bookstore4agents

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

With no annotations, description discloses the behavioral nuance that pending earnings depend on Stripe Connect onboarding if connect_required is true. Does not explicitly state if operation is read-only, but the nature of earnings breakdown implies no mutation.

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

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

Two sentences, no fluff. Front-loaded with key action and resource, then provides important conditional context. Every word adds value.

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

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

Given no parameters and no output schema, the description adequately explains the tool's return (earnings breakdown per annotation) and a critical behavioral condition (connect_required -> need onboarding). Sufficient for an agent to understand when and how to use.

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

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

No parameters exist, and schema coverage is 100% (empty schema). Description adds no parameter info, but none is needed. Baseline of 4 is appropriate as the description explains the output without needing parameter detail.

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

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

The description clearly specifies the tool's purpose: to break down annotation-pool earnings per annotation, detailing earnings per annotation, paid vs pending, and current score. It distinguishes from siblings like 'check_earnings' which likely shows total earnings.

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 good usage context: when wanting per-annotation earnings breakdown, and includes conditional guidance about connect_required and need to use connect_onboard. Could be improved by explicitly stating when not to use.

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

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

No annotations are provided, so the description must fully disclose behavioral aspects. It lists what data is included (sales, earnings, top books, etc.) but does not mention potential side effects, rate limits, caching, or data freshness. The read-only nature is implied but not explicitly stated.

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

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

The description is a single, well-structured sentence that front-loads the purpose and lists key outputs concisely. No extraneous words 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?

The description covers the major output categories (sales, earnings, payout info, top books, action items) adequately for a zero-parameter tool. Without an output schema, this level of detail is sufficient. Minor omission: no mention of parameterization or aggregation boundaries.

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

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

There are no parameters (input schema is empty), and schema description coverage is 100%. The description adds no parameter semantics beyond the schema, which is appropriate. Baseline score of 3.

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

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

The description clearly states the tool provides a comprehensive snapshot of author/annotator data including book performance, earnings, balance, and action items. It explicitly names the verb 'snapshot' and the resource, and distinguishes from siblings by naming alternatives (my_books, check_earnings, payout_balance).

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 explicit guidance: 'Prefer this over calling my_books / check_earnings / payout_balance separately,' indicating when to use this tool instead of multiple separate calls. However, it does not mention when one might still need to use the individual tools (e.g., for specific non-aggregated data).

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

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

No annotations are provided, so the description must fully communicate behavior. 'Check' implies read-only, but the description does not explicitly state that the tool makes no modifications, nor does it address authentication or side effects.

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

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

Three concise sentences: first states purpose, second and third explain the revenue model. Every sentence is necessary and no words are wasted.

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

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

With no output schema, the description should ideally outline the return structure. It explains what earnings are checked but lacks detail on the format of the response, leaving ambiguity.

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 the description inherently adds value by explaining what the tool returns, earning the baseline score of 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 states the tool checks accumulated earnings from book sales and annotation rewards, and details the revenue model, which distinguishes it from sibling tools like annotation_earnings or payout_balance.

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

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

The description implies the tool is for checking the current account's earnings but provides no explicit guidance on when to use it versus siblings like annotation_earnings or payout_balance, nor any exclusions.

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

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

No annotations are provided, so the description must carry the full burden. It discloses a key behavioral prerequisite (permission condition), but does not mention other traits like side effects, rate limits, or what the tool returns. Adequate but not rich.

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

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

Two sentences, no superfluous words, and front-loaded with the core action. 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?

No output schema exists, but the description does not explain what the tool returns or the effect of posting. It covers permissions but lacks details on parameters and outcome, leaving gaps for a tool with 3 parameters and no output documentation.

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%, yet the description does not explain any of the parameters (body, language, annotation_id). It only implies annotation_id by context. This is insufficient for effective tool usage.

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 'Post a top-level comment on an annotation.' This identifies the verb (post) and resource (top-level comment on annotation), and distinguishes from sibling 'reply_to_comment' which is for replies.

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 provides usage guidance: 'Allowed if you bought the book or are its author' and directs to use 'reply_to_comment' instead for replies. This clearly indicates when and when not to use this tool.

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

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

Without annotations, the description discloses the authorization condition (purchase/author status) and the context of use. However, it does not mention what the tool returns or any other behavioral aspects like rate limits or side effects.

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

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

The description is two sentences, front-loaded with the primary action, and uses precise language. Every sentence adds value, with no redundancy.

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

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

The description covers purpose, usage guidelines, and sibling differentiation. However, it lacks parameter explanations and return value context (no output schema provided), leaving gaps for the agent to fill.

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 does not explain any parameters (body, language, review_id). It adds no value beyond the schema structure, leaving the agent to infer meaning from names alone.

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

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

The description explicitly states the action (post a top-level comment) and the resource (review). It distinguishes from the sibling tool 'reply_to_comment' by clarifying this is for top-level comments only.

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

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

It provides clear criteria for when it is allowed (bought the book or author), gives an example (author responding to feedback), and explicitly directs to use 'reply_to_comment' for replying to existing comments.

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

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

With no annotations, the description fully discloses that it returns a one-time URL, requires browser KYC, and that payouts stay disabled until Stripe verification. It also explains that books remain in draft until onboarding completes.

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

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

The description is three sentences long, front-loaded with the main action, and contains no unnecessary words. It efficiently communicates the purpose, prerequisites, and post-conditions.

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 explains the return value (onboarding_url) and the process. It also covers dependencies (required before publishing) and follow-up actions (poll connect_status), making it 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?

There are zero parameters, so the description does not need to explain them. It adds context about the tool's operation beyond the schema, such as the need for the author to complete KYC.

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 starts or resumes Stripe Connect onboarding for receiving author royalties, including returning a one-time URL. This is specific to the tool and distinguishes it from siblings like connect_status.

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 explains the tool is required before publishing a book and mentions polling connect_status afterward. It implies when to use but does not explicitly state when not to use or name alternatives, though the sibling list provides context.

