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

No annotations are provided, so the description must convey behavioral traits. It states the tool adds a connection but does not disclose side effects (e.g., is it idempotent? does it overwrite existing connections?), permissions required, or error conditions. The behavior is straightforward, but additional transparency would be helpful.

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: a one-sentence purpose followed by a clear, structured list of arguments with explanations. Every sentence adds value, and the front-loaded purpose helps the agent quickly understand the tool's function.

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

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

The tool has no output schema, and the description does not mention what the tool returns (e.g., confirmation, connection ID). It also lacks details on side effects, such as whether connections are unique or can be duplicated. For a tool with 5 parameters and no output schema, this omission reduces completeness.

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

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

The input schema has 0% description coverage, but the description provides detailed semantics for all parameters. It explains from_book and to_book as titles, relationship with four enumerated values and their meanings, reason, and strength with three allowed values. This adds significant meaning beyond the schema's bare type declarations.

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 adds a connection between two books for future recommendations. The verb 'add' and resource 'connection between two books' are specific. This distinguishes it from sibling tools like add_book_to_stack (which adds a book to a stack) and get_similar_books (which retrieves existing recommendations).

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 purpose is clear, but the description does not explicitly state when to use this tool versus alternatives (e.g., when to add a connection vs. using get_similar_books). No when-not or alternative guidance is provided, relying on the user to infer context from the purpose.

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 for behavioral disclosure. It only states 'add', implying mutation, but does not mention required permissions, side effects (e.g., overwrites?), idempotency, or what happens if the stack doesn't exist.

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

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

The description is extremely short (one sentence), but conciseness is not beneficial when essential information is omitted. It fails to earn its place by providing minimal value relative to 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?

Given the tool has 5 parameters (3 required), no output schema, and no annotations, the single-sentence description is severely inadequate. Critical details about stack existence, parameter roles, and return values are missing.

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

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

Schema description coverage is 0%, yet the description provides no explanation for any of the five parameters (domain, title, author, why, difficulty). The schema exposes required fields, but the agent cannot infer their meanings or constraints from the tool description.

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

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

The description clearly states the verb 'add' and the resource 'book to an existing stack', which conveys the core action. However, it does not differentiate from sibling tools like 'add_book_connection' or 'save_bookstack', leaving ambiguity about what 'stack' means in this context.

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

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

No guidance is provided on when to use this tool versus alternatives, nor are there any preconditions or exclusions. The word 'manually' hints at a contrast with automated processes but does not elaborate.

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

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

With no annotations, the description carries full burden. It reveals that results are saved and affect recommendations, which is useful. However, it does not detail side effects, permissions, or whether the analysis is incremental.

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: two short paragraphs with a bulleted list. Every sentence is informative and the key action 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?

Given the simplicity (no parameters, no output schema), the description adequately covers inputs (reading history) and outputs (saved results). It could be slightly more explicit about the scope (all completed books) but is largely complete.

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

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

The tool has zero parameters, so schema coverage is 100% by default. The description adds value by explaining that input is implicitly the user's reading history, which is meaningful 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?

The description uses a specific verb ('analyze') and resource ('reading history/patterns'), and the bulleted list clarifies what is analyzed. It is distinct from sibling tools like 'get_reading_log' or 'get_profile' which are retrieval-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?

The description implies usage for deeper pattern analysis after reading, but does not explicitly state when to use this tool over alternatives like 'get_reading_log' or 'get_profile'. No exclusions or context are provided.

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

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

Discloses that the tool returns a prompt and does not persist (by directing to 'save_bookstack'). With no annotations provided, the description carries the full burden. It does not mention error handling or side effects, but the behavior is clear enough for a generation 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?

Four sentences, no filler. Uses clear Args format. Every sentence adds value: purpose, parameter, return value, and follow-up action. 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?

Covers purpose, parameter, return value, and post-action. For a simple one-parameter tool with no output schema or annotations, this is sufficiently complete. Could mention error handling or domain validation, but not necessary 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?

Adds meaning to the 'domain' parameter with an example ('e.g., "classic_lit"') and indicates it is an ID. Schema coverage is 0%, so the description compensates well. No other parameters to document.

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?

Describes specific verb 'build' and resource 'curated reading stack', clearly indicating it creates a reading stack for a domain. Distinguishes from siblings like 'add_book_to_stack' and 'save_bookstack' by mentioning return of a prompt and suggesting subsequent save action.

