terminal

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

With no annotations, the description carries the burden of disclosure. It does mention the cost model ('paid, $0.002/req or pass') and mentions 'episode citations' as part of the output. However, it does not clarify whether this is read-only, what 'pass' means, or any other side effects or prerequisites.

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 uses a clear 'Args' section. However, the first sentence is cryptic and packed with jargon ('x402/MPP/USDC'), which may confuse agents. Still, every sentence adds some 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?

There is no output schema and no annotations, so the description must explain return values and context. It mentions 'episode citations' but does not describe the structure of the brief or what 'pass' means. The tool appears to be a niche payments ecosystem brief, but important details are missing.

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

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

The description explicitly explains the 'limit' parameter with a range (1-50), which is not present in the schema (schema only has default 20). This adds meaningful value beyond the input schema, even though the schema has only one 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 says 'Agentic-payments ecosystem brief' but lacks a specific verb like 'get' or 'list'. It mentions x402/MPP/USDC events, which suggests content, but doesn't clearly state what action the tool performs. It does not distinguish from sibling tools like agentpay_latest.

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

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

No explicit guidance on when to use this tool versus alternatives such as agentpay_latest or other search tools. The mention of 'paid' hints at a different access tier, but no when-to-use or when-not-to-use instructions are provided.

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

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It mentions a cost per request and an ambiguous 'or pass' condition, but does not clarify whether the operation is read-only, what constitutes a 'pass', or the response format. The description is too shallow for a tool that has side effects (payment) and unclear semantics.

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 includes the core purpose and a notable cost condition. Every word is informative, with no fluff or repetition, and it is front-loaded with the main purpose.

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

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

Given the lack of an output schema and annotations, the description provides only minimal context. It states what is returned (a single event) and the cost, but does not explain the meaning of 'pass', the structure of an event, or any edge cases (e.g., no events available). While the tool is simple, the description leaves gaps that could affect correct usage.

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

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

The tool has zero parameters, so there is no parameter-level information to add. The baseline score of 4 applies, and the description does not need to elaborate on parameters since none exist.

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

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

The description clearly identifies the tool as returning the single most recent agentic-payments event, with a specific scope (most recent) and resource (agentic-payments event). It distinguishes itself from sibling tools like agentpay by the 'latest' qualifier, making its purpose unambiguous.

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

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

The description provides no guidance on when to use this tool over alternatives such as agentpay or funding_latest. It does not mention any prerequisites, exclusions, or contextual cues for choosing 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?

The description adds a cost-related behavioral note ('paid, $0.002/req or pass') and specifies the limit range, which is useful. However, with no annotations, it does not disclose the return format, pagination, or the nature of the operation beyond being a metrics lookup. It provides some context but not 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, with a clear first sentence conveying the purpose and pricing, followed by a bulleted parameter list. No redundant information is present, and the structure front-loads the key message.

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 only two parameters and no output schema, the description covers purpose and parameters well. However, it lacks usage context, such as when to prefer capex over capex_summary, and does not describe the response structure, leaving the agent to infer behavior. It is moderately complete but not comprehensive.

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

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

The schema has zero description coverage for parameters, but the description fully compensates by explaining both parameters with concrete examples ('cloud_growth', 'memory_price', 'capital_raise') and constraints ('1-50'). This adds significant meaning beyond the bare 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 domain (AI-capex / model-economy metrics) and enumerates specific metric families, making the purpose understandable. However, it lacks an explicit verb like 'get' or 'list' and does not directly distinguish itself from the sibling tool 'capex_summary'.

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 about when to use this tool versus alternatives. The description only explains the parameters, with no mention of suitable scenarios, prerequisites, or exclusions. This is a clear gap given the large sibling toolset.

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 carry the full behavioral burden. It adds a billing detail ('paid, $0.001/req or pass') but the phrase is ambiguous and does not clarify whether the tool is read-only, whether 'pass' means free/skip, or any other runtime behavior. The cost disclosure is not enough to provide clear transparency.

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

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

The description is a single focused sentence that front-loads the main purpose. The parenthetical billing phrase adds information but is somewhat cryptic; overall it is appropriately concise with no filler.