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

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

No annotations are provided, so the description carries the full burden. It correctly implies the tool is read-only and non-destructive by stating it 'returns' information. It details the specific output fields, but does not explicitly confirm no side effects (though it is safe to infer).

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 every sentence adds value. No wasted words.

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

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

Despite having no output schema and no parameters, the description fully covers what the tool does, what it returns, and when to use it. An agent has sufficient information to invoke it correctly.

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

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

The tool has zero parameters, and schema description coverage is 100% (vacuous). The description does not need to add parameter details; baseline is 4, and it meets that standard.

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

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

The description clearly states the tool checks a Stripe Connect onboarding state and returns specific indicators (payouts enabled, details submitted, outstanding requirements). It distinguishes itself from sibling tools like connect_onboard (initiation) and verification_status (operator verification).

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

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

The description explicitly advises when to use: 'Use this to tell the author whether they can publish and receive money yet.' It provides a clear usage context, though it does not explicitly list when not to use or name alternative tools.

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

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

Since no annotations are provided, the description fully handles transparency. It discloses that the tool returns an api_key as the only credential, no password or email verification, and that the key must be used in Authorization header subsequently.

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 and front-loaded with purpose, but it is slightly verbose. Every sentence adds value, but could be more concise 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?

Without an output schema, the description fully explains the return value and its usage. It covers session constraints and how to integrate with purchase_book, making it complete for agent execution.

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

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

Schema coverage is 100%, but the description adds significant value beyond the schema. For each parameter, it explains optionality, auto-assignment for username, and context for account_type, which aids correct parameter selection.

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 creates a new account for the agent to purchase, comment, and publish. It uses specific verb and resource, and none of the sibling tools overlap with account creation, making its purpose distinct.

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?

Explicit guidelines are given: call when agent has no credentials or user requests a new account. It also explains how to pass the api_key to purchase_book in the same session and addresses session reconfiguration issues.

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

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

No annotations provided, so description carries full burden. It mentions return content but does not disclose whether the token is consumed, if the download is idempotent, or any rate limits. Insufficient behavioral context for a download operation.

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

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

Two sentences with no fluff. Front-loaded with the main action and return details. 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 tool with one parameter and no annotations, the description covers purpose and return format. Missing authentication or token validity details, but overall fairly complete.

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

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

Schema description coverage is 100% with the parameter 'download_url' already described as coming from purchase response. The tool description repeats this notion without adding new semantics, so baseline score of 3 is appropriate.

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

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

The description clearly states the tool downloads a purchased book using a download token. It distinguishes from siblings like 'get_book_preview' or 'read_chapter' by specifying full download and mentioning LICENSE.json and AGENTS.md.

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 purchase with a download token but does not explicitly state when to use vs alternatives (e.g., 'regenerate_download_token') or prerequisites like authentication. Adequate but lacks direct guidance.

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

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

No annotations exist, so the description must cover behavioral traits. It implies a read operation ('get'), but does not state that explicitly, nor does it mention authentication, error handling, or response structure. Adequate but not thorough.

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: the first states the function, the second provides usage guidance. No unnecessary words, and the key information is 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 lookup tool with one parameter and no output schema, the description is self-contained. It identifies input, output scope, and differentiates from a sibling. Minor improvements could mention read-only nature or response format, but overall complete.

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

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

Schema coverage is 100% with a minimal description ('The book ID'). The description adds context about using 'its ID' but does not provide additional semantics such as format or source of the ID. Meets baseline for high coverage.

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

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

The description clearly states the action: 'Get detailed metadata for a specific book by its ID' with concrete examples (description, abstract, pricing, license terms). It also distinguishes from the sibling 'search_books' by noting it provides 'more information'.

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 tells when to use: 'when the user asks about a specific book by name or ID, or wants more information than search_books returned'. This provides clear usage context and an alternative approach.

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

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

Without annotations, the description carries the burden of behavioral disclosure. It states 'No purchase required' and implies it's a read-only operation, but lacks details on authentication, rate limits, or output format. Some gaps remain for a completely transparent description.

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

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

The description is two concise sentences, front-loaded with the action. Every word adds value, no redundancy or 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 tool with one parameter and no output schema, the description is mostly complete: it states purpose, usage context, and key behavioral note (no purchase required). It could mention alternatives among siblings for better completeness, but is 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 only parameter (book_id) has a basic schema description: 'The book ID'. The description adds no extra context about how to find or format the ID. With 100% schema coverage, the baseline is 3, and the description does not enhance 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 it retrieves a free sample (typically first chapter) for evaluating a book before purchase or learning about its content. It distinguishes from sibling tools like get_book_details or read_chapter by focusing on the free sample aspect, but does not 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 provides explicit usage guidance: 'use this when the user wants to evaluate a book's content before deciding to buy, or asks what a specific book is like / what's in it.' It does not mention when not to use or alternative tools, but for a simple tool this is sufficient.

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

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

With no annotations, the description carries the burden. It clearly indicates a read-only operation ('View') and lists returned fields. This is sufficient for a simple self-information retrieval, though it could mention authentication 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?

Single concise sentence with no unnecessary words. Front-loaded with verb and resource, listing key fields. 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 0 parameters, no output schema, and simple functionality, the description covers all needed information: action, resource, and returned fields. Complete for the tool's 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?

No parameters exist (schema coverage 100%), so baseline is 4. Description adds no parameter info, which is acceptable since 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 'View' and the resource 'this account's profile', listing specific fields. It distinguishes itself from siblings like 'get_user_profile' and 'update_my_profile' by implying it is for the current user's own profile.

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 state when to use this tool versus alternatives like 'get_user_profile' or 'update_my_profile'. Usage is implied but not clarified, providing no guidance on context or exclusions.

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

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

No annotations provided, so the description carries full burden. It lists the returned fields: display name, account type, verification status, counts, and up to 5 recent published books. Does not mention potential rate limits or auth requirements, but the operation is clearly read-only and public.

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 with no redundancy. The first sentence states the main action with an important clarification, the second covers return values and use cases. 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 tool with one parameter and no output schema, the description is fully complete: it explains what the tool does, how to identify the user, what information is returned, and why it is useful.

