money leaves the account (a key safety behavior) and includes a risk label. However, it lacks details on auth, limits, success/failure outcomes, or cancellation behavior. Adequate but minimal.

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 that front-loads the tool name and risk label, then concisely states the action. No wasted words; every part is informative.

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 simplicity of the tool (3 parameters, no output schema, no annotations), the description covers the essential distinction (request vs. send) and the risk level. It is complete enough for an AI to understand usage, though additional context like recipient prerequisites would be helpful. Score 4 for adequate 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 coverage is 100% with descriptions for all three parameters. The description adds no further meaning beyond the schema; it repeats recipient and amount in the main text but without extra nuance. 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 the verb 'Request a payment' and the resource 'from a contact via Venmo', and adds the clarifying note 'no money leaves your account' which differentiates it from a send tool. This is specific and distinct, even though no payment sibling is present.

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 requesting payment via Venmo. It does not explicitly state when not to use or provide alternatives, but the context is clear given the tool name and description. With no confusing siblings, this is adequate.

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 only behavioral hint is 'risk:low' in the prefix. No annotations provided. Description does not disclose what happens on missing passes, auth requirements, or whether it modifies anything.

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, efficient. The risk tag in brackets adds useful metadata. Could include a brief note on output behavior.

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 description doesn't explain what happens when pass is shown (e.g., displayed on device, returns data). Lacks handling for multiple matches or 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 coverage is 100% with basic descriptions for both parameters. The tool description adds no additional meaning beyond the schema.

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

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

The description clearly states the verb 'Pull up' and resource 'boarding pass stored in Apple Wallet'. It distinguishes from sibling 'delta__boardingpass_show' by specifying 'Apple Wallet', but could be more explicit about it being a general wallet 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 on when to use this tool versus alternatives like delta__boardingpass_show. No context about prerequisites 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.