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

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

Provides workflow guidance by instructing to call 'save_bookstack' after generating recommendations. However, it lacks explicit when-to-use or when-not-to-use guidelines, and does not compare to other tools like 'get_bookstacks' or 'add_book_to_stack'.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It does not confirm whether the tool is read-only or has side effects, nor does it explain what 'analysis' entails beyond returning results. This lack of transparency is a significant gap.

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

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

The description is two sentences, no wasted words. It conveys purpose, outputs, and follow-up action efficiently.

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

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

Given the absence of an output schema, the description adequately states what is returned (context builder prompt and current profile). However, it could provide more detail about the format of these returns or the nature of 'latent features'. Still, it is sufficient for 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?

The input schema has zero parameters with 100% coverage. No parameter descriptions are needed, so the tool meets the baseline expectation for a parameterless tool.

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

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

The description clearly states the action: 'Analyze the profile to extract latent features' and specifies the return values (context builder prompt and current profile). It distinguishes from sibling tools by mentioning a specific follow-up action (update_latent_features).

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 instructs to call update_latent_features after analysis, providing clear workflow guidance. However, it does not state when to use this tool vs alternatives, though the implied sequence is clear given the sibling set.

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

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

No annotations are present, so the description bears full burden. It mentions 'Get or create' but does not clarify whether creation is automatic, what happens if the author exists, or any side effects. Minimal behavioral context.

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

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

The description is extremely concise, with the main purpose front-loaded. The docstring format for arguments and returns is efficient and wastes no words.

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

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

For a simple tool with one parameter and no output schema, the description covers basic functionality. It mentions return fields (books read, ratings, notes) but lacks clarity on the creation aspect, which is important for completeness.

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

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

The schema coverage is 0% but the description adds an example ('Leo Tolstoy') and clarifies that 'author' is the author's name. This adds some meaning beyond the schema, though more details (e.g., case sensitivity) would improve it.

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

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

The description states 'Get or create a profile for an author,' which clearly identifies the verb (get/create) and resource (author profile). However, it does not differentiate from sibling tools like 'get_profile' or 'get_favorite_authors', though the specificity to authors helps.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'get_profile' or 'save_profile'. It lacks information on prerequisites or preferred scenarios.

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

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

No annotations are present, so the description carries the full burden. It only states the retrieval action but does not disclose safety (read-only), side effects, authentication needs, or behavior like pagination. For a getter, this is insufficient.

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

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

The description is a single, efficient sentence that front-loads the tool's purpose. No extraneous 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 and minimal description, the tool lacks completeness. It does not explain return structure, ordering, error handling, or behavior when no domain 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?

The schema has 0% description coverage. The description adds meaning by implying the 'domain' parameter filters by domain, but does not specify format, required status, or possible values.

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

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

The description clearly states the tool retrieves book stacks, with an option to filter by domain ('all' vs 'specific domain's stack'). However, it does not distinguish this tool from siblings like 'build_bookstack' or 'save_bookstack'.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, 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 exist, and the description fails to disclose behavioral traits such as authentication requirements, how favorites are determined, or whether the operation is read-only.

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 front-loaded purpose and an Args line for the parameter—efficient but somewhat sparse.

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

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

Given no output schema and one simple parameter, the description is minimally viable but omits context like what 'favorite' means or how affinity is computed.

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 minimal meaning to the 'limit' parameter (max authors, default 10), which is not present in the schema's property definition (empty description). However, schema coverage is 0%, so the description partially compensates.

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), the resource (your favorite authors), and the ranking criterion (by affinity), distinguishing it from sibling tools like get_author_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?

No guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions provided.

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

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

No annotations are provided, so the description carries the full burden. It only says 'get the next recommended book' without disclosing how recommendations are determined, whether calling this tool changes state (e.g., marks the book as 'next'), or any prerequisites. Behavioral details are absent.

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

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

The description is a single sentence, which is concise. However, it is under-specified—it does not earn its place by providing enough information. It is neither bloated nor efficiently informative.

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

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

Given the tool's complexity (one optional param, no output schema, no annotations), the description is incomplete. It does not explain what 'next' means, how the recommendation is generated, or what the return value looks like. An agent would struggle to use this tool correctly without additional context.