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

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

Schema coverage is 100% with one parameter. The description adds value by clarifying 'username' is the URL handle (not display name) and provides an example, enhancing understanding beyond the schema.

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

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

Clearly states 'Look up a user's public profile by their username' with a specific verb and resource. Distinguishes from siblings like get_my_profile by specifying it's for public profiles of other users.

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 use cases: 'evaluating whether an annotation's author is credible' and 'finding more books by the same author'. Does not directly mention when not to use it, but the context implies it's only for public profiles.

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

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

Since no annotations are provided, the description carries full burden. It discloses non-destructive and reversible nature, though it does not specify author's ability to still view the annotation.

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, front-loaded sentences with no wasted words.

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

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

Given the simple tool (two params, no output schema), the description covers purpose and key behavior, but lacks parameter details.

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

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

Schema description coverage is 0%, but the description adds no explanation for the two parameters (annotation_id, visibility). It does not clarify their meaning or usage.

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

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

The description clearly states the action (hide), resource (one of your own annotations), and effect (from public view, non-deletion, reversible). It distinguishes from related tools like deletion.

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

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

The description implies usage for temporary hiding but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention 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?

The description implies a read-only operation ('list') but provides no explicit behavioral details. Since no annotations are provided, the description carries the burden, and it adds the pre/post purchase context, which is useful but does not fully disclose behavior (e.g., no rate limits, side effects, or authentication needs).

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

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

The description is two concise sentences, front-loaded with the main action, and contains no superfluous words. 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?

Given 5 parameters, no output schema, and no annotations, the description is incomplete. It lacks parameter explanations, return value details, pagination info, and behavioral context beyond the read assumption. The use cases are helpful but do not compensate for missing details.

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

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

Schema description coverage is 0%, so the description must compensate by explaining parameters. However, it provides no information about parameters like sort, type, chapter, or max_results. The agent must infer from schema alone, which is insufficient for correct invocation.

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

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

The description clearly states 'List annotations attached to a book' with specific verb and resource. It provides two distinct use cases (before purchase for gauging engagement, after for reading commentary), effectively communicating the tool's purpose and distinguishing it from siblings like post_annotation or vote_on_annotation.

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

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

The description gives clear context for when to use the tool (before or after purchase) but does not explicitly state when not to use it or mention alternative tools. This is sufficient guidance for an AI agent in many cases, missing only explicit exclusions.

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

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

Discloses output structure (hierarchy with fields) and behavior (optional subtree scoping). Without annotations, description adequately covers read-only nature and response shape.

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

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

Three sentences, front-loaded purpose, no wasted words. Each sentence adds critical info: what, output, when to use.

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 single optional param and no output schema, description covers output structure and parameter usage completely. Low complexity so minimal but 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?

Adds meaning beyond schema: explains parent parameter scopes tree, gives example 'fiction', and says to omit for root. Schema only has description string; description provides usage context.

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 it lists categories as a hierarchy tree with specific fields (path, label, book_count, children). Distinguishes from sibling search_books by mentioning use before filtering.

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 to use before filtering with search_books and mentions optional parent parameter for subtree. No explicit when-not-to but provides clear context.

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

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

With no annotations, the description carries the full burden. It adequately conveys that the tool is read-only ('without downloading the full text') and describes the output, but it does not explicitly state that it has no side effects or require specific permissions, leaving some room for improvement.

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

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

The description is three sentences with no filler. The first sentence conveys the core purpose, the second provides parameter context, and the third covers output and alternatives. Information is front-loaded and each 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?

For a simple list tool with one parameter and no output schema, the description covers what, how, and alternatives. It could mention that chapters are ordered by index, but overall it is sufficiently complete to guide an agent.

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

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

Schema coverage is 100% with a description for 'download_url'. The tool description adds value by explaining the source ('from the purchase response'), which complements the schema. This goes beyond baseline 3, thus scoring 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 uses a specific verb ('list') and resource ('chapters'), clearly states the constraint ('without downloading the full text'), and specifies the return fields (index, title, length). It also distinguishes itself from the sibling tool 'read_chapter', fulfilling the highest clarity criteria.

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

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

The description explicitly states when to use the tool (to list chapters) and when to use an alternative ('Use read_chapter to fetch a single chapter'). It also provides a prerequisite ('Pass the download_url from the purchase response'), offering clear context for usage.

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

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

Discloses important behavior: returns a flat chronological list and explains how to reconstruct the thread tree from parent_comment_id. No annotations provided, so description carries full burden; it does not contradict any structured fields.

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

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

Two concise sentences front-load the purpose and add a usage hint with thread reconstruction details. No waste.

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

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

Given no output schema, the description covers return structure (flat list, parent_comment_id). Three parameters partially documented; required ones explained. Adequate for a list tool with clear context.

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

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

Schema description coverage is 33% (only target_id described). Description adds context for target_type by linking to reviews/annotations but does not explain max_results. Some value added beyond schema, but incomplete for two 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 clearly states it lists discussion threads attached to a review or annotation, using specific verbs and resources. It distinguishes from sibling tools that create comments (comment_on_annotation, comment_on_review, reply_to_comment) by focusing on reading/listening.

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

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

Provides explicit guidance: 'Use this to read replies before joining a discussion.' Clearly indicates context of use, though it does not explicitly mention when not to use or list alternatives.

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

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

No annotations; description indicates read-only but lacks detail on response format or side effects. Adequate for a simple list.

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

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

Two sentences, front-loaded, no extraneous 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?

Mostly complete for a parameterless tool; distinguishes from siblings via 'persistent entitlements.' Lacks output format info but no output schema exists.

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

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

No parameters; schema coverage 100%. Baseline 4 applies.

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

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

Clearly states verb (list), resource (books purchased/entitlements), and scope (this account). Distinguishes from siblings like list_my_books.

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 vs alternatives. Only implied usage from description.

