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 does well by mentioning input validation failures and runtime errors, and clarifies the content parameter's dual purpose (text for self posts, URL for link posts). However, it doesn't address important behavioral aspects like authentication requirements, rate limits, whether the operation is idempotent, or what specific information the return dictionary contains.

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 clear sections (Args, Returns, Raises) and front-loads the core purpose. Every sentence adds value, though the formatting with section headers could be slightly more concise. The information density is high with minimal 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 5-parameter mutation tool with no annotations and no output schema, the description does an excellent job covering parameter semantics and basic error conditions. It falls short of a perfect score because it doesn't fully describe the return value (only states it's a 'dictionary containing information about the created post' without specifying what information) or address authentication/rate limiting concerns that are important for API tools.

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 description coverage, the description fully compensates by providing detailed semantic information for all 5 parameters. It explains what each parameter represents, includes constraints (max 300 characters for title), clarifies format options (with/without 'r/' prefix for subreddit), explains the dual nature of the content parameter, and specifies requirements (flair must be available in the subreddit).

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

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

The description clearly states the specific action ('Create a new post') and target resource ('in a subreddit'), distinguishing it from sibling tools that are primarily read operations (like get_submission_by_id, get_top_posts) or other actions (like reply_to_post, join_subreddit). The verb+resource combination is precise and unambiguous.

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

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

The description provides clear context about when to use this tool (to create posts in subreddits) and implicitly distinguishes it from sibling tools that retrieve or interact with existing content. However, it doesn't explicitly state when NOT to use it or name specific alternatives for similar operations, keeping it from a perfect score.

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 effectively describes the tool's behavior: it retrieves structured submission information, optionally includes comments with configurable limits, and raises specific exceptions (ValueError for invalid IDs, RuntimeError for other errors). However, it doesn't mention rate limits, authentication requirements, or whether the operation is idempotent.

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 appropriately structured with clear sections (Args, Returns, Raises), but it's quite lengthy due to the detailed return structure documentation. While this information is valuable, it could be more front-loaded; the core purpose is clear in the first sentence, but the extensive return documentation might be better placed in an output schema.

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 of a Reddit submission retrieval tool with 3 parameters and no output schema, the description is exceptionally complete. It covers purpose, parameter semantics, return structure in detail, and error conditions. The detailed return documentation compensates for the lack of output schema, making this fully self-contained for an AI agent.

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

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

The schema description coverage is 0%, so the description must fully compensate. It provides detailed semantics for all three parameters: submission_id (accepts URL or ID), include_comments (loads comment forest), and comment_replace_more_limit (controls MoreComments replacement). This adds significant value beyond the bare schema, explaining what each parameter does and how they interact.

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: 'Get a Reddit submission by its ID.' It specifies the exact resource (Reddit submission) and action (retrieve), and distinguishes it from siblings like get_submission_by_url (which uses URL instead of ID) and get_top_posts (which lists posts rather than retrieving a specific one).

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

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

The description provides clear context for when to use this tool: to retrieve a specific Reddit submission by ID. It distinguishes from get_submission_by_url by noting the submission_id parameter 'can be full URL or just ID,' but doesn't explicitly state when to choose this over alternatives like search_posts or when not to use it (e.g., for bulk retrieval).

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

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

With no annotations provided, the description carries full burden and does well by documenting error conditions (ValueError for invalid URLs, RuntimeError for other errors) and the detailed return structure. It explains what data is fetched and when comments are included, though it doesn't mention rate limits, authentication needs, or performance characteristics.

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 appropriately front-loaded with the core purpose, but the extremely detailed return structure (40+ fields) could be streamlined. While the return documentation is valuable, it occupies significant space that might be better in an output schema. The Args/Returns/Raises structure is clear but verbose.

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

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

Given no annotations, 0% schema coverage, and no output schema, the description provides complete context: clear purpose, detailed parameter explanations, comprehensive return structure documentation, and error conditions. For a 3-parameter tool with rich return data, this description leaves minimal gaps for agent understanding.

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 fully. It provides excellent parameter semantics: explains what 'url' represents, clarifies that 'include_comments' loads the full comment forest, and defines 'comment_replace_more_limit' with specific values (0 for none, None for all). This adds substantial meaning beyond the bare schema.