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

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

For a simple 0-parameter summary tool, the description gives the core purpose but leaves ambiguity around the billing parenthetical and does not describe the return format beyond 'metric families'. A bit more explanation would make it complete, but it 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?

The tool has zero parameters, so the schema is trivially complete. The description adds no parameter details, but none are needed; the baseline for 0-param tools is 4.

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

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

The description clearly identifies the tool as providing metric families from the capex tracker. It names the specific resource ('capex tracker') and the content ('metric families'), and the term 'summary' distinguishes it from the sibling 'capex' tool, though it lacks an explicit verb like 'lists' or 'returns'.

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 about when to use this tool versus alternatives. The description does not mention the sibling 'capex' tool or any exclusions, leaving the usage context only implied by the word 'summary'.

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

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

No annotations are provided, so the description carries the full burden. It discloses the paid nature ($0.002/req) and a limit range, which is useful, but it does not state whether the operation is read-only, what the return structure looks like, how 'in-date' is determined, or what happens when the limit is exceeded. The phrase 'or pass' is ambiguous and adds no clarity.

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 brief and front-loaded with the core purpose. The 'Args' section is efficiently formatted. However, the phrase 'or pass' is unexplained and slightly confusing, and the cost note feels placementally odd, adding minor noise.

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

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

For a simple single-parameter list tool, the description is somewhat adequate, but it lacks any mention of what the returned catalogue objects contain, whether there is pagination, or any authentication requirements. The paid pricing note is useful but the overall context feels incomplete for an agent to reliably invoke and interpret results without additional assumptions.

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 explicitly documents the 'limit' parameter with a range (1-50) and meaning ('max catalogues to return'), which goes beyond the schema's bare type/default. This is significant value-add since schema description coverage is effectively low, and it compensates 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 states it returns 'in-date retailer catalogues from the PriceMate corpus', which is a clear resource with a specific scope. The verb is implicit but the plural 'catalogues' indicates a list/retrieval operation. It does not explicitly differentiate from sibling tools like 'deals' or 'deals_hot', but the corpus and 'in-date' qualifier provide 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 the many sibling tools. There is no mention of alternatives, prerequisites, or exclusions. The only contextual hint is 'paid', which may imply cost considerations but does not help with 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?

With no annotations, the description carries full burden. It adds cost and data scope but does not disclose response format, pagination behavior, error handling, or any side effects. The phrase 'or pass' is unclear and reduces 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 well-structured with a concise overview and an Args list. Every sentence contributes value, but the 'or pass' phrase is confusing and detracts from clarity, preventing a perfect score.

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 two-parameter query tool, the description covers the essential scope: data source, countries, categories, currency, and cost. However, it lacks any mention of result sorting, output format, or how it relates to deals_hot/deals_search, leaving advisory 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?

The description adds meaningful parameter details beyond the bare schema: category is illustrated with examples (Electronics, Groceries, Appliances) and limit is given a range (1-100). Since schema descriptions are absent, this compensates well for the missing schema-level documentation.

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

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

Description clearly states it returns live SADC deals from a specific catalogue, with geographic scope and product categories. It distinguishes the tool as a general deals listing but does not explicitly contrast with sibling tools deals_hot or deals_search, so it misses full 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?

No when-to-use guidance or alternatives are provided. The description does not tell the agent when to choose this over deals_hot or deals_search, and mentions cost ambiguously with 'or pass' without explaining the choice.

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 'paid, $0.001/req or pass' (cost hint) and that it returns products sorted by savings, but it does not explicitly state whether the operation is read-only, describe pagination, error handling, or the meaning of 'pass'. This is insufficient for a tool with no annotation 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 concise, comprising two sentences that convey the core purpose and output. The phrase 'paid, $0.001/req or pass' is cryptic but does not add excessive length. It is efficiently structured and front-loaded with the key 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?

With only one parameter and no output schema, the description should clarify return fields, the meaning of 'savings', and terms like 'in-date' and 'SADC'. It does not, leaving gaps about the response structure and criteria. The cost note is ambiguous, and the tool's behavior is only partially explained.

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

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

Schema description coverage is 0%, so the description must compensate. It does not mention the 'limit' parameter at all. While the schema shows an integer with default 10, the description provides no additional meaning about what limit controls (e.g., number of results), leaving the agent to infer.