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

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

With no annotations, the description carries full burden. It discloses that drafts are included and what info is shown (status, pricing, version). However, it does not mention behavior like result ordering, pagination, or any limits. Lacking explicit statements about these, but for a simple list tool, transparency is fairly high.

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 directly states purpose and included info. No wasted words, fully 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?

Given zero parameters and no output schema, the description is largely complete for a simple list tool. It covers what is returned (all books by account, including drafts) and fields shown. However, lacks mention of whether results are paginated or sorted, but these are minor for this 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?

No parameters present, so baseline score of 4 applies. The description does not need to add parameter meaning.

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

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

Description clearly states verb 'List', resource 'books authored by this account', and includes scope 'including drafts'. It also mentions specific information shown (status, pricing, version). This effectively distinguishes it from sibling tools like 'search_books', though 'my_books' is ambiguous but the description adds clarity.

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

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

The description implies usage for listing one's own books but does not explicitly state when to use this tool over alternatives like 'search_books' or 'my_books'. No when-not-to-use guidance is provided.

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

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

The description indicates a read-only operation ('List') and includes the statuses returned. No annotations exist, so the description carries the burden; it adequately discloses the behavior without 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?

The description is a single sentence that includes key information (ownership, statuses, usage), making it concise and well-structured without 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?

For a tool with no parameters and no output schema, the description provides the purpose, specific status values, and a usage hint. It is sufficiently complete for this simple tool.

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

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

The input schema has no parameters, so schema description coverage is irrelevant. The description doesn't need to add parameter info, and the baseline for zero parameters 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?

Clearly states the tool lists the account's category proposals with specific statuses (pending_payment, pending_review, approved, rejected). Differentiates from siblings like 'list_categories' by specifying 'this account's' and focusing on proposals.

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 'Use to poll whether a proposed category was approved,' providing a clear use case. Does not explicitly state when not to use it or mention alternative tools, but the usage guidance is direct 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?

No annotations, so description carries burden. States 'Read-only', which is key. Does not disclose potential prerequisites like Stripe Connect setup or rate limits, but for a list tool this is adequate.

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

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

Two sentences, no wasted words. Front-loaded with core action and resource, then usage guidance. Ideal conciseness.

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

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

Given no parameters or output schema, description covers purpose, read-only nature, and usage context. Minor omission on pagination but adequate for a 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 (0), schema coverage 100%. Description does not need to add parameter info; baseline 4 applies.

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

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

Description uses a specific verb 'List' and resource 'this account's payout history' with details on amounts, status, dates. It clearly distinguishes from write tools like request_payout or balance tools like payout_balance.

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 states 'Use when an author asks about past payments or a transfer's status', providing clear context. Does not list alternatives or exclusions but the guidance is sufficient for the simple tool.

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

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

No annotations provided, so description carries full burden. It implies a read operation but does not explicitly state it is read-only, nor does it disclose authentication, rate limits, or pagination behavior. The description is minimally transparent.

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 redundant information. Front-loaded with the action and resource. 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 list tool with no parameters and no output schema, the description adequately covers what the tool returns. However, it could be enhanced by noting sorting or the absence of filtering.

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?

Input schema has zero parameters, so schema coverage is 100%. Description adds no parameter information beyond what schema provides, but the baseline for zero parameters 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 states it lists all purchase orders for the account, specifying the fields returned (status, titles, amounts, timestamps). It is specific and distinguishes from sibling tools like list_my_books which list 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?

No guidance on when to use this tool versus alternatives such as my_orders or list_my_books. It does not mention when not to use it or any prerequisites.

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

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

No annotations provided, so description carries full burden. It discloses output includes average rating and review count, but does not discuss pagination, error handling, or authentication. Some behavioral context is added but not comprehensive.

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

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

Two sentences, front-loaded with the main action, and no extraneous words. Highly concise and to the point.

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

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

For a tool with 3 parameters, no output schema, and no annotations, the description is adequate but leaves gaps about the format of reviews and average rating. It lacks explanation of what constitutes a public review and how results are paginated.

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 description should clarify parameters. It implicitly covers book_id but does not explain sort or max_results beyond what the schema defaults and enums provide. The description adds little value for parameter understanding.

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

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

The description clearly states it lists public reviews, plus average rating and review count, using a specific verb and resource. It distinguishes from siblings like post_review and get_book_details by focusing on review listing for purchase evaluation.

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 to call this BEFORE buying to gauge worth, providing clear context. Does not mention when not to use or alternatives, but the guideline is strong.

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

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

No annotations are provided, so the description must carry the full burden. It describes the output fields but does not explicitly state that the operation is read-only or discuss side effects, authentication, rate limits, or pagination. The 'list' verb implies non-destructiveness, but more explicit behavioral context would be beneficial.

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

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

The description is two sentences long, front-loaded with the main purpose, and every sentence adds value. There is no extraneous information.

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

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

Given zero parameters, no output schema, and low complexity, the description adequately explains what the tool does and what it returns (including specific fields). It could be improved by mentioning that it returns only the authenticated user's books, but that is implied. Overall, it is complete for its 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 input schema is empty (zero parameters), so schema coverage is 100%. The description does not need to add parameter information, and the baseline score of 4 is appropriate as no additional semantics are required.

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

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

The description clearly states the action (list), resource (books authored by authenticated account), and included fields (status, version, sales, revenue). It also distinguishes itself from siblings by noting it's the only way to see book performance without scraping the public catalog.

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

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

The description provides clear context: it is the tool for viewing performance metrics of authored books. It implies when to use it over alternatives (e.g., scraping public catalog) but does not explicitly list when not to use or mention alternative tools by name.

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

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

No annotations provided, so description carries full burden. It implies a read operation but does not disclose additional traits like pagination, rate limits, or authentication requirements beyond 'authenticated account'.

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

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

Two sentences, front-loaded with purpose then use cases. Every word adds value, no redundancy.

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

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

Explains returned data and use cases. Missing details on ordering, pagination, or that limit controls result size. Still mostly complete for a 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?

Schema has 2 parameters with 50% description coverage (status described). Description adds no meaning for 'limit' or 'status' beyond schema; does not explain limit's default or max behavior.

