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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Add pushable rocks' implies a mutation operation but gives no details on effects (e.g., whether rocks are interactable, affect gameplay like blocking paths, or require specific permissions). It lacks information on side effects, error conditions, or what happens if positions overlap existing elements.

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 just three words, front-loading the core action. There's no wasted text or redundancy. However, this brevity contributes to underspecification rather than effective communication.

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

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

Given no annotations, no output schema, and a mutation tool with potential gameplay implications, the description is severely incomplete. It doesn't explain the tool's role in the broader context (e.g., level editing), what 'pushable rocks' are functionally, or the expected outcome. For a tool that likely modifies game state, this lack of context is inadequate.

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

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

Schema description coverage is 100% with the parameter 'positions' documented as 'Positions for pushable rocks'. The description adds no additional meaning beyond this, such as coordinate systems (e.g., grid-based), valid ranges, or constraints (e.g., must be empty tiles). With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.

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 'Add pushable rocks' is a tautology that essentially restates the tool name. While it identifies the resource ('pushable rocks') and verb ('add'), it lacks specificity about what 'add' means in this context (e.g., to a level, grid, or game state). It doesn't distinguish from sibling tools like 'remove_pushable_rock' beyond the opposite 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing level), context (e.g., during level design), or comparisons to siblings like 'place_tile' or 'set_barrier' for similar placement operations. There's no indication of when this tool is appropriate or not.

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 mentions the tile's behavior ('break after crossing'), which is useful, but lacks critical details: whether this is a mutation (implied by 'Add'), what permissions are needed, if it affects game state, or what happens on success/failure. For a tool with no annotations, 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 with a clarifying parenthetical. It's front-loaded with the core action and wastes no words, making it easy to parse 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 no annotations and no output schema, the description is incomplete for a mutation tool. It lacks information on behavioral impact (e.g., whether changes are saved immediately), error conditions, or return values. The context of level editing is implied but not stated, leaving 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?

Schema description coverage is 100%, with the parameter 'positions' documented as 'Positions for thin ice'. The description adds no additional parameter semantics beyond this, but the schema provides adequate detail. With high coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the action ('Add thin ice tiles') and the resource ('thin ice tiles'), with the parenthetical explaining the tile's behavior ('break after crossing'). This distinguishes it from sibling tools like 'remove_thin_ice' and 'place_tile', though it doesn't explicitly contrast with other tile-adding tools like 'add_pushable_rock'.

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. The description doesn't mention prerequisites, context (e.g., level editing), or comparisons to similar tools like 'place_tile' or 'add_pushable_rock', leaving the agent to infer usage from the tool 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?

With no annotations provided, the description carries full burden for behavioral disclosure. 'Add' implies a mutation/write operation, but the description doesn't specify permissions needed, whether this affects game state immediately, what happens if positions conflict with existing elements, or any side effects. For a mutation tool with zero annotation coverage, 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 communicates the core functionality without any wasted words. It's appropriately sized for a simple tool and front-loads the essential information.

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

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

For a mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what happens after adding the warp pair, whether there's confirmation or error handling, coordinate system details, or how this integrates with other level editing operations. The context signals show this is a complex server with many sibling tools, making the lack of contextual guidance more problematic.

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

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

Schema description coverage is 100%, so the schema already documents all four parameters (x1, y1, x2, y2) as coordinate pairs. The description adds minimal value beyond the schema by implying these represent 'two positions' but doesn't explain coordinate systems, units, or relationships between the pairs beyond what's in the schema descriptions.

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

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

The description clearly states the action ('Add a warp portal pair') and the resource ('connecting two positions'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'remove_warp' or other placement tools, but the verb+resource combination is specific enough for basic understanding.

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 'place_tile' or 'remove_warp'. There's no mention of prerequisites, constraints, or typical scenarios for adding warp pairs versus other level editing operations.

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 mentions analysis but doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires a level to be loaded, what the output format might be, or any performance considerations. This leaves significant gaps for an agent to understand how to use it effectively.

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 directly states the tool's purpose without unnecessary words. It's appropriately sized for a zero-parameter tool and front-loaded with the core action.

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

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

Given the complexity of analyzing 'difficulty and characteristics' with no annotations, no output schema, and vague purpose, the description is incomplete. It doesn't explain what the analysis entails, what metrics are used, or how results are returned, making it inadequate for an agent to leverage this tool fully.

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

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

With 0 parameters and 100% schema description coverage, the baseline is high. The description implies the tool operates on a 'current level' context, which adds semantic meaning beyond the empty schema, suggesting it might rely on an implicit state rather than explicit inputs.

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 'Analyze current level difficulty and characteristics' states a clear verb ('Analyze') and resource ('current level'), but is vague about what constitutes 'difficulty and characteristics' and doesn't differentiate from sibling tools like 'get_level_requirements' or 'validate_quality_gate' that might provide related information. It's functional but lacks specificity.

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 'get_level_requirements' and 'validate_quality_gate', the description doesn't indicate if this is for real-time analysis, post-creation evaluation, or comparison purposes, leaving usage context unclear.

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 implies a read-only check, but doesn't disclose what the status includes (e.g., logged-in state, user info), whether it requires network calls, or error behavior. For a tool with no 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 a single, efficient sentence with no wasted words. It's front-loaded and directly states the tool's function without unnecessary elaboration.

