Recao

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

Beyond annotations, the description discloses cost (metered at provider cost +10%, billed against trust cap), model-dependent output counts, and the restriction to paid plans. This adds significant value, especially since annotations only provide basic hints.

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

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

The description is a single paragraph that efficiently covers purpose, model behavior, and cost. It is front-loaded and contains no unnecessary repetition, though it could be slightly more terse.

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 complexity (3 parameters, no output schema), the description explains the purpose and cost but does not describe the return format (e.g., URLs, data type) or potential error cases. Some gaps remain for a fully complete specification.

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 detailed parameter descriptions. The tool description echoes some schema info (e.g., model behavior) but adds little new semantic insight 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 the tool generates a UGC persona (avatar) based on a persona brief, returning stills for image-to-video. It differentiates model behaviors (default vs. imagen/flux) and mentions cost and billing, making the exact purpose unmistakable.

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 when a generated avatar is needed for UGC, and clarifies that it is for paid plans only. It also explains model selection implications. However, it does not explicitly state when not to use or provide alternatives, though no direct sibling exists.

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

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

Annotations already indicate readOnlyHint and idempotentHint; description adds behavioral detail about showing all language variants and creative assets, without contradicting 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?

Two concise sentences plus a third; no wasted words, though integration of second sentence could be tighter without losing clarity.

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

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

Despite no output schema, description adequately lists return contents (language variants, creative URLs, icon variations) for a simple two-parameter 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?

With 0% schema description coverage, the description clarifies adId's origin but does not explain datePreset beyond its enum name, leaving some meaning implicit.

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 retrieves full details and locale/creative variations for one specific ad, distinguishing it from sibling tool get_competitor_ads which lists ads.

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 adId from get_competitor_ads and states its usefulness for competitor localization analysis, providing clear context for when to use and hinting at alternatives.

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

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds behavioral details: data source (Apple Ad Repository), sorting by longevity, and included fields. No contradictions.

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 packs all key information but is slightly dense. Could be split for better readability, but remains efficient and front-loaded with 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 adequately describes the result contents and sorting. Lacks mention of pagination or size limits, but overall covers essential aspects for a read-only, list-type 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 50%. The description adds meaning for datePreset (up to 1 year back) and countries (EU storefronts), but does not explain the 'type' parameter or explicitly connect 'id' to the sibling search tool. It partially compensates for missing schema descriptions.

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

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

The description clearly states it retrieves competitor ads from Apple App Store with specific details like creative copy, placements, formats, and winner analysis. It distinguishes itself from siblings like get_ad_details (specific ad) and search_app_advertiser (search), and the title reinforces the purpose.

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

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

The description indicates when to use: to get all competitor ads for EU storefronts up to 1 year back. It mentions the data source and implied constraints. While it doesn't explicitly contrast with siblings, the context signals and naming provide enough guidance.

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

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds context about the tool's data source and its relation to the roadmap, without contradicting annotations. It doesn't introduce new behavioral traits beyond what annotations cover, but the added context is valuable.

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

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

The description is two sentences with no wasted words. The main purpose is front-loaded, and the second sentence provides actionable guidance. Every sentence is essential.

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 optional parameter, no output schema), the description is fairly complete. It explains what it does, when to use it, and how to invoke it. The lack of output schema is acceptable for a retrieval tool, but mentioning the return format could 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 schema has 0% parameter description coverage, so the description must compensate. It explains that omitting slug lists all playbooks, which adds meaning beyond the schema type. However, it could be more explicit about what the slug represents (e.g., a playbook 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 identifies the tool as retrieving a Recao GTM playbook, specifying the resource and verb. It distinguishes itself from siblings by mentioning 'the-roadmap' and listing all playbooks, and provides context about the domain (solo app founder, competitor data).

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

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

The description advises starting with 'the-roadmap' before using this tool, and explains that omitting the slug lists all playbooks. While it doesn't explicitly state when not to use it, this guidance is clear and helpful for the 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?

Annotations already mark the tool as readOnly and non-destructive. The description adds value by explaining the sorting order and that memory accrues automatically from competitor scans and memory_note writes, providing useful behavioral context beyond 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?