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 products with the biggest absolute price drops among in-date SADC products, sorted by savings. This specific verb+resource+scope distinguishes it from sibling tools like deals and deals_search, which likely cover general deals or search functionality.

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

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

The description provides clear context for when to use this tool: when looking for hot deals (biggest absolute price drops) among in-date SADC products. It does not explicitly mention alternatives or exclusions, but the specificity of 'biggest absolute price drops' and 'in-date SADC' strongly implies its use case.

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

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

The description discloses cost constraints and parameter validations (minimum 2-char query, 1-50 limit), which are not present in annotations. However, it does not describe return format, error behavior, or rate limits, leaving some important behavioral aspects undisclosed.

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?

At two short sentences plus a compact Args section, the description is tightly written and front-loads the key purpose and cost. No filler 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?

The description covers the tool's purpose, parameters, and constraints, but lacks a description of the return content/structure. Since no output schema is provided, this omission leaves the agent to infer what the response contains.

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 provides no parameter descriptions, but the description compensates by explaining q as a search term with examples and a minimum length, and limit with a range (1-50) and default via schema. This fully clarifies the 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?

The description begins with 'Search in-date SADC products by name or brand,' which names a specific action (search), resource (products), and scope (SADC, in-date). This distinguishes it from sibling tools like deals and deals_hot, which likely list or highlight deals.

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

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

The examples and the qualifier 'in-date SADC products' imply when the tool is useful, but the description does not explicitly compare it to alternatives or state exclusions. The cost note ('paid, $0.005/req or pass') suggests a consideration but not a usage rule.

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 adds useful behavioral context: the data source (podcast corpus), the paid nature ($0.005/req), and the limit range (1-50). However, it does not describe the return format, default behavior, or the meaning of 'pass', leaving gaps in expected 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 brief and to the point, with no filler. It efficiently includes the resource, cost, and limit semantics. The phrase 'or pass' is slightly ambiguous, but the overall structure is clean and front-loaded.

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

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

For a simple one-parameter tool, the description covers core purpose, source, cost, and limit semantics. However, with no output schema, the absence of return-value details leaves uncertainty, and the lack of sibling guidance reduces overall 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 schema only defines 'limit' as an integer with default 20, and description coverage is 0%. The description compensates by explaining 'limit: max events (1-50)', which clarifies both meaning and constraints. This is adequate for the single 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 identifies the tool as providing Funding/IPO events mined from the podcast corpus, making the resource and scope apparent. However, it lacks a concrete verb like 'list' or 'get' and does not distinguish this tool from its siblings (funding_latest, funding_search), so it cannot achieve a perfect score.

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

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

No usage guidance is provided. The description does not explain when to use this tool over funding_latest or funding_search, nor does it mention any alternatives or exclusions. The only extra information is a cost note, which is not usage direction.

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 behavioral disclosure. It does disclose the paid nature and 'or pass' behavior, but 'pass' is undefined, and there is no mention of return format, empty results, or whether the event is a full article or summary. The cost disclosure is useful but incomplete.

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

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

The description is a single sentence that front-loads the core purpose and includes pricing information. Every word earns its place, and it is appropriately compact for a zero-parameter tool.

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 (no params, no output schema), the description covers the essential resource and cost. However, the ambiguous 'or pass' and lack of return-value details leave some gaps, making it minimally viable rather than 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?

The tool has zero parameters, so the baseline of 4 applies. The description adds no parameter-specific meaning, but none is needed because the schema is empty and fully covered.

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 identifies the resource as 'the single most recent funding/IPO event,' which clearly scopes it as a latest-event retrieval. Although it lacks an explicit verb, it distinguishes itself from siblings like funding and funding_search through the 'single most recent' qualifier.

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 when-to-use or when-not-to-use guidance is given. The phrase 'or pass' hints at a conditional behavior, but there is no contrast with alternatives like funding or funding_search, and no context for when this tool should be chosen over others.

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

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

With no annotations, the description carries the full burden. It discloses the paid nature ($0.003/req or pass) and that 'company' is a fragment match, adding useful context. However, it omits return structure, error behaviors, and any side effects, leaving significant gaps.