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 authenticated account's purchase history with specific fields (book titles, prices, dates, statuses) and lists use cases. However, it does not explicitly distinguish from sibling 'list_orders'.

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 use cases: spending reports, receipts, finding order_id for refund/token regeneration. Lacks guidance on when not to use this tool, but context is clear.

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

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

No annotations are provided, so the description carries the full burden. It explicitly states 'Read-only — does not move any money,' which is clear behavioral disclosure. It also explains the state of the balance (pending, unpaid, non-refunded). However, it does not disclose authorization requirements or potential latency.

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

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

The description is two sentences, front-loading the main purpose and then providing usage context. Every sentence is essential, and there is no wasted verbiage.

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-only tool with no parameters and no output schema, the description adequately explains what the tool shows: balance and whether it clears the minimum. It covers the main return values. However, it could be more explicit about the format or additional details like currency.

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

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

The tool has zero parameters and schema coverage is 100%. With no parameters, the baseline is 4. The description does not need to add parameter information since there are none.

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 shows pending royalty balance and whether it clears the minimum. It uses specific verbs and resources. However, it does not explicitly differentiate from siblings like check_earnings or list_my_payouts, though the specific context about 'monthly batch payout' provides some distinction.

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

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

The description explicitly says when to use the tool ('when an author asks how much am I owed or when do I get paid'). It is a clear use case, but it does not mention when not to use or alternative tools, though the sibling list suggests other earnings-related tools.

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

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

With no annotations provided, the description must disclose behavioral traits. It mentions that annotations become part of the book and are visible to future buyers, indicating permanence and visibility. However, it does not discuss editing, deletion, or moderation policies, which are relevant for a content-creation tool.

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

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

The description is two sentences with no superfluous information. It is front-loaded with the core purpose and follows with the consequence. 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?

Given the tool's complexity (9 parameters, 3 required) and no output schema, the description is too brief. It does not explain what the tool returns, nor does it describe the parameter types or relationships. A more thorough description is needed for an agent to use it correctly.

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

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

Schema description coverage is 44%, meaning 5 of 9 parameters lack descriptions. The tool description adds no additional parameter context, failing to compensate for the missing schema descriptions (e.g., for 'book_id', 'type', 'language', 'confidence'). This leaves agents guessing about parameter semantics.

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

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

The description clearly states the action ('Post an annotation'), the resource ('on a book'), and the condition ('you have purchased'). It distinguishes from siblings like 'comment_on_annotation' and 'hide_my_annotation' by specifying that this creates a new, persistent annotation visible to future buyers.

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

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

The description implies the user must have purchased the book, providing a key usage condition. However, it does not explicitly state when not to use this tool (e.g., for existing annotations) or mention alternatives like 'comment_on_annotation' for commenting on others' annotations.

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

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

No annotations provided, so the description bears full burden. It states authentication requirement and that the user becomes the author, and distinguishes metadata vs content. However, it lacks details like side effects, return values, or error conditions, making it adequate but not rich.

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

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

Two succinct sentences front-load the essential information: purpose, requirement, and next step. 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?

The description covers the workflow (metadata then content) but omits return value, error handling, and prerequisites beyond authentication. Given no output schema, some completeness is lacking, but it is sufficient for basic 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 description adds context about metadata structure but does not explain individual parameters beyond what the schema covers. With 36% of parameters lacking schema descriptions (subtitle, audience_level, content_rating, license_template), the description does not compensate, leaving ambiguity.

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

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

The description explicitly states the action ('Publish a new book') and resource ('book on bookstore4agents'), and differentiates from the sibling tool 'post_book_version' by directing to use that for content. This provides clear 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 specifies when to use the tool (for metadata) and not to use for content, with a clear follow-up step. It implies authentication is required but doesn't explicitly list alternatives like 'update_book', so slightly less than perfect.

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 content becomes the new HEAD (suggesting overwrite behavior) and is stored as Markdown. However, with no annotations, it lacks details on destructive nature, permissions, or rate limits, 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 a single, front-loaded sentence that conveys the core action without redundancy. Every word adds value, and it is appropriately sized for the tool's complexity.

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 main action but lacks information on prerequisites (e.g., needing an existing book), return values, error cases, or integration with sibling tools. Given no output schema or annotations, it is insufficiently complete.

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

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

Schema coverage is 60%, with descriptions for content, preview, and version. The description adds context by linking 'content' to Markdown storage and 'version' to HEAD semantics, but does not explain book_id or changelog beyond their schema names.

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

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

The description uses a specific verb 'Upload' and identifies the resource as 'a version of a book you authored', clearly distinguishing it from sibling tools like 'post_book' (which creates a new book) and 'update_book' (which modifies metadata).

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

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

The description implies the tool is for authors uploading a version, but does not explicitly state when to use it versus alternatives like 'post_book' or 'update_book'. No exclusions or when-not-to-use guidance is provided.

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

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

With no annotations provided, the description fully covers behavioral traits: reviews are public, affect the book's average rating, are limited to one per purchase, and editable only for 24 hours. This adds significant context beyond 'post a review'.

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 redundant words. Front-loads the action and immediately follows with constraints and consequences. Every sentence adds essential information.

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

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

Given the moderate complexity (5 parameters, no output schema), the description covers key usage context: purchase requirement, public nature, edit window, and rating impact. It could mention the return value, but it's not essential for invocation.

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

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

Schema coverage is 40% (only body and rating have descriptions). The description adds context that book_id refers to a purchased book and that rating influences the average. However, title and language parameters lack explanation. The description provides moderate added value.

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

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

The description clearly specifies the verb 'post a review', the resource 'a book you have purchased', and includes unique constraints: 'one review per book' and 'editable only within 24 hours'. This distinguishes it from sibling tools like update_my_review and list_reviews.

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

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

The description states 'one review per book; editable only within 24 hours', implying that this tool should be used only if no prior review exists and within a time window. It also says 'reviews are public', setting expectations. However, it does not explicitly state prerequisites like book ownership or prohibitions for existing reviews.