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

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

There is one optional parameter 'domain' with no description in the schema (0% coverage). The tool description does not mention or explain this parameter, leaving the agent without understanding how to use it. Since schema coverage is low, the description should compensate but fails to do so.

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

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

The description states 'Get the next recommended book to read' which clearly identifies the verb (Get) and resource (next recommended book). It distinguishes from sibling tools like get_similar_books and get_author_profile. However, it lacks nuance about what 'next' means.

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

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

The description provides no guidance on when to use this tool versus alternatives. No explicit when-to-use, when-not-to-use, or comparison with siblings like get_similar_books. The agent is left to infer usage from the name alone.

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

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

No annotations provided. Description does not disclose behavioral traits like authentication needs, data scope, or side effects. Only states the 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?

Single concise sentence with no waste. Front-loaded purpose.

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

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

For a simple profile retrieval with no output schema, the description is adequate but minimal. Lacks detail on what fields are returned.

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 is 100% (empty). Baseline for 0 params is 4. Description adds no parameter info, but none 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?

Description clearly states 'Retrieve the current user profile.' Specific verb+resource, and distinguishes from sibling tools which are mostly about books, reading, or building stacks.

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. Purpose is clear, but no context for exclusions or 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 are present, so the description carries full burden. It doesn't disclose whether the tool is read-only, what a 'progress summary' includes, or any behavioral traits like data freshness or limits.

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 short sentence, which is efficient but too vague to be helpful. It sacrifices necessary detail for brevity, providing minimal actionable 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 lack of an output schema, the description should explain the return format of the progress summary. It also fails to differentiate from sibling tools. The tool's complexity is low, but the description remains incomplete.

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

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

The sole parameter 'period' has a default of 'all' but no description in the schema or the tool description. Schema coverage is 0%, and the description fails to explain valid values (e.g., 'week', 'month') or the meaning of the parameter.

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

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

The description clearly states 'Get reading progress summary across all domains.' This is a specific verb+resource combination, but it doesn't differentiate from sibling tools like 'get_reading_log' or 'analyze_reading_patterns'.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'get_reading_log' or 'analyze_reading_patterns'. The description lacks context for appropriate usage conditions 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 are provided, and the description only says 'Get reading log entries.' It does not disclose whether this operation is read-only, requires authentication, or has any side effects. The description adds no behavioral context beyond the implied 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?

The description is a single short sentence, which is concise but lacks essential details. It is not wordy, but brevity here comes at the cost of clarity and completeness.

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

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

Given the tool has one optional parameter and no output schema, the description should at least hint at what reading log entries are and how 'limit' affects the result. It fails to provide sufficient context for an AI agent to use the tool effectively.

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

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

The input schema has one parameter 'limit' with no description (0% coverage). The description does not mention the parameter or explain its effect, such as whether it limits the number of entries returned. No added 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 states the verb 'Get' and resource 'reading log entries,' which is clear but very generic. It doesn't specify the scope or differentiate from sibling tools like 'get_profile' or 'get_bookstacks,' leaving ambiguity about what exactly a 'reading log' encompasses.

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. With 19 sibling tools, including 'get_progress' and 'get_next_book,' the description provides no context for selecting this tool over others.

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

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

No annotations are present, so the description must fully convey behavioral traits. It only states that the tool returns connected books, without disclosing whether it is read-only, destructive, or any side effects. This is insufficient for safe 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 sentences and an Args line. It is front-loaded with the core purpose and contains no unnecessary words or redundancies.

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 basic input and output, but lacks details on the form of the returned books (e.g., list of titles, objects). Given the absence of an output schema and the presence of many sibling tools, more specificity would improve completeness.

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

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

The description adds meaningful context to the single parameter 'title' by clarifying it must be 'a book you've read', which is not evident from the schema alone (which only shows 'Title'). This helps the agent understand the input requirement.

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 with a specific verb ('Find') and resource ('books connected to one you've read'). It distinguishes from siblings like 'get_next_book' by focusing on connectivity rather than sequential recommendation.

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

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

No guidance is provided on when to use this tool versus alternatives (e.g., 'get_next_book', 'add_book_connection'). The description does not mention exclusions or context for optimal 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 must reveal behavioral traits. It only says 'Log a completed book (quick mode)' but doesn't clarify what 'quick mode' entails, whether it creates or updates records, or what side effects occur (e.g., does it affect reading progress?). The term 'completed book' implies state changes, but details are missing.