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

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

The description is compact and front-loaded with the core purpose, followed by a simple args list. The pricing note is relevant and the structure is scannable. Every sentence 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 two-parameter search, the description covers the primary function and parameters, but it does not specify the output format or fields of returned events, and there is no output schema to compensate. It also lacks details on pagination or ordering.

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

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

Schema description coverage is 0%, but the description fully explains both parameters: 'company' as a name fragment with example values, and 'limit' as max events with an explicit range (1-20). This completely compensates for the schema's lack of descriptions.

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

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

The description 'Funding events by company name' clearly states the tool's function: retrieving funding events filtered by a company. This distinguishes it from sibling tools like 'funding' and 'funding_latest', which likely list all events. The verb is implicit but unambiguous.

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

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

The phrase 'by company name' implies usage when a specific company's funding events are needed, but it does not explicitly state alternatives or when not to use the tool. No usage guidance beyond this implication is provided.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It adds key context about cost ('paid, $0.01/req or pass') and licensing ('licensed'), which are important for agent decision-making. However, it does not describe error behavior, rate limits, or the exact structure of the metadata, leaving gaps in transparency.

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

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

The description is exceptionally concise, using two short sentences plus an Args section. Key details (full article, markdown, cost) are front-loaded, and every sentence earns its place. No fluff or redundancy.

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

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

For a simple single-parameter tool with no output schema, the description covers the essential aspects: what is returned, cost, and how to obtain the slug. The only notable omission is specifying what 'metadata' includes, but this does not hinder correct invocation. Overall, it is adequately complete for the tool's simplicity.

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

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

The schema has zero description coverage for 'slug', but the description compensates by explaining that it is 'the article slug from list_articles'. This adds meaningful provenance and usage context beyond the bare schema property. It does not detail format or examples, but it is sufficient for a simple string identifier.

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 'One full licensed Monexus article as markdown plus metadata', specifying the resource (article), format (markdown), and content (full article with metadata). This distinguishes it from siblings like list_articles, which likely returns summaries, and get_context/get_thread, which target different resources.

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

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

The description implies usage by instructing that the slug comes 'from list_articles', suggesting a workflow where list_articles is called first. However, it does not explicitly state when to prefer this tool over alternatives like get_context or search_wire, nor does it provide exclusions or conditional usage guidance.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It discloses a critical operational trait: the tool is paid ($0.005/req or pass). It also implies a read-only nature via 'get' and describes output content. However, it does not mention error handling, response format beyond content components, or any access restrictions.

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

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

The description is two sentences long, front-loaded with the purpose, and includes a concise Args section. Every sentence contributes value—the first defines the tool, the second explains the parameter and cost. 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 single-parameter read tool with no output schema, the description is reasonably complete: it states what the tool does, what the parameter is, and a caveat about cost. It lacks details on return format and error behavior, but given the low complexity, these are not critical 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?

The input schema has no parameter descriptions (0% coverage), but the tool description fully compensates by explaining item_id as 'the thread/item id to build the context brief for'. This adds clear semantic meaning beyond the schema's bare type/title, making the parameter's role immediately understandable.

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 produces a 'Full context brief for a thread' with components 'background, timeline and significance', distinguishing it from sibling tools like get_thread which likely return raw thread data. The verb 'get' combined with the specific resource and output scope makes the purpose unambiguous.

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

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

Usage is implied by the description's focus on context briefs, suggesting it is meant for retrieving synthesized background and timeline rather than raw thread details. However, there is no explicit 'when to use' or comparison with alternatives like get_thread, leaving room for ambiguity.

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

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

With no annotations, the description carries the full burden. It discloses the paid nature ($0.002/req or pass) and the output scope (all wire items), but does not mention error behavior, authorization requirements, or rate limits. The 'or pass' wording is vague, adding some uncertainty rather than 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, with the core action in the first sentence and a clear Args section for the parameter. No fluff or redundancy; every word earns its place.

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

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

For a simple single-parameter get tool, the description covers the essential purpose, parameter source, and return content (all wire items). It does not describe a response schema, but given the tool's simplicity, the description is reasonably complete. Minor gaps remain around error cases and output structure details.

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

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

The schema only names the parameter with minimal title, but the description fully compensates by explaining thread_id is the id returned by list_threads or search_wire. This gives the agent actionable guidance on how to obtain a valid value, adding significant 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 tool retrieves a single event thread with all its wire items, using a specific verb (get) and resource (thread). It distinguishes itself from sibling tools like get_article, get_context, and list_threads by focusing on thread-specific wire items.