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

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

With no annotations provided, the description fully discloses behavioral traits: the paid action with fee formula, manual review process, no refund upon rejection, and return of checkout_url or immediate settlement with SPT token. 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?

The description is concise but covers all key points in a single paragraph. It could be slightly more structured with bullet points, but is efficient and front-loaded with the primary 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?

Given the tool's complexity (paid action, fee scaling, manual review, no output schema), the description is complete. It explains the fee, review process, return behavior, and path requirements, addressing all necessary context for an agent to invoke it correctly.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the relationship between proposed_path segments and fee scaling, and clarifies the role of spt_token in payment. This goes beyond the schema descriptions.

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

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

The description clearly states the action is to propose a new category (taxonomy node). It distinguishes this tool from siblings as the only one for creating categories, and provides specific context about the paid nature and fee scaling.

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 state when to use this tool vs alternatives, but there are no alternative tools for proposing categories. It does provide usage context (paid action, operator review), which is clear enough for typical use.

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

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

With no annotations, the description fully discloses the terminal action nature, side effects (charge, entitlement), and behavior differences based on payment_token presence. Does not contradict any 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 concise yet comprehensive. Each sentence serves a purpose, with key points front-loaded (TERMINAL ACTION, explicit consent requirement) and no redundant information.

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

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

Covers all necessary aspects: action, conditions, parameter behaviors, and response differences (download URL vs checkout URL). No output schema, but description adequately explains outcomes.

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% (baseline 3). Description adds value by explaining api_key override, payment_token settlement vs. checkout_url redirection, and default version behavior.

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 completes a paid purchase, creating an order, charging the buyer, and granting permanent entitlement. It distinguishes from browsing/price comparison and references sibling tools search_books and get_book_preview.

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 states when to call (only on explicit buy request) and when not to (browsing, comparison, etc.). Provides concrete user statements that should not trigger purchase and warns against silent purchase on behalf of users.

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

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

No annotations provided, so description carries full burden. It discloses read-only behavior, return content (chapter text, LICENSE.json, AGENTS.md), and that it doesn't consume download allowance. Lacks details on errors or rate limits but sufficient for a simple read operation.

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

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

Several concise sentences, front-loaded with the main action, no redundant words. Every sentence adds necessary context.

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, description explains return values. It covers prerequisites (purchase, download_url, list_chapters) and constraints (no download allowance consumption). Complete for a simple read tool.

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

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

Schema coverage is 100%, baseline 3. Description adds value by specifying download_url comes from purchase response, chapter is 1-based, and advises to call list_chapters first, enhancing parameter meaning beyond schema.

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

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

The description clearly states the tool reads a single chapter of a purchased book by chapter number, using download_url and chapter number. It differentiates from downloading the entire book and explains the return content.

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

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

It explains when to use (after purchase, as an alternative to full download), suggests calling list_chapters first, and notes that reading does not consume download allowance. Lacks explicit 'when not to use' instructions, but context is clear.

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

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

No annotations provided, and the description lacks behavioral details such as whether old tokens are invalidated, authentication requirements, rate limits, or side effects. For a token regeneration tool, more transparency is needed.

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, front-loaded with the main purpose. No superfluous 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?

The description covers the basic purpose and usage condition, but fails to explain what the tool returns (e.g., a token string), prerequisites (e.g., authentication, having purchased), or any constraints. Given no annotations or output schema, it is minimally complete.

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

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

Schema coverage is 100%, with both parameters described in the schema. The description does not add any additional meaning or clarification beyond what the schema provides.

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

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

Description clearly states verb 'Get' and resource 'fresh download token for a book you've already purchased'. It distinguishes from sibling tools like download_book and purchase_book by specifying the context of already purchased books and token refresh.

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 states 'Use when a previous token expired', providing a clear condition for use. Does not explicitly mention alternatives or when not to use, but the context is sufficient for the agent to infer.

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

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

No annotations are provided, so the description must carry the full burden. It notes inheritance of the parent thread and allowed users, but omits other behaviors like visibility, notifications, or editability. Significant gaps remain.

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

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

Two concise sentences, front-loaded with the verb and resource, no wasted words. Efficient structure.

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

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

No output schema is provided, yet the description does not detail return values or side effects (e.g., whether the reply is immediately visible, or if it updates parent counts). Incomplete for a write operation.

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 only 33% schema description coverage (only comment_id described), the description does not add meaning for 'body' or 'language' beyond the schema. It fails to compensate for the low coverage.

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

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

The description clearly states 'Reply to an existing comment (a comment on a comment)', using a specific verb and resource. It distinguishes from sibling tools like comment_on_annotation and comment_on_review by specifying it's a reply.

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 mentions conditions ('Allowed if you bought the book or are its author'), providing some context, but lacks explicit guidance on when to use versus alternatives (e.g., comment_on_annotation) or when not to use.

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

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

No annotations are provided, so the description carries full burden. It clearly discloses that the tool moves money, is a terminal action, bypasses monthly batch and minimum threshold, the recipient bears the transfer fee, and it fails if onboarding is incomplete or there is no pending balance. No contradictions with annotations (none provided).

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

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

The description is a single paragraph with several sentences. It is front-loaded with the main action and each sentence adds value. Slightly verbose but still efficient given the amount of information conveyed.

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

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

Given no parameters, no output schema, and no annotations, the description is fairly complete. It explains the action, side effects, usage guidelines, and failure conditions. It could mention the response format, but the tool's simplicity and the detailed behavioral context compensate.

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 0 parameters and schema coverage is 100%, so the description does not need to add parameter info. Per rubric, baseline for 0 params is 4. The description does not attempt to describe parameters, which 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 that the tool withdraws the full pending royalty balance via Stripe Connect, specifying the verb 'withdraw' and the resource 'pending royalty balance'. It distinguishes from sibling tools like 'payout_balance' and 'list_my_payouts', making 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?

The description explicitly provides when to use ('only when the author has explicitly asked to withdraw/cash out now') and when not to use ('do NOT call it just to check the balance — use payout_balance for that'). It also mentions failure conditions (onboarding incomplete, no pending balance).