Two sentences, no wasted words. Front-loaded with purpose and immediately provides usage guidance. Highly efficient.

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

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

Given zero parameters and no output schema, the description comprehensively covers what the tool does, how to use it with memory_recall, and how data accumulates. No gaps remain for this simple list tool.

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

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

No parameters exist, so baseline is 4. The description correctly omits parameter details, as none are 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 states the verb 'list' and the resource 'company memory', specifies the format (one line per entry with name and description, newest first), and distinguishes from sibling tools by advising to use memory_recall for full bodies.

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 traverse index-first, then use memory_recall for full bodies, providing clear context. Lacks explicit exclusion conditions but is sufficiently directive.

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?

Disclosure of idempotent behavior (write or update) aligns with idempotentHint=true. Mentioning persistence across sessions and weekly reports adds context beyond annotations. No contradictions with annotations.

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

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

Two sentences with no wasted words. Purpose and usage are front-loaded. 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?

Given full schema coverage, no output schema, and annotations providing safety profile, the description is complete. It explains purpose, parameter conventions, and persistence, making it fully actionable.

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?

Adding value beyond schema descriptions: specifies 'short kebab-case slug' for name, 'one-line summary for the index' for description, and 'Full content (markdown fine)' for body. Schema coverage is 100%, but description enriches semantics.

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

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

Clearly states 'Write (or update) a memory entry' with specific examples of content (decisions, campaign outcomes, learnings). Distinguishes from siblings like memory_index and memory_recall by focusing on writing/updating.

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 instructions on how to use parameters (kebab-case name, one-line description, body). Mentions future sessions and weekly reports read this, implying when it's valuable. Does not explicitly state when not to use or list alternatives, but guidance is clear and helpful.

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

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. Description adds that it reads 'full body' (beyond metadata). No contradiction, but behavioral details are minimal given annotation coverage.

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, front-loaded with action, no wasted words. Efficient and direct.

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 one parameter and no output schema, the description adequately conveys purpose and usage context. Could mention error behavior, but not essential.

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 additional meaning beyond the schema description (both say 'kebab-case slug from memory_index'). 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?

Description uses specific verb 'Read' with resource 'memory entry's full body', and distinguishes from sibling 'memory_index' (which lists names). Clearly states what tool does.

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 advises to get names from memory_index first, providing context for when to use this tool. Does not mention when not to use it, but the sequential hint is helpful.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description confirms it reads scans and memory, consistent with read-only behavior. Does not add significant behavioral context beyond 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?

Two clear, front-loaded sentences. First sentence states core purpose and outcome; second provides actionable guidance. 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?

Explains input (scans/memory) and output (stage, constraint, playbook). Lacks explicit output format or error conditions, but given no output schema and zero parameters, it is adequately 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?

No parameters in schema; description adds value by explaining the tool reads user scans and memory, compensating for the absence of parameters. Baseline 4 for zero-parameter 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's purpose: diagnose the Recao Roadmap stage (S0-S4), binding constraint, and playbook. It specifies it's the starting point for go-to-market work, distinguishing it from siblings like get_playbook which might be a follow-up.

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 says it's where the agent starts, implying first use. Suggests writing a memory_note to improve results. While it doesn't list when not to use or alternatives, the context of siblings provides 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?

Annotations already provide readOnlyHint, idempotentHint, destructiveHint. The description adds that it returns IDs, but no further behavioral details. No contradiction with annotations.

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

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

Two sentences with no extraneous information. The first sentence immediately states the purpose, making it 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?

The tool is simple (2 params, 1 required). The description explains it returns IDs for downstream use, which is sufficient. Missing details like pagination or result limits, but the openWorldHint annotation mitigates that.

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 50% of parameters (name has description). The description adds value for the 'name' parameter by suggesting it for competitor's app name. However, the 'types' parameter (enum) is not explained, and the description does not fully compensate for the coverage gap.

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 'Apple Ad Repository', and the scope 'apps or developers advertising on the EU App Store'. It also distinguishes from siblings by specifying the output is IDs for use with get_competitor_ads.