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

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

The description provides usage context by stating the thread_id should come from list_threads or search_wire, indicating this tool is intended for fetching a specific thread after listing/searching. It does not explicitly name alternatives to avoid, but the guidance on where to obtain the ID implies the correct workflow.

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

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

With no annotations, the description carries the full burden. It discloses cost ($0.002/req or pass), pagination via the 'before' cursor, and optional filters. However, it does not describe default ordering, return format, authentication requirements, error behavior, or other operational nuances. This is more informative than a bare description but still lacks significant behavioral depth.

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

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

The description is very concise: a single lead sentence plus three short parameter definitions. No wasted words. The most important info (licensed articles, cost) appears first. The parameter list is structured and easy to scan.

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

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

The tool is relatively simple (list with filters and pagination), and the description covers the basic filters and pagination. But with no output schema, it does not describe the shape of returned articles or how ordering works by default. It also omits any info on error handling or rate limits. Given the tool's moderate complexity, the description is adequate but not fully complete.

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

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

The schema has 0% description coverage, so the description must explain parameters. It does explain all three: category (filter), limit (max count), before (pagination cursor with published-before semantics). This adds meaning beyond the schema's bare names, types, defaults. However, the explanations are minimal and do not include examples or constraints like maximum limit 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 identifies the tool as an index of 55,000+ licensed Monexus articles, which matches the 'list' function implied by the name. It distinguishes this from sibling tools like get_article (single article) and search_wire (search), making the purpose specific and unambiguous.

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

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

The description does not explicitly mention when to use this tool versus alternatives such as search_wire or get_article. It implies usage through the list/filter/pagination context, but lacks explicit guidance on when to choose this over browsing categories or searching. The cost/availability note hints at licensing constraints but no clear if-then usage rules.

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 of behavioral disclosure. It usefully adds that the tool is free and needs no key, and that it returns counts and timestamps. However, it does not explicitly state that it is read-only, describe ordering, or mention any rate limits or response envelope.

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

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

The description is one compact, front-loaded sentence. Every part adds value: the resource type, the output highlights, and the access note. There is no filler or redundancy.

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

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

For a zero-parameter list tool with no output schema or annotations, the description covers the key aspects: what the resource is, what fields are shown, and the auth requirement. It could be slightly richer about the exact return shape, but it is sufficient for an agent to invoke correctly.

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

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

The input schema has zero parameters, so there are no parameter semantics to clarify. The description adds the relevant context that no key is needed, which preemptively addresses a possible auth parameter question. With no params, baseline 4 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 identifies the resource as a beat/category scoreboard and mentions what it contains (item counts and latest timestamps). Although it lacks an explicit verb like 'list,' the name and 'scoreboard' make the listing behavior clear. It is distinct from sibling tools that focus on articles, threads, or 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 gives no guidance on when to use this tool versus siblings. The only contextual hint is 'free, no key needed,' which is an access condition, not a usage scenario or exclusion. There are no alternatives named or when-not-to-use instructions.

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

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

With no annotations, the description carries the full burden of disclosing behavior. It adds useful context about the data type ('live event threads', 'developing stories') and mentions a pricing/access policy ('paid, $0.002/req or pass'). However, it does not specify return format, pagination, ordering, authentication needs, or any side effects, leaving significant gaps.

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

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

The description is a single, compressed sentence that packs the core idea and a critical caveat into few words. It is fully front-loaded and every phrase earns its place. However, it is slightly cryptic—especially 'or pass'—which reduces clarity, so it is not a perfect 5.

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

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

For a simple, parameterless list tool, the description conveys the essential topic but leaves ambiguity around 'or pass' and does not describe the return value or any limits. Since there is no output schema, these omissions are noticeable, and the description does not fully stand alone.

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 zero parameters with 100% 'coverage' (trivially). Per guidelines, a 0-parameter tool gets a baseline of 4 because there is nothing to document. The description adds no parameter-related detail, but none is needed.

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

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

The description clearly identifies the resource being listed ('Live event threads') and explains their nature ('wire items clustered into developing stories'), which distinguishes this from sibling tools like get_thread or search_wire. The verb 'list' is not stated in the description, but the tool name supplies it, making the purpose clear enough.