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

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

The description is short and front-loaded with the core action. However, the inclusion of 'Args:' and the bullet list is slightly unconventional for a tool description; it could be more compact and inline. Still, it is efficient with no wasted words.

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

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

For a simple logging tool with 5 parameters and no output schema, the description is barely adequate. It does not explain return values, error conditions, or whether it requires existing book entries. Given the lack of annotations and output schema, more detail would help, but the core action is understood.

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%, so the description must compensate. It adds brief explanations like 'rating: Optional 1-5 rating' (provides range) and 'domain: Which domain this book belongs to' (vague but adds context). However, explanations are minimal and mostly restate the parameter names; e.g., 'title: Book title' adds no additional meaning. Overall, it adds some value but could be richer.

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 'Log a completed book (quick mode)', which specifies the verb (log) and resource (completed book). This distinguishes it from siblings like 'add_book_to_stack' (adds without logging completion) and 'get_reading_log' (retrieves logs).

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

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

No guidance on when to use this tool vs alternatives. It doesn't mention prerequisites (e.g., does the book need to already exist in the system?) or when 'quick mode' is appropriate. Users must infer usage from the name and parameters.

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

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

With no annotations, the description must disclose behavioral traits. It only states 'save' implying a write operation, but does not specify whether it creates or updates, or what happens on duplicate domain or existing books.

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 one sentence and a parameter list. No unnecessary words.

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

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

Given no output schema and only 3 parameters, the description lacks return value details, error handling, and behavioral specifics. A mutation tool should provide more context.

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

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

The description adds basic meaning to all three parameters (domain ID, list of book recommendations, optional description), but the 'books' parameter is defined as a generic object with no further structure, 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 clearly states 'Save a curated book stack for a domain' with a specific verb and resource. However, it does not differentiate from sibling tools like 'build_bookstack', which may also create stacks.

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 'build_bookstack' or 'add_book_to_stack'. No context for prerequisites or conditions.

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

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

With no annotations, the description must disclose behavioral traits. It clearly indicates a write operation (save), and details parameter structure, but does not mention side effects (e.g., overwriting existing profile), required permissions, or success/failure conditions. The return value is briefly noted as a confirmation.

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 fairly long but well-structured with clear sections for each parameter. However, it is not concise; some explanations could be shortened without losing clarity. The front-loading of the purpose is good, but the parameter details could be more compact.

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 4 required parameters, nested objects, and no output schema, the description covers the input structure well and mentions return value. It does not explain error handling or partial saves, but given the complexity, it is reasonably 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?

Given 0% schema coverage, the description fully compensates by explaining each parameter's structure, including sub-fields for domains, preferences, and context. It provides meaningful detail beyond the schema, such as example values and the purpose of each field.

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 saves the user's reading profile and specifies it is used after an interview. The verb 'save' is specific and distinguishes from siblings like 'get_profile' (retrieval) and 'start_interview' (initiation), though it does not explicitly contrast all siblings.

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

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

The description implicitly suggests use after an interview via the phrase 'after the interview', but does not explicitly state when to use vs alternatives, nor provide any when-not-to-use guidance. More explicit context about its role in the reading profile pipeline would help.

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

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

No annotations provided; description fails to disclose behavioral traits such as whether saving is idempotent, overwrites existing reflections, or requires specific permissions. Only lists parameters without operational details.

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

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

Description is concise with purpose stated upfront. Bullet list for parameters is clear, though 'Args:' label is slightly wasteful. Overall 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?

Moderate complexity with 6 parameters; description adequately explains each but misses behavioral context like return value or side effects. No output schema exacerbates the gap.

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?

Despite 0% schema coverage, description adds brief but helpful comments for all 6 parameters (e.g., 'One sentence distillation' for key_takeaway, valid values for next_appetite). Adds meaning beyond parameter names.

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

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

Description clearly states 'Save a deep reflection for a book' using specific verb and resource. Distinguishes from sibling tools like 'start_reflection' which likely initiates rather than saves.

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

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

No explicit guidance on when to use this tool versus alternatives like 'start_reflection' or 'log_book'. The description implies it's for saving after reading, but does not provide context for selection.