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 'Start here with your competitor's app name', indicating the tool as an entry point. It also mentions integration with get_competitor_ads. However, it does not explicitly state when not to use or compare with other siblings like get_ad_details or get_playbook.

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

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

Beyond annotations (idempotentHint=true), the description discloses that the key arrives in the response AND by email with a verification link that unlocks full quota. This adds significant behavioral context about the signup flow.

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 with no wasted words. The first sentence states the purpose, the second adds a key differentiator (no browser), and the third outlines the process and follow-up action.

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

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

The description covers the signup process, key delivery, verification, and how to use the key. It could mention that this is a prerequisite for other tools, but for a signup tool it is fairly complete without an output schema.

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

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

Schema coverage is 100% and each parameter already has a good description in the schema. The tool description does not add extra semantics beyond what is in the input 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 'Create', the resource 'free Recao account', and the outcome 'get an API key'. It distinguishes from sibling tools which are about ads, memory, and account management (upgrade, whoami).

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

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

It provides clear context: 'Agent-native signup, no browser needed' and explains the key delivery and reconnection. However, it doesn't explicitly state when not to use this tool or mention alternatives for existing accounts.

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 adds behavioral context beyond annotations: explains that payment happens in the browser (so no server-side billing) and that the link should be handed to the human. Annotations already declare readOnlyHint, destructiveHint, and idempotentHint as true, which are consistent. The description does not contradict annotations and provides useful operational details.

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 extremely concise: two sentences plus a parenthetical. The main purpose is front-loaded, and every word adds value. 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 simple tool with one parameter and no output schema, the description covers the essential aspects: what the tool does, the plan options, and that payment is handled by the human. It is sufficient for an AI agent to select and invoke the tool correctly, though it could mention prerequisites like having an existing account.

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 so by explaining the two enum values (Indie and Pro) with their respective features and pricing, adding semantic meaning beyond the schema's bare enum list.

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 'Get the checkout link to upgrade this account to a paid plan', specifying the verb (Get), resource (checkout link), and action (upgrade). The tool is distinct from all sibling tools, which include sign_up, whoami, and various data access tools, so there is no ambiguity.

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

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

Description provides clear context about when to use this tool: to generate a checkout link for upgrading to a paid plan. It also explains the two plan options with pricing and features. However, it does not explicitly state when not to use this tool or compare it with alternatives, though no sibling tool overlaps in functionality.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context about spending, trust-ladder, and whether generation is blocked, without contradicting 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?

Description is a single concise sentence that front-loads key information and includes a practical usage note. 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?

Despite lacking an output schema and parameters, the description fully details what the tool returns (spend, cost+10%, trust-ladder cap, accrued amount, blocked status) and provides a usage tip, making it complete for its purpose.

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, so description does not need to add parameter info. The baseline is 4, which is met.

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 'Show this account's metered generation spend...and its trust-ladder position.' It specifies the exact information returned, distinguishing it from sibling tools.

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

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

The description includes a usage hint ('Use it to report costs back to your human'), but does not explicitly mention when not to use or provide alternatives.

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

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds value by specifying the returned fields (plan, email, verification state), which goes beyond what annotations provide. No contradictions.

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 is front-loaded with the action 'Show' and efficiently conveys both the positive case (authenticated account) and the negative case (anonymous). 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 tool with no parameters, no output schema, and simple functionality, the description provides sufficient context: it covers what the tool returns and the two possible states (authenticated vs anonymous). No additional information is needed.

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 no parameters and schema description coverage is 100% (empty). With 0 parameters, the description is not required to add parameter meaning. Baseline is 4 for such cases.

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

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

The description explicitly states the tool shows authenticated account details (plan, email, verification state) or confirms anonymity. This is a specific verb+resource combination that clearly distinguishes it from sibling tools like sign_up or upgrade.

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

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

The description implicitly indicates use for checking authentication status, but does not provide explicit guidance on when to use this tool versus alternatives or when not to use it. Given the tool's simplicity and lack of parameters, this is adequate but leaves room for improvement.

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