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

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

The description implies this tool is used for accessing live event threads, but provides no explicit guidance on when to choose this over alternatives such as get_thread or search_wire. It does mention a cost/availability caveat ('paid, $0.002/req or pass'), which hints at conditions of use, but there are no clear exclusions or comparisons.

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 behavioral disclosure. It does add value by stating the paid cost ($0.005/req or pass) and the event categories, but it does not describe the return format, pagination behavior, or any permission requirements, leaving notable gaps.

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

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

The description is extremely concise, with only two sentences covering the tool's purpose, cost, and parameter meaning. It is front-loaded and every word earns its place; the line break for the argument is clean and 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?

This is a simple one-parameter tool with no output schema, so the description need not be exhaustive. It covers what the tool watches, the cost, and the limit range, but it omits what the returned data looks like and any filtering capabilities, leaving it adequate but not fully self-sufficient.

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

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

The schema only defines limit as an integer with default 20 and no description. The description adds 'max events (1-50)', providing both meaning and a validation range, which compensates for the schema's lack of property 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 identifies the resource as model-card events (launches, silent downgrades, safeguards, policy events) and scopes them by lab, which is specific. However, it uses the nominal 'watch' rather than an explicit verb like 'list' or 'get', and it does not distinguish this tool from its siblings modelwatch_latest and modelwatch_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?

There is no guidance on when to use this tool versus modelwatch_latest or modelwatch_search. The only contextual hint is the paid nature and the limit parameter, but no alternative selection criteria or exclusions are mentioned.

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

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

With no annotations available, the description carries full behavioral disclosure burden. It mentions 'paid, $0.002/req or pass', which is a cost/access trait, but the meaning of 'pass' is cryptic and no information about the output format, side effects, or operational behavior is given.

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 and remains concise. However, the parenthetical 'paid, $0.002/req or pass' adds confusing, possibly non-essential detail that could be better placed or explained elsewhere, slightly detracting 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?

Since there is no output schema and no annotations, the description should fully explain what the tool returns and the meaning of key terms. It does not describe the return value's shape, what constitutes a 'model-economy event', or the 'pass' mechanism, leaving the tool under-specified.

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

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

The tool has zero parameters, so the baseline score of 4 applies. The description does not need to add parameter information, and the schema coverage is complete by default.

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 indicates the tool returns the most recent model-economy event, distinguishing it from sibling tools like modelwatch or modelwatch_search via 'latest'. However, it lacks an explicit verb such as 'returns' or 'fetches', relying on the noun phrase to imply the action.

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 modelwatch or modelwatch_search. The description only states what the tool provides, not in which scenarios it is the appropriate choice.

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

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

With no annotations provided, the description carries the full burden. It discloses pricing ($0.003/req or pass) and the limit range, which adds value. However, it does not describe the return format, error behavior, or confirm that this is a read-only operation, leaving some transparency gaps.

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

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

The description is extremely concise, using an Args block to structure parameter details. Every sentence adds useful information, with no wasted words or repetition.

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

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

For a simple two-parameter search tool, the description covers purpose, parameters, and pricing, making it largely complete. It does not mention return format or sibling alternatives, but given the low complexity and the absence of an output schema, this is acceptable.

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 significantly enhances the parameters beyond the bare schema. It explains 'lab' as a name fragment with examples and 'limit' as max events with a range of 1-20. Since schema description coverage is 0%, this enrichment is crucial and well-executed.

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 retrieves model-watch events filtered by lab name, with concrete examples. The verb 'search' is in the name, and the resource and filtering scope are clear. It distinguishes from siblings like modelwatch and modelwatch_latest implicitly, though not by name.

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 this tool is for lab-specific queries via the required lab parameter, but it does not explicitly state when to prefer this over siblings like modelwatch or modelwatch_latest. No exclusions or alternatives are mentioned, so usage guidance is only implied.

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

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

The description discloses that the tool is paid ($0.001/req or pass), which is valuable beyond the schema. However, it does not state whether this is a read-only operation, how results are ordered, or what happens when no filters are provided (beyond returning latest). Without annotations, this leaves some behavioral ambiguity, but the cost disclosure earns a middle score.