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

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

No annotations are provided, so the description must cover behavioral traits. It states the tool returns a prompt, implying a read-like operation, but does not disclose if it modifies any state (e.g., creating a session). For a tool that 'begins' something, behavioral impact is relevant but unaddressed.

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 redundant words. The first sentence clearly states the action and outcome. Every sentence serves a purpose.

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

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

Given the tool has no parameters and an output schema exists (implied by 'has output schema: true'), the description sufficiently covers purpose, return value, and usage context. No additional information is needed for an agent to use this tool correctly.

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

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

The input schema has zero parameters with 100% coverage, so no parameter explanation is needed. The description adds no parameter info, which is appropriate given the empty schema. 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 tool name 'start_interview' clearly indicates the action. The description specifies 'Begin the reading goal interview' and describes the return value as 'the interview prompt to guide the conversation'. It distinguishes itself from sibling tools like 'start_reflection' and others by focusing on the initial interview setup.

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 this tool: 'when the user says "interview me" or "set up my profile"'. This provides clear trigger phrases. However, it does not mention when not to use it or alternative tools, but the specificity is sufficient for a single-purpose 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 exist, so the description must fully disclose behavior. It fails to explain what starting a reflection session entails—no side effects, required states, or return values are mentioned.

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

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

The description is a single concise sentence with no wasted words. However, it is so brief that it sacrifices completeness; a touch more detail could greatly improve it without losing conciseness.

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

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

Given the tool's simplicity (one param, no output schema, no annotations), the description is incomplete. It doesn't explain the output or behavior of the reflection session, leaving gaps that could confuse an AI agent.

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

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

The only parameter 'title' is implicit in the description as the book title, but no details are given about format, existence requirements, or how it interacts with the system. With 0% schema coverage, more explanation is needed.

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

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

The description clearly states the tool starts a deep reflection session for a book, using a specific verb and resource. It implicitly distinguishes from sibling tools like save_reflection and log_book by focusing on starting rather than saving or logging.

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

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

No guidance is provided on when to use this tool versus alternatives. With many sibling tools, explicit context about prerequisites or conditions (e.g., when a book must exist) would help the agent decide.

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

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

With no annotations, the description carries the full burden. It indicates a write operation but leaves out details about potential side effects, required permissions, or whether updates are incremental or full replacements. This lack of disclosure limits an agent's understanding of behavioral consequences.

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 relatively concise and structured with an Args section. The lead sentence immediately conveys the tool's purpose. Minor verbosity from the Args formatting does not detract significantly.

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 parameter set and no output schema, the description covers the essential inputs. However, it omits details about behavior such as whether updates are additive or whether non-existent authors are created, leaving some contextual gaps.

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

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

The description compensates for the 0% schema coverage by explaining each parameter in detail, especially 'style_notes' with its expected dictionary keys (prose, themes, strengths, comparable_to). This adds significant meaning beyond the raw schema types.

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 updates notes about an author's style and impressions. It specifies the resource (author notes) and the action (update). However, it doesn't differentiate from siblings like 'save_reflection' or 'get_author_profile', though the purpose is specific enough.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'save_reflection' or 'get_author_profile'. The description merely explains what the tool does without contextual usage tips.

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 bears full responsibility for behavioral disclosure. While it indicates a write operation ('update'), it does not specify whether the merge or replaces, any side effects, permissions required, or expected response. This is a significant gap for a mutation 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 concise with only three lines, front-loaded with the main purpose. The 'Args' line is helpful but somewhat redundant. Could be slightly tighter, but overall 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 the tool has one parameter and no annotations or output schema, the description covers the core functionality but lacks details on behavioral aspects (e.g., does it merge or replace?), error handling, and return value. It is minimally viable but incomplete for complex interactions.

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

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

The schema has 0% description coverage (no description in schema), but the tool description includes an 'Args' line explaining the 'features' parameter as 'Dictionary of latent features extracted from analysis'. This adds context beyond the type definition, though it does not detail the dictionary's structure or constraints. Baseline for low coverage is 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 verb 'update' and the resource 'profile with latent features'. It distinguishes from sibling tools like 'save_profile' and 'update_author_notes' by specifying 'latent features', indicating a specific update operation. However, the term 'latent features' could be more explicitly defined.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as 'save_profile' or 'analyze_reading_patterns'. It does not mention prerequisites, exclusions, or typical use cases. This leaves the agent without context for appropriate invocation.

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