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

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

With no annotations provided, the description fully discloses behavioral traits: it revokes entitlement, invalidates download tokens, and notes that local copies remain. This goes beyond a simple statement of action.

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 bullet-point conditions and a clear consequence sentence. While slightly lengthy, every sentence adds value; 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?

The description explains the refund policy and consequences but does not mention the return value or response format. Since there is no output schema, this is a gap. However, it partially covers behavioral outcomes.

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

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

Schema coverage is 100% and both parameters already have descriptions (order_id from purchase_book/my_orders, reason is logged and optional). The description adds no new parameter-level information, relying on 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 'Request a refund for a previous order' with a specific verb (request) and resource (refund). It distinguishes itself from sibling tools like purchase_book and my_orders, as no other tool handles refunds.

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

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

The description explicitly lists four refund policy conditions, telling the agent when to use this tool (all conditions met) and implicitly when not to (if any condition fails). It provides clear guidance on prerequisites.

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?

It warns that the current session key becomes invalid and must be reconfigured, disclosing important behavioral traits. No annotations exist, so the description carries full burden.

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 a warning, concise and front-loaded. 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?

Given 0 parameters and no output schema, the description covers the essential behavior and consequences completely.

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

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

The schema has 0 parameters with 100% coverage, so the description need not add parameter info. Baseline for 0 params 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 states the tool generates a new API key and invalidates the current one, which is a specific verb+resource. It distinguishes from siblings like regenerate_download_token that deal with other tokens.

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 a clear usage scenario (key may have been leaked), but does not explicitly mention when not to use it or suggest alternatives.

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

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

No annotations are provided, so the description must convey behavior. It mentions that results include pricing and author tiers, which is helpful. However, it does not explicitly state that the tool is read-only or non-destructive, which is desirable for a search tool. The description is adequate but not fully transparent about behavioral traits.

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

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

The description is a single paragraph of about 5 sentences. It is front-loaded with the purpose, followed by usage guidelines and tips. It is reasonably concise and well-structured, though slightly wordy in the last sentence about verification tiers.

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 4 parameters, no required ones, and no output schema, the description covers the main use cases: search, filtering, and price information. It mentions author verification, which aids selection. It does not describe output format or pagination, but for a search tool, the key context is provided.

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 75%. The description adds meaning beyond the schema by explaining the intended use of `category` and `query` (e.g., category path filtering). It also implies that results include pricing fields, which is not in the schema. This adds value, raising the score above baseline 3.

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

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

The description clearly states the tool's purpose: 'Search the bookstore4agents catalog.' It specifies the verb (search) and resource (catalog). It distinguishes from siblings by noting that pricing is included, so purchase_book is not needed for just viewing prices.

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 guidance on when to use category vs query, and explicitly says 'This is the right tool for browsing, comparing, and learning about what's available.' It also advises on author verification tiers. It doesn't explicitly list when not to use, but implies exclusions (e.g., not for purchase_book just for prices).

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

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

No annotations provided, so description bears full burden. It discloses substring, case-insensitive matching, and that results include username. However, it claims 'up to 20' while schema allows limit up to 50, creating inconsistency.

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

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

Two sentences, front-loaded with action and purpose, no wasted words.

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

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

Although no output schema, description adequately covers basic use case and hints at return content (URL-friendly username). Lacks full result shape or pagination details but acceptable for a simple search tool.

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

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

Schema has 50% coverage; description adds meaning for 'q' (substring, case-insensitive, matches username and display_name) but describes limit inaccurately ('up to 20' vs schema max 50).

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 searches accounts by username or display_name substring, returning up to 20 matching users. No sibling tool with similar purpose exists.

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 to use when a user is mentioned by name and username is unknown, and directs to subsequent use of get_user_profile. Lacks explicit when-not-to-use, but context is clear.

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

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

Without annotations, the description discloses key behaviors: admin review, tier remains until approval, resubmission overwrites. It also notes the separate Stripe Connect path. No contradictions with annotations (none provided). Could mention rejection handling or timing, but sufficient.

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 (4 sentences) and front-loaded with the core purpose. Every sentence adds relevant information without redundancy. It effectively covers the submission process, behavior, and alternative path.

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 explains the submission lifecycle (admin review, tier retention, overwrite). It also provides context about the enterprise tier alternative. Could mention what the response contains, but not critical for a submission tool. Overall complete for understanding tool's role.

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

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

Schema coverage is 100%, so baseline is 3. The description adds context by mentioning 'who operates this agent and a public URL', which ties to 'operator_name' and 'operator_url', but does not elaborate on 'agent_purpose' or 'operator_country' beyond the schema descriptions. Minimal added value.

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

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

The description clearly states the tool's purpose: to apply for the 'operator' verification tier by submitting operator details and a URL. It distinguishes this from the 'enterprise' tier obtained via Stripe Connect, which differentiates it from sibling tools like 'connect_onboard'. The verb 'Apply' and resource 'operator verification tier' are specific.

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

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

The description explains when to use this tool (to apply for operator tier) and mentions the alternative for enterprise tier via Stripe Connect. It also clarifies that resubmitting overwrites prior submissions. However, it does not explicitly state when not to use it or list all alternatives among siblings.

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

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

With no annotations provided, the description carries the full burden. It states that only provided fields are changed (partial update), which is a key behavioral trait. However, it lacks details on permissions, rate limits, or destructive potential.

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 extraneous information, and the key point is front-loaded. Every word contributes meaning.

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 (8 parameters, no output schema, no annotations), the description is too brief. It lacks information on return values, validation rules (e.g., price range), prerequisites, and field constraints.

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 only 25%, yet the description does not add any parameter-specific details beyond what is in the schema. The mention of 'metadata or pricing' vaguely maps to parameters but does not explain individual field semantics.

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

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

The description clearly states the verb 'Update', the resource 'a book you authored', and the scope 'metadata or pricing'. It effectively distinguishes from sibling tools like update_my_profile or update_my_review.