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 list of args. Every piece of information is useful and directly relevant. The description is efficient and well-structured.

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

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

The tool has no output schema, so the description should ideally describe the return shape. It does not, nor does it mention ordering or edge cases. However, it does cover purpose and all parameters. For a simple search tool, this is adequate but not fully complete.

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

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

All three parameters are explained in the description with specific semantics: category as a beat filter with examples, query as full-text search, limit with a range (1-100). The schema has no descriptions (0% coverage), so the description fully compensates and adds constraints not present in the schema.

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

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

The description clearly identifies the tool as retrieving the latest wire items from Monexus Terminal, with optional filters. The name 'search_wire' and the description align, distinguishing it from article/thread siblings by resource type. However, it lacks an explicit verb like 'searches' or 'retrieves' in the description, relying on the tool name for the action.

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 mention of when to use this tool versus the sibling tools. It does not state that it is for wire items only or that alternatives exist for articles/threads. The description provides no contextual guidance on selection.

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

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

With no annotations, the description carries the burden. It discloses a cost of $0.005/req or pass, which is useful behavioral context, but it does not explain window size, return structure, or read-safety. Minimal but non-zero 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 uses two concise sentences plus a compact args list, and every sentence earns its place. The phrase 'or pass' is a bit ambiguous, but overall it is efficient 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?

For a simple two-parameter tool, the essential inputs are covered, but with no output schema and no details on what the windowed context contains, the description is somewhat incomplete. It is enough to invoke but not to anticipate results.

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 has no descriptions (0% coverage), but the description compensates by explaining that episode comes from transcripts_search and that start is in seconds, adding units and source not present in the schema.

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

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

The description clearly states the tool returns windowed context around a transcript segment, using episode and start time. It references transcripts_search for episode IDs, which helps distinguish it from sibling transcript tools, though it doesn't explicitly name alternatives.

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 after transcripts_search provides an episode and start segment, but gives no explicit when-to-use or exclusions versus siblings like transcripts_episode or get_context. It provides clear context but is not comparative.

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

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

No annotations are provided, so the description carries the full burden. It discloses a key behavioral trait—the opening may be paid ($0.01/req) or passed—which is useful. However, it does not mention authentication, error handling, or rate limits, leaving some gaps.

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

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

The description is extremely concise, with two sentences that front-load the purpose and then explain the argument. No wasted words; every part 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 single-parameter tool with no output schema, the description covers the key aspects: what the tool returns (metadata, segment count, opening), the cost consideration, and the source of the parameter. It is sufficient for an agent to invoke it correctly, though it omits detailed return formatting.

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 has one parameter (episode) with no description, so coverage is 0%. The description compensates by explaining exactly what the parameter is ('episode id from transcripts_search'), adding meaning beyond the bare string type.

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 resource ('One podcast episode') and what it returns (metadata, segment count, opening). It distinguishes from siblings like transcripts_search and transcripts_sentiment by focusing on a single episode's details, though it lacks an explicit verb like 'get' or 'fetch'.

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 usage context: the episode id is from transcripts_search, implying this tool is used after a search to retrieve details for a specific episode. It does not explicitly state when not to use it, but the prerequisite 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?

With no annotations provided, the description must carry the behavioral disclosure burden. It discloses the cost per request, the minimum query length, and FTS ranking. However, it does not discuss read-only guarantees, error behavior, or how results are sorted beyond 'FTS-ranked', leaving some gaps.

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

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

The description is concise and well-structured: a clear opening sentence, a sentence on output details, a usage note, and a compact args list. Every sentence earns its place without fluff or redundancy.

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

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

For a simple search tool with no output schema, the description covers the essentials: purpose, output fields, cost, and parameter constraints. It doesn't explain how to chain with sibling tools (e.g., transcripts_context), but that is not strictly required for invoking this tool correctly.

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

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

The schema has 0% description coverage, so the description fully compensates by documenting 'q' with a length requirement and examples, and 'limit' with a range. This adds significant meaning beyond the schema, though it could be even more explicit about default behavior or optionality.

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 a podcast corpus, with a specific verb and resource. It mentions FTS-ranked segments and result fields, distinguishing it from single-episode fetchers. However, it doesn't explicitly compare to siblings like transcripts_episode, which would fully satisfy the 'distinguishes from siblings' criterion.

