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 behavioral traits such as the requirement to follow specific design rules (e.g., dimensions, player spawn, tile types), difficulty settings, and playability constraints. It doesn't mention performance, rate limits, or error handling, but covers core operational behavior adequately.

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. It front-loads the purpose and rules, but includes extensive guidelines and parameter explanations that could be streamlined. Every sentence adds value, but the organization could be more efficient, with some redundancy in design rules.

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

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

Given the complexity (8 parameters, no annotations, 0% schema coverage) and the presence of an output schema (which handles return values), the description is complete. It covers purpose, usage, behavioral traits, and parameter semantics thoroughly, providing all necessary context for an AI agent to select and invoke the tool correctly without relying on structured fields.

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

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

Schema description coverage is 0%, so the description must compensate. It adds significant meaning beyond the input schema by explaining each parameter's role in level design: level_name and description for identification, tiles as a 2D array of tile types with mappings (0-7), width and height as dimensions with defaults, and maxEnemies, enemySpawnChance, coinSpawnChance for difficulty tuning with guidelines. This fully documents all 8 parameters.

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

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

The description explicitly states the tool's purpose: 'creating fast, fun, and playable levels for the VibeTide 2D platformer game.' It specifies the verb ('create') and resource ('levels'), and distinguishes it from siblings like edit_entire_level or view_level by focusing on creation rather than modification or viewing.

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

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

The description provides explicit usage guidelines, including when to use it (e.g., for designing levels with specific dimensions and rules) and when not to use it (e.g., not for mazes). It distinguishes from siblings by emphasizing creation over editing or viewing, and includes detailed design rules and difficulty parameters to guide usage.

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

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

No annotations are provided, so the description carries the full burden. It states the tool returns 'decoded level data with visualization,' which adds some behavioral context about the output. However, it lacks details on potential errors (e.g., invalid URLs), performance aspects, or side effects, which are important for a decoding operation with no annotation coverage.

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

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

The description is well-structured and concise: a clear purpose statement followed by brief Arg and Return sections. Every sentence adds value without redundancy. It could be slightly more front-loaded by integrating the return info into the main statement, but overall it's 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's moderate complexity (decoding from URLs), the description covers the core purpose and parameter semantics adequately. The presence of an output schema means the description doesn't need to detail return values, and it appropriately focuses on the decoding process. It could improve by addressing error cases or sibling differentiation.

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 for the single parameter: 'encoded_level' is described as 'The encoded level string from a URL or sharing link.' This clarifies the parameter's purpose and format beyond the schema's minimal title ('Encoded Level') and 0% coverage. With only one parameter, this provides adequate semantic value.

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

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

The description clearly states the tool's purpose: 'Decode a VibeTide level from an encoded URL string.' It specifies the verb ('decode'), resource ('VibeTide level'), and source ('encoded URL string'). However, it doesn't explicitly differentiate from siblings like 'view_level' or 'play_level' beyond the URL decoding aspect.

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 mentioning 'URL or sharing link,' suggesting this tool is for processing shared/encoded levels rather than direct access. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'view_level' or 'play_level,' nor does it mention any 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 provided, so the description carries full burden. It states the tool edits and replaces content, implying mutation, but lacks details on permissions, side effects (e.g., overwriting existing data), error handling, or rate limits. The mention of 'Returns the completely modified level data' adds some behavioral context, but it's minimal 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 well-structured and appropriately sized, with a clear opening sentence stating the purpose, followed by a detailed parameter list. Every sentence adds value, though the parameter explanations could be slightly more concise (e.g., combining similar optional fields).

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 (7 parameters, mutation tool, no annotations) and an output schema (which handles return values), the description is reasonably complete. It covers the purpose and parameters thoroughly, but lacks usage guidelines and behavioral details like error cases or prerequisites, leaving some gaps for the 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 description adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose, constraints (e.g., tile types 0-7, ranges for percentages), and optionality, effectively compensating for the schema's lack of documentation and providing essential context for correct usage.

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

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

The description clearly states the tool's purpose: 'Edit an entire VibeTide level, replacing all tiles and optionally metadata.' It specifies the verb ('edit'), resource ('VibeTide level'), and scope ('entire'), but doesn't explicitly differentiate from siblings like edit_level_metadata or edit_level_tile, which likely handle partial edits.

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 siblings like edit_level_metadata and edit_level_tile that handle partial edits, the description doesn't indicate that this tool is for complete replacements or when that's preferable, leaving the agent to infer usage from the name and parameters 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 are provided, so the description carries the full burden. It discloses that the tool modifies level data (implied mutation) and returns modified data, but lacks details on permissions, error handling, or side effects. The description adds some behavioral context (efficiency comparison, optional parameters) but doesn't fully cover traits like safety or constraints beyond what's implied by 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?

The description is well-structured and front-loaded: the first sentence states the purpose, the second provides usage guidelines, followed by clear sections for arguments and returns. Every sentence adds value without redundancy, making it efficient and easy to parse.