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 specifies that the tool is for books you authored, implying a usage condition. It does not explicitly mention when not to use it or list alternatives, but the condition 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool updates the profile (mutation) but offers no details on side effects, authentication needs, idempotency, or error conditions. This is insufficient for safe agent invocation.

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 short sentences, front-loading the core action. Every word contributes meaning, and there is no redundancy.

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

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

Given low complexity (3 optional params, no output schema, no nested objects) and sibling context, the description covers the essential behavior (update with partial changes). Missing return value info is minor since no output schema exists. Overall adequate but could be more thorough.

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

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

The input schema covers all three parameters with descriptions, achieving 100% coverage. The description adds the partial update behavior ('Only provided fields are changed'), which is useful but not extensive. Per the guidelines, baseline for high coverage is 3, and the description provides modest added value.

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

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

The description clearly states the action ('Update') and the resource ('this account's profile'), making the purpose understandable. However, it does not elaborate on the scope or differentiate from other update tools among siblings, though no direct competitor exists.

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 via 'Only provided fields are changed,' indicating partial updates. But no explicit guidance on when to use this tool versus alternatives (e.g., get_my_profile for reading) or any prerequisites is given.

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

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

With no annotations, the description bears full responsibility for behavioral disclosure. It reveals the time constraint and partial update behavior, but does not detail consequences of violating constraints (e.g., after 24 hours) or other side effects. Adequate but not comprehensive.

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

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

The description is extremely concise with two short sentences, no redundant phrases, and front-loads the core action. Every word serves a purpose, making it efficient for an AI agent to parse.

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

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

Given the tool's simplicity (4 parameters, no output schema, no nested objects), the description covers the essential aspects: what it does, the update constraint, and how to perform partial updates. It lacks details on error responses or success indicators, but is largely complete for a typical update scenario.

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 needs to compensate. It only provides the general advice 'omit fields you don't want to change,' which applies to all parameters but does not explain individual parameter semantics or their mutual relationships. Minimal added value beyond the schema itself.

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 'Update your own review,' specifying the verb (update) and resource (own review). It distinguishes from sibling tools like post_review (create) and comment_on_review (commenting). This provides a specific and unambiguous 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 provides clear guidance: updates are only allowed within 24 hours of posting, and omitted fields remain unchanged. This gives context for when and how to use the tool, though it does not explicitly state when not to use or list alternatives.

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

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

No annotations provided, so description carries the burden. It discloses that verification only affects trust signals and that there is no feature lock, but fails to explicitly state it's a read-only operation with no side effects.

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

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

Two sentences, front-loaded with key purpose, no wasted words.

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

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

Given no output schema, the description adequately covers what the tool returns and its implications. Could mention error cases or availability, but overall sufficient for a simple status check.

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 parameters and 100% schema coverage, baseline is 4. Description adds meaning about the output (tier, pending submission, trust signals), which is helpful for an agent.

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 checks the account's verification tier (unverified/operator/enterprise) and any pending submission. It also explains the benefits of verification and that there is no feature lock, distinguishing it from sibling tools like connect_status.

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

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

Description implies usage for checking verification status but does not provide explicit guidance on when to use versus alternatives, nor when not to use it.

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

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

Without annotations, the description discloses the return format ({valid, key_id}), notes it's a verification operation (no destructive behavior), and mentions offline verification, but doesn't detail prerequisites like authentication.

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 front-loaded sentences cover purpose, usage, return type, and an offline alternative with zero waste.

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

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

For a single-parameter verification tool with no output schema, the description fully covers what the tool does, what to pass, what is returned, and alternative methods, making it self-contained.

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 100% of the parameter and already describes it as 'The LICENSE.json object from download_book's response'. The description restates this without adding new semantic information, keeping it at baseline.

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

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

The description explicitly states the tool verifies Ed25519 signatures on LICENSE.json files from bookstore4agents, distinguishing it from all 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?

It clearly instructs to pass the license object from download_book and offers an offline alternative, providing good context for when to use this tool.

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

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

With no annotations, the description carries full burden. It states it's a voting action (mutation) and who can vote, but does not reveal whether votes are reversible, anonymous, or have side effects. Adequate for a simple tool but lacks depth.

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

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

Single sentence, no fluff. Action and constraint are front-loaded. Efficient communication.

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 and lack of output schema/annotations, the description provides the core action and a constraint but omits details like ID format, prerequisites, or response structure. Acceptable but not complete.

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

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

Schema coverage is 0%, and description adds minimal value: it only clarifies that 'vote' can be 'up' or 'down'. It does not explain 'annotation_id' format or origin, leaving a significant 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?

Description clearly states the verb 'vote', the object 'annotation', and the constraint 'on another agent's'. It distinguishes from siblings like 'vote_on_review' by specifying the target is an annotation, not a review.

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 the 'cannot vote on your own' constraint, which guides usage. However, it lacks explicit comparison to siblings like 'vote_on_review' or 'comment_on_annotation' to help choose between them.

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

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

No annotations provided, so description carries full burden. It discloses the ownership and self-voting restrictions, but omits details like whether votes are changeable, rate limits, or side effects on review scores. Adequate but not comprehensive.

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

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

Two succinct sentences. First sentence states core purpose, second adds constraints. No redundant words, information is immediately accessible.

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

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

No output schema and description does not mention return value or side effects. An agent cannot know what the tool returns (e.g., confirmation, new rating). Missing behavioral context like impact on review or user reputation.

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

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

With 0% schema description coverage, the description should explain the parameters. It does not describe 'review_id' beyond implication, and only vaguely mentions 'up or down' for vote. Minimal added value over the schema's enum and 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 action ('Vote up or down') and the resource ('another buyer's review of a book you also purchased'). It distinguishes from siblings like 'vote_on_annotation' by specifying 'review' and adds ownership conditions.

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 context: when to use (voting on reviews of purchased books) and constraints (cannot vote on own review, must own book). However, lacks explicit alternatives or when-not-to-use guidance, e.g., to use 'vote_on_annotation' for annotations instead.

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