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

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

The description clearly states the specific action ('Get a Reddit submission') and resource ('by its URL'), distinguishing it from sibling tools like get_submission_by_id (which uses ID instead of URL) and get_top_posts (which retrieves multiple posts). The verb 'retrieve' is precise and the scope is well-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 implies usage context through the parameter explanations (e.g., include_comments for loading comments), but doesn't explicitly state when to use this tool versus alternatives like get_submission_by_id or search_posts. It provides clear parameter guidance but lacks explicit sibling differentiation in the main description text.

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 adds value by mentioning error conditions ('Raises' section) and clarifying the parameter format ('with or without 'r/' prefix'), but it doesn't cover aspects like rate limits, authentication needs, or what specific information is returned, which are gaps for a tool with no annotations.

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

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

The description is appropriately sized and front-loaded, with the core purpose stated first. The structured sections (Args, Returns, Raises) add clarity without redundancy. However, the 'Raises' section could be more concise, and the overall text is slightly verbose for such a simple tool.

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

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

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose, parameter semantics, and error handling, but lacks details on return value structure or behavioral traits like rate limits, making it incomplete for optimal agent 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 schema description coverage is 0%, so the description must compensate. It adds meaning by explaining the 'subreddit_name' parameter format ('with or without 'r/' prefix'), which goes beyond the schema's basic type. However, it doesn't detail constraints like length or valid characters, leaving some semantics uncovered.

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

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

The description clearly states the verb 'Get' and resource 'information about a subreddit', making the purpose explicit. However, it doesn't distinguish this tool from sibling tools like 'get_subreddit_stats' or 'get_trending_subreddits', which also retrieve subreddit-related data, so it lacks sibling differentiation.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'get_subreddit_stats' or 'get_trending_subreddits', nor does it specify prerequisites or exclusions, leaving usage context implied at best.

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 effectively describes the tool's behavior by detailing the return structure, including fields like 'user_is_banned' and 'mod_permissions' that imply authentication context, and specifies error conditions ('Raises: ValueError, RuntimeError'), adding valuable context beyond basic functionality.

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 clear sections (Args, Returns, Raises) and front-loaded purpose. However, the detailed return structure is lengthy; while informative, it could be more concise by summarizing key fields rather than listing all, but it remains organized and each part 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's complexity (single parameter but rich return data), no annotations, and no output schema, the description is highly complete. It fully documents the parameter, provides a detailed return structure with nested objects, and specifies error handling, making it sufficient for an agent to understand and 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 schema description coverage is 0%, so the description must compensate. It adds significant meaning beyond the input schema by explaining the 'subreddit' parameter: 'Name of the subreddit (with or without 'r/' prefix)', clarifying format and usage. This fully documents the single parameter, compensating for the lack of 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 tool's purpose with a specific verb ('Get') and resource ('statistics and information about a subreddit'), distinguishing it from siblings like 'get_subreddit_info' (which might return different data) and 'get_trending_subreddits' (which focuses on trending rather than specific subreddit stats). The title 'null' is irrelevant as the description stands alone.

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

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

The description implies usage by specifying it retrieves 'statistics and information about a subreddit', but does not explicitly state when to use this tool versus alternatives like 'get_subreddit_info' or 'get_top_posts'. No exclusions or prerequisites are mentioned, leaving the agent to infer context from the tool name and description alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It partially succeeds by documenting the return structure and error conditions (Raises section), but misses critical details like rate limits, authentication requirements, or whether this is a read-only operation. The behavioral context is incomplete for a tool with 5 parameters.

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 clear sections (Args, Returns, Raises) and front-loads the core purpose. While comprehensive, some details in the Returns section could be more concise, but overall it maintains good information density with minimal wasted text.

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 (5 parameters, no annotations, no output schema), the description provides substantial context including parameter semantics, return structure, and error conditions. However, it lacks behavioral aspects like rate limits or authentication needs, preventing a perfect score despite strong coverage elsewhere.

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 fully compensates by providing detailed semantic explanations for all 5 parameters. Each parameter gets clear documentation of its purpose, format constraints, and special values (e.g., 'with or without r/ prefix', '0 for none, None for all'), adding substantial value beyond the bare schema.

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

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

The description clearly states the specific action ('Get top posts') and target resource ('from a subreddit'), distinguishing it from sibling tools like search_posts or get_submission_by_id. It precisely communicates the tool's function without being tautological.