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

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

Given the tool's complexity (mutation with 6 parameters) and no annotations, the description does well by covering purpose, usage, parameters, and returns. However, it lacks details on behavioral traits like error conditions or side effects. The presence of an output schema (implied by 'Returns' section) helps, but some gaps remain 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?

Schema description coverage is 0%, so the description must compensate. It provides a detailed 'Args' section explaining each parameter's purpose, including optional status, data types (e.g., string, integer, number), and value ranges (e.g., '0-10', '0-100'). This adds significant meaning beyond the bare schema, fully documenting all 6 parameters.

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

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

The description clearly states the tool's purpose: 'Edit only the metadata of a VibeTide level without changing the tile layout.' It specifies the verb ('edit'), resource ('metadata of a VibeTide level'), and scope ('without changing the tile layout'), and distinguishes it from sibling edit_entire_level by emphasizing efficiency for metadata-only changes.

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

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

The description provides explicit guidance on when to use this tool versus alternatives: 'This is much more efficient than edit_entire_level when you only want to change game parameters like enemy count, spawn rates, name, or description.' It names the alternative tool and specifies the use case (metadata-only changes), offering clear 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool modifies level data by replacing an entire row, which implies mutation, but doesn't cover permissions, side effects, error handling, or rate limits. The return statement is helpful but minimal. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is efficiently structured with a clear purpose statement, bullet-point parameter explanations, and a return value note. Every sentence adds value: the first defines the tool, the Args section clarifies parameters, and the Returns statement completes the picture. No wasted words, and information is front-loaded appropriately.

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 3 parameters with 0% schema coverage but good description compensation, and an output schema exists (so return values needn't be detailed), the description is moderately complete. However, as a mutation tool with no annotations, it lacks critical behavioral context like error conditions or side effects. The presence of an output schema raises the baseline, but gaps remain for safe agent invocation.

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

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

The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains 'encoded_level' comes from 'a URL or sharing link', clarifies 'row' is '0-based, from top', and specifies 'new_row_tiles' values are 'tile types' with range '0-7'. This compensates well for the schema's lack of descriptions, though it doesn't detail array length constraints or validation rules.

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 ('Edit an entire row') and resource ('in a VibeTide level'), making the purpose immediately understandable. It distinguishes from siblings like 'edit_level_tile' (single tile) and 'edit_entire_level' (whole level), though it doesn't explicitly name these alternatives. The verb+resource combination is specific but could be more precise about the scope of editing.

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 'edit_level_tile' or 'edit_entire_level'. It mentions the source of 'encoded_level' (URL or sharing link) but doesn't explain prerequisites, error conditions, or contextual constraints. Usage is implied through parameter descriptions but not explicitly stated.

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 tool modifies a level (implied mutation) and returns modified data, but lacks details on permissions, side effects, error conditions, or rate limits. The behavioral disclosure is basic but adequate for the core 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 efficiently structured with a clear purpose statement followed by parameter explanations and return value. Every sentence adds value, with no redundant or unnecessary information. The formatting with Args/Returns sections enhances readability without verbosity.

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

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

Given 4 parameters with 0% schema coverage and an output schema present, the description provides good parameter context and states the return purpose. It covers the essential what/how for a tile-editing operation, though could benefit from more behavioral details given the mutation nature and lack of annotations.

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

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

Schema description coverage is 0%, so the description must compensate. It provides meaningful context for all 4 parameters: encoded_level source, row/col indexing (0-based), and new_tile_type range/legend reference. This adds substantial value beyond the bare schema, though tile legend details aren't fully explained.

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 ('Edit a single tile'), target resource ('in a VibeTide level'), and distinguishes from siblings like edit_entire_level, edit_level_row, and edit_level_metadata by specifying it's for a single tile. 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 when modifying individual tiles in a level, but doesn't explicitly state when to use this vs. alternatives like edit_entire_level or edit_level_row. No guidance on prerequisites or exclusions is provided, leaving usage context partially inferred rather than clearly defined.

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 that the tool returns information (a read operation) and covers 'all available tile types,' indicating comprehensiveness. However, it lacks details on rate limits, authentication needs, or error behaviors. It adds some context but doesn't fully compensate for the absence of 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 two concise sentences with zero waste: the first states the purpose, and the second clarifies the return value. It's front-loaded and appropriately sized, earning its place by efficiently conveying essential information without redundancy.

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

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

Given the tool's low complexity (0 parameters, read-only operation) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers what the tool does and what it returns, though it could benefit from more behavioral context (e.g., caching or performance notes) to reach a 5.

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

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

The tool has 0 parameters, and schema description coverage is 100% (though empty). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for zero-parameter tools. It appropriately focuses on the tool's purpose without unnecessary parameter details.