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 a clear use case: 'Ideal for research agents that need quoted, dated business-news material.' This gives context on when to use the tool, but it does not mention when not to use it or explicitly name alternative tools, stopping short of a full 5.

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

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

There are no annotations, so the description carries the full burden. It discloses that the tool is paid and includes a 'pass' option, but the meaning of 'or pass' is ambiguous. It also does not mention response format, authentication, or rate limits, leaving significant behavioral gaps.

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

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

The description is extremely concise, with the core purpose in the first line and parameter explanations in a list. Every sentence earns its place, and it is well-structured.

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

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

For a simple read-like tool with 2 parameters and no output schema, the description provides basic invocation information such as cost and limits. However, it lacks details about the return format or error behavior, which is important without an output schema, so it is only partially complete.

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

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

Schema description coverage is 0%, and the description compensates by explaining both parameters: 'q: search term' and 'limit: max segments scored (1-20)'. This adds clear semantic meaning beyond the schema's type/default 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 states 'Lexicon sentiment over top matching segments' which clearly identifies the tool's function as computing sentiment scores for segments matching a search query. It is distinguishable from sibling transcripts tools by its focus on sentiment, though it lacks an explicit imperative verb.

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

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

No guidance is provided on when to use this tool versus alternatives like transcripts_search or transcripts_context. The cost note ('paid, $0.002/req or pass') is a usage consideration but does not help with tool selection.

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

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

With no annotations provided, the description carries the full burden. It discloses important behavioral traits such as the paid nature ('$0.01/req or pass') and the limit parameter's max datapoints range (1-50). However, it does not describe the response format, any authentication requirements, or potential errors, leaving gaps in transparency.

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

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

The description is extremely concise, with a front-loaded purpose statement and a clearly formatted arguments section. Every sentence earns its place, providing necessary context without any fluff.

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

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

For a simple one-parameter tool with no output schema, the description covers the essential purpose, examples, cost, and limit semantics. However, it lacks an explicit statement of the return format and fails to differentiate from 'verticals_latest', which is a notable omission for a tool in a crowded sibling set.

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 fully explains the only parameter 'limit' by specifying it as the max datapoints and providing the allowed range (1-50). This adds significant meaning beyond the bare schema, which only lists type and default. Given 0% schema coverage, this is a strong compensatory explanation.

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 indicates the tool provides vertical intel for agent-commerce and messy-middle segments, with specific examples (Shopify GMV, Ambrook, super.com). It is not a tautology and gives a clear sense of the resource. However, it does not explicitly distinguish itself from the sibling tool 'verticals_latest', which may cause confusion.

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

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

There is no guidance on when to use this tool versus alternatives like verticals_latest or other vertical-related tools. The only hint is the paid nature ('$0.01/req or pass'), which implies cost-conscious usage, but no explicit when-to-use or when-not-to-use context is provided.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It adds a key financial detail (paid, $0.002/req) and hints at a 'pass' behavior when no data is available, which goes beyond the schema. However, it omits other important aspects like read-only status, response format, or error conditions, leaving significant gaps.

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

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

The description is a single sentence with no filler or redundant information. It packs a surprising amount of detail (latest datapoint, paid cost, pass behavior) into a very compact format, demonstrating excellent 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?

Despite the tool's simplicity, the description is incompletely contextual. It does not define what 'vertical-intel' means, describe the expected return value, or explain the 'pass' condition. Since there is no output schema and no annotations, the description leaves the agent with substantial ambiguity about how to interpret 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?

The tool has zero parameters, so the schema is inherently complete. According to the calibration baseline for 0 parameters, a score of 4 is appropriate; the description does not need to compensate for missing parameter documentation.

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

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

The description identifies the resource as a 'vertical-intel datapoint' and specifies it as the single most recent one, which clearly implies a retrieval operation. However, it lacks an explicit verb like 'gets' or 'retrieves' and does not directly contrast with sibling tools such as 'verticals'.

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

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

There is no guidance on when to use this tool versus alternatives. The description mentions pricing and a 'pass' condition but provides no context about typical use cases, prerequisites, or why a user might choose this over 'verticals' or other sibling tools.

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