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 like search_posts or get_submission_by_id. It lacks context about appropriate use cases, prerequisites, or comparisons with sibling tools, leaving the agent without selection criteria.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions error handling (Raises section) and the return format (dictionary with basic info), which adds value beyond the input schema. However, it lacks details on rate limits, authentication needs, or what 'trending' means algorithmically, leaving gaps in behavioral understanding.

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, starting with a clear purpose statement followed by organized sections for Args, Returns, and Raises. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 low complexity (1 optional parameter) and lack of annotations/output schema, the description is adequate but has clear gaps. It covers the parameter and basic return format but doesn't explain the 'basic info' structure or provide full behavioral context (e.g., what 'trending' entails). This meets minimum viability but could be more complete.

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

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

The description adds significant meaning beyond the input schema, which has 0% coverage. It explains that 'limit' controls the maximum number of trending subreddits returned, specifies the valid range (1-50), and notes it's optional with a default of 5 (implied from schema). This compensates well for the schema's lack of descriptions, though it doesn't detail the structure of the returned basic info.

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 ('Get') and resource ('currently trending subreddits'), making it immediately understandable. It distinguishes itself from siblings like get_subreddit_info or get_top_posts by focusing on trending content rather than specific subreddit details or top posts. However, it doesn't explicitly contrast with all siblings, keeping it at a 4 rather than a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer get_trending_subreddits over get_top_posts or search_posts for discovering content, nor does it specify any prerequisites or exclusions. This lack of context leaves the agent without clear usage direction.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some context by detailing the return structure and error cases (Raises section), which helps the agent understand output format and potential failures. However, it lacks critical behavioral traits like authentication requirements, rate limits, or data freshness, which are essential 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 front-loaded with a clear purpose statement, but it becomes overly verbose by including a full return structure dictionary, which could be summarized or moved to an output schema. The 'Args' and 'Returns' sections are helpful but lengthy, reducing efficiency. Some sentences, like the detailed comment fields, don't earn their place in a tool description meant for agent selection.

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 (4 parameters, no annotations, no output schema), the description is mostly complete. It covers parameters thoroughly, explains the return structure in detail, and includes error cases. However, it misses behavioral aspects like authentication or rate limits, and the verbose return details could be optimized, but it's sufficient for the agent to understand the tool's function and outputs.

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 significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose, provides examples (e.g., 'with or without 'u/' prefix' for username), lists valid values for 'sort' and 'time_filter', and specifies the range for 'limit'. This fully compensates for the schema's lack of documentation, making parameters clear and actionable.

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: 'Get a user's comment history.' It specifies the verb ('Get') and resource ('user's comment history'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_user_posts' or 'get_user_info,' which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_user_posts' for posts instead of comments, or 'get_user_info' for general user data. There's no context about prerequisites, such as authentication needs or rate limits, leaving the agent with no usage differentiation.

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 and does so effectively by documenting the return structure, error conditions (ValueError for invalid usernames, RuntimeError for other errors), and the specific data fields included. It provides comprehensive behavioral context beyond basic functionality.

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 appropriately sized but not optimally structured. While the initial sentence clearly states the purpose, the detailed return structure documentation (while valuable) makes it somewhat dense. Every sentence earns its place, but the information could be more front-loaded with the core purpose emphasized before the detailed return format.

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 moderate complexity (single parameter, no output schema, no annotations), the description provides complete context. It covers purpose, parameter meaning, return structure with all fields documented, and error conditions. For a read-only data retrieval tool, this is comprehensive and leaves no significant gaps for agent understanding.

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 significant value beyond the input schema, which has 0% description coverage. It explains that the 'username' parameter refers to 'The username of the Reddit user to get info for,' providing essential semantic context that the schema's title alone doesn't convey. For a single parameter with no schema descriptions, this is highly valuable.

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 ('Get') and resource ('information about a Reddit user'), distinguishing it from siblings like get_user_comments or get_user_posts which retrieve different types of user data. It precisely defines what information is retrieved rather than just restating the tool name.