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 the reference guide for VibeTide tile types' specifies the verb (get) and resource (reference guide for tile types). It distinguishes from siblings like 'edit_level_tile' or 'view_level' by focusing on reference information rather than level manipulation. However, it doesn't explicitly contrast with all siblings, so it's not a perfect 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 implies usage context through 'reference guide' and 'information about all available tile types and their properties,' suggesting this is for lookup/learning rather than editing. However, it doesn't explicitly state when to use this vs. alternatives like 'view_level' (which might show tiles in context) or provide clear exclusions. The guidance is implied but not explicit.

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 of behavioral disclosure. It states the tool returns a URL but doesn't cover aspects like whether it's a read-only operation, if it requires authentication, rate limits, or error handling. The description is minimal and misses key behavioral traits for a tool that likely interacts with a web service.

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 highly concise and well-structured: it starts with the core purpose, lists the single argument with a brief explanation, and notes the return value. Every sentence adds value without redundancy, making it easy to scan and understand quickly.

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 annotations, but has an output schema), the description is adequate but incomplete. It covers the basic purpose and parameter intent but lacks behavioral context and usage guidelines. The output schema likely handles return values, so the description doesn't need to detail them, but overall it's minimal for a tool that might involve web 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 description adds minimal semantics beyond the input schema. It explains that 'encoded_level' is 'An encoded level string for playing', which clarifies its purpose but doesn't provide format details or examples. With 0% schema description coverage, this partially compensates but is insufficient for full understanding. The baseline is adjusted due to low coverage.

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

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

The description clearly states the tool's purpose: 'Get the URL to play a VibeTide level in the web player.' It specifies the verb ('Get'), resource ('URL'), and context ('VibeTide level in the web player'). However, it doesn't explicitly distinguish it from sibling tools like 'view_level' or 'decode_level_from_url', which might have overlapping purposes.

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 'view_level' or 'decode_level_from_url', nor does it specify prerequisites or exclusions. Usage is implied by the purpose but lacks explicit 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 carries the full burden of behavioral disclosure. It states that the tool returns 'a visual representation of the level', which is helpful, but doesn't cover important aspects like whether this is a read-only operation, potential rate limits, authentication needs, or what format the visual representation takes. For a tool with no annotation coverage, this leaves significant gaps.

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

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

The description is appropriately concise with three sentences that each serve a purpose: stating the tool's function, describing the parameter, and explaining the return value. It's front-loaded with the main purpose. The structure is clear, though the 'Args:' and 'Returns:' formatting could be slightly more polished.

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 that there's an output schema (which should document return values), the description doesn't need to fully explain returns. However, for a tool with no annotations and 0% schema description coverage, it should provide more behavioral context. The description covers the basics but lacks details on usage scenarios, error conditions, or visual representation specifics that would make it complete.

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

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

The description adds meaningful context for the single parameter 'encoded_level', explaining it should be 'from a URL or sharing link'. With 0% schema description coverage, this compensates somewhat by clarifying the parameter's source and format. However, it doesn't provide examples or detailed syntax, leaving room for improvement in fully documenting 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 the tool's purpose: 'View a VibeTide level with visual representation.' It specifies the verb ('view') and resource ('VibeTide level'), distinguishing it from siblings like 'create_level' or 'edit_level_metadata'. However, it doesn't explicitly differentiate from 'view_level_image', which might serve a similar visual purpose.

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

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

The description provides minimal guidance on when to use this tool. It mentions that the input is 'an encoded level string from a URL or sharing link', but doesn't specify when to choose this over alternatives like 'view_level_image' or 'play_level'. No explicit when/when-not scenarios or prerequisites are included.

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 key behaviors: the tool generates a PNG image, saves it to a temporary file, returns the file path for display, and mentions auto-adjustment for wide levels. It doesn't cover potential errors, performance characteristics, or file cleanup, but provides substantial operational 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 efficiently structured: a clear purpose statement upfront, followed by comparative context, then behavioral details, and finally organized parameter and return value sections. Every sentence adds value without redundancy, and the information is well-organized for quick comprehension.

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 (3 parameters, no annotations, but with output schema), the description is complete enough. It explains the purpose, usage context, key behaviors, parameter meanings, and return value. The output schema handles the return structure, so the description doesn't need to elaborate further on that aspect.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all three parameters: 'encoded_level' is explained as 'an encoded level string from a URL or sharing link', 'tile_size' as 'size of each tile in pixels' with default and auto-adjustment note, and 'max_width' as 'maximum image width in pixels' with default. This goes well beyond the bare schema titles.

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 ('view a VibeTide level as a beautiful PNG image'), identifies the resource ('VibeTide level'), and distinguishes it from siblings by explicitly contrasting with 'the ASCII version' (likely referring to the sibling 'view_level' tool). The purpose is precise and differentiated.

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 ('generates a much better visual representation than the ASCII version, using the same colors as the web builder'), which implicitly suggests it's preferable for visual display over text-based alternatives. However, it doesn't explicitly name when not to use it or mention specific alternative tools by name beyond the implied contrast.

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