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

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

No guidance is provided on when to use this tool versus alternatives like get_user_comments or get_user_posts, nor are there any prerequisites or contextual usage instructions mentioned. The description only explains what the tool does, not when it should be selected over other available tools.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so effectively. It describes the return structure in detail, specifies error conditions with 'Raises' (ValueError for invalid inputs, RuntimeError for other errors), and mentions the data fetching timestamp. However, it doesn't cover rate limits, authentication needs, or pagination behavior, leaving some gaps.

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

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

The description is well-structured with clear sections (Args, Returns, Raises) and front-loads the core purpose. However, the detailed return structure explanation is lengthy; while informative, it could be more concise by summarizing key fields rather than listing all 20+ attributes, especially since there's no output schema.

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 moderate complexity (4 parameters, no annotations, no output schema), the description is mostly complete. It covers purpose, parameters, return structure, and errors. However, it lacks information on behavioral aspects like rate limits, authentication requirements, and whether the tool is read-only or has side effects, which would enhance 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 significant value beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: 'username' accepts Reddit usernames with or without prefix, 'sort' lists valid options, 'time_filter' specifies time periods, and 'limit' defines the range (1-100). This compensates fully for the schema's lack of descriptions.

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

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('user's post/submission history'), making it immediately understandable. It distinguishes itself from siblings like 'get_user_comments' (which focuses on comments) and 'get_user_info' (which provides profile information), establishing a clear functional boundary.

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 through parameter explanations but doesn't explicitly state when to use this tool versus alternatives. For example, it doesn't compare with 'search_posts' (which might search across users) or 'get_top_posts' (which might get popular posts regardless of user). The guidance is functional but lacks explicit contextual boundaries.

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 mentions potential errors (ValueError, RuntimeError) and the return format (dictionary with action and subreddit info), which adds useful context. However, it lacks details on permissions, rate limits, or side effects (e.g., impact on user profile).

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 the core purpose in the first sentence. Subsequent sections (Args, Returns, Raises) are organized efficiently, with each sentence providing essential information without redundancy. No wasted words.

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

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

Given the tool's moderate complexity (mutation with two parameters) and no annotations or output schema, the description is largely complete: it covers purpose, parameters, returns, and errors. However, it lacks details on authentication needs or rate limits, which are important for a mutation tool.

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

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

The schema description coverage is 0%, so the description must compensate. It fully explains both parameters: 'subreddit_name' (name with or without 'r/' prefix) and 'unsubscribe' (if True, leave instead of join). This adds critical meaning beyond the bare schema, clarifying format and default 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's purpose with specific verbs ('join/subscribe to' and 'leave/unsubscribe from') and identifies the resource ('a subreddit'). It distinguishes this tool from all sibling tools, which are primarily read-only or posting tools, by being the only one that modifies subscription 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?

The description implicitly provides usage context by explaining the dual functionality (join vs. leave based on the 'unsubscribe' parameter). However, it does not explicitly state when to use this tool versus alternatives (e.g., no comparison to other subscription-related tools, though none exist among siblings), nor does it mention prerequisites like authentication or rate limits.

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

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

With no annotations provided, the description carries full burden. It discloses the mutation nature ('Post a reply'), character limits (1-10000 characters), return format (dictionary with reply and parent info), and error conditions. However, it doesn't mention authentication requirements, rate limits, or whether replies are editable/deletable.

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?

Well-structured with clear sections (Args, Returns, Raises) and front-loaded purpose statement. The parameter explanations are efficient but could be slightly more concise by combining format options for comment_id into a single phrase.

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 mutation tool with no annotations and no output schema, the description does well by covering purpose, parameters, return format, and error cases. It could improve by mentioning authentication needs or whether this creates publicly visible content, but overall provides substantial 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?

With 0% schema description coverage, the description fully compensates by explaining both parameters: comment_id accepts multiple formats (URL, permalink, or ID) and content has character constraints (1-10000). This adds crucial semantic information beyond the bare schema.

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

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

The description clearly states the specific action ('Post a reply') and target resource ('to an existing Reddit comment'), distinguishing it from sibling tools like 'reply_to_post' which targets posts instead of comments. The verb+resource combination is precise and unambiguous.

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

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

The description implies usage context by specifying it's for replying to comments, but doesn't explicitly state when to use this versus alternatives like 'reply_to_post' or other comment-related tools. It provides clear prerequisites (needs comment_id and content) but lacks explicit exclusion guidance.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context beyond basic functionality: it specifies return format ('Dictionary containing information about the created reply and parent post'), error conditions ('Raises: ValueError, RuntimeError'), and content length constraints ('1-10000 characters'). However, it lacks details on permissions, rate limits, or side effects like post visibility changes.

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 the core purpose, followed by organized sections (Args, Returns, Raises). Every sentence adds value: the opening defines the tool, and subsequent sections provide essential operational details without redundancy. It's appropriately sized for a 3-parameter tool with no annotations.

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 annotations and no output schema, the description does a strong job covering basics: purpose, parameters, returns, and errors. However, for a mutation tool (posting a reply), it lacks details on authentication needs, rate limits, or confirmation of success/failure states beyond error mentions. It's mostly complete but has minor gaps in operational 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 0%, so the description must compensate fully. It adds significant meaning beyond the schema: it explains that 'post_id' accepts multiple formats ('full URL, permalink, or just ID'), specifies character limits for 'content' ('1-10000 characters'), and clarifies that 'subreddit' is optional and used 'for validation, with or without 'r/' prefix'. This provides crucial usage context not in the schema.

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

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

The description clearly states the specific action ('Post a reply') and target resource ('to an existing Reddit post'), distinguishing it from sibling tools like 'reply_to_comment' (for comments) and 'create_post' (for new posts). The verb+resource combination is precise and unambiguous.

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

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

The description implies usage context by specifying it's for replying to 'an existing Reddit post', which naturally excludes creating new posts or replying to comments. However, it doesn't explicitly state when to use this tool versus alternatives like 'reply_to_comment' or provide any exclusions or prerequisites beyond the implied scope.

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 effectively describes the tool's behavior: it performs a search operation (implying read-only, non-destructive), specifies error conditions ('Raises: ValueError, RuntimeError'), and details the return structure. This provides comprehensive behavioral context beyond basic functionality.

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 clear sections (Args, Returns, Raises) and efficiently explains parameters and return values. However, it could be more front-loaded; the core purpose is stated first, but the detailed parameter explanations follow immediately, making it slightly dense. Every sentence earns its place, but some redundancy exists in explaining the return dictionary 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?

For a tool with no annotations, no output schema, and 0% schema description coverage, the description is highly complete. It covers purpose, all parameters with semantics, detailed return structure, and error conditions. This provides the agent with all necessary information to correctly invoke and interpret results from this 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?

Given 0% schema description coverage, the description fully compensates by explaining all 5 parameters in detail. It clarifies semantics such as optional subreddit filtering, sort options, time filter meanings, and limit range. This adds significant value beyond the bare schema, which only lists parameter names and types without 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 clearly states the tool's purpose: 'Search for Reddit posts using a search query.' It specifies the verb ('search') and resource ('Reddit posts'), but does not explicitly differentiate from sibling tools like 'get_top_posts' or 'get_submission_by_id', which also retrieve posts. The purpose is clear but lacks sibling 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 implies usage through parameter explanations (e.g., 'If None, searches all of Reddit'), but does not explicitly state when to use this tool versus alternatives like 'get_top_posts' for non-search-based retrieval or 'get_submission_by_id' for specific posts. It provides context for parameter choices but lacks direct guidance on tool selection.

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

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

With no annotations provided, the description carries full burden and does an excellent job disclosing behavioral traits. It specifies authentication requirements through the 'Raises' section, describes the complete return structure in detail, and documents error conditions. The only minor gap is lack of rate limit or performance characteristics.

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 appropriately front-loaded with the core purpose, but the extensive return value documentation (25+ fields) could be considered verbose for a description. While valuable, it might be better placed in an output schema. The structure is logical but not maximally concise.

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

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

For a zero-parameter read operation with no annotations and no output schema, the description provides exceptional completeness. It covers purpose, authentication requirements, detailed return structure, and error conditions - everything an agent needs to understand and invoke 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 tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description correctly states no parameters are needed ('currently authenticated user' implies no input required), which aligns perfectly with the empty input schema.

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

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

The description clearly states the specific action ('Get information about') and resource ('currently authenticated user'), distinguishing it from sibling tools like get_user_info which presumably fetches information about other users. The purpose is immediately apparent in the first sentence.

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 context through 'currently authenticated user' and the error handling section mentioning authentication requirements, providing clear when-to-use guidance. However, it doesn't explicitly contrast with alternatives like get_user_info or state 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.