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 tool with no output schema, the description is minimally adequate but lacks details on return values or behavioral context. Given no annotations, it should ideally explain what 'status' entails or usage prerequisites, leaving room for improvement.

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%, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, earning a baseline score above minimum viable.

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 ('Check') and resource ('Firebase authentication status'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools, which all appear to be level-editing related, so this tool stands out but without explicit comparison.

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. Given the sibling tools are focused on level manipulation, this authentication check might be a prerequisite, but the description doesn't state this or any other contextual usage rules.

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 mentions checking 'auth status + strict quality gate', which gives some behavioral context about what gets evaluated. However, it lacks details on permissions needed, rate limits, whether it's read-only or has side effects, or what the output looks like. For a tool with zero annotation coverage, 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 extremely concise and front-loaded: a single phrase that directly states the tool's function. Every word earns its place, with no wasted text or redundancy. It efficiently communicates the core purpose without unnecessary elaboration.

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 implied by checking multiple blockers (auth and quality), no annotations, and no output schema, the description is incomplete. It doesn't explain what the checks entail, what constitutes a 'blocker', how results are returned, or error conditions. For a diagnostic tool with no structured support, more detail is needed to be fully helpful.

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 with 100% schema description coverage (empty schema). The description doesn't need to explain parameters, and it doesn't add any parameter-specific information. Since there are no parameters, a baseline score of 4 is appropriate as the description doesn't have to compensate for any gaps.

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: 'Check publish blockers' with specific checks on 'auth status + strict quality gate'. It uses a specific verb ('Check') and identifies the resource (publish readiness). However, it doesn't explicitly differentiate from sibling tools like 'validate_quality_gate' or 'auth_status', which appear to check similar aspects individually.

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 'publish blockers', suggesting this tool should be used before publishing (e.g., before 'publish_level'). However, it doesn't provide explicit guidance on when to use this versus alternatives like 'validate_quality_gate' or 'auth_status', nor does it specify prerequisites 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, so the description carries the full burden. It states the tool clears elements and preserves grid size, but lacks critical behavioral details: whether this action is reversible (e.g., via 'undo'), if it affects saved drafts, what 'elements' encompass (tiles, objects, etc.), or any permissions required. For a mutation tool with zero annotation coverage, this 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 a single, efficient sentence that front-loads the core action ('Clear all elements from the level') and adds a key constraint ('keeping grid size'). There is no wasted verbiage, making it highly concise and well-structured for quick understanding.

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 (a mutation operation with no annotations and no output schema), the description is incomplete. It lacks details on what 'elements' include, the impact on level state (e.g., draft vs. published), reversibility, and error conditions. For a tool that modifies level data, this leaves too many unknowns for safe and effective 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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds context by specifying that grid size is preserved, which is useful semantic information beyond the empty schema. This compensates adequately, though not perfectly as it doesn't detail side effects.

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 ('Clear all elements') and the resource ('from the level'), with a specific constraint ('keeping grid size'). It distinguishes from sibling 'clear_region' by operating on the entire level rather than a region. However, it doesn't explicitly contrast with other deletion tools like 'remove_tile' or 'delete_draft', keeping it from 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?

No explicit guidance is provided on when to use this tool versus alternatives. The description implies it clears all elements while preserving grid size, but it doesn't specify scenarios (e.g., resetting a level vs. partial edits) or mention sibling tools like 'clear_region' for targeted clearing. This leaves usage context ambiguous.

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 'Auto-solves' behavior which is valuable context beyond basic clearing. However, it doesn't mention whether this is destructive (likely yes), permission requirements, rate limits, or what 'Auto-solves' specifically entails.

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

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

Two concise sentences with zero waste. First sentence states core functionality, second adds crucial behavioral context. Perfectly front-loaded and appropriately sized.

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 destructive operation with no annotations and no output schema, the description is minimal but functional. It covers the basic purpose and one behavioral trait, but lacks details about what 'Clear all tiles' means (what happens to different tile types), the 'Auto-solves' mechanism, or error conditions.

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

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

Schema description coverage is 100% with clear parameter documentation. The description adds no additional parameter information beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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 ('Clear all tiles'), target resource ('in a rectangular region'), and behavioral outcome ('Auto-solves'). It distinguishes from siblings like 'clear_level' (which clears entire level) and 'remove_tile' (which removes individual tiles).

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 clearing rectangular regions and mentions auto-solving, but provides no explicit guidance on when to use this versus alternatives like 'clear_level', 'remove_tile', or 'fill_region'. No prerequisites or exclusions are mentioned.

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 but only states the basic action. It doesn't disclose behavioral traits like whether this requires authentication, creates a draft or published level, what happens on success/failure, or if there are rate limits. The description is minimal and lacks critical 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 a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it immediately understandable without unnecessary elaboration.

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 creation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'empty' entails (e.g., no tiles, default layout), the return value (e.g., level ID, success confirmation), or error conditions. Given the complexity of level creation in this context, more context is needed.

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

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

Schema description coverage is 100%, so the schema fully documents all parameters (name, width, height). The description adds no additional meaning beyond implying these parameters define the level, which is already clear from the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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') and resource ('new empty ice puzzle level'), distinguishing it from sibling tools like 'set_grid_size' (which modifies existing levels) or 'import_level' (which creates from external data). It precisely defines what the tool does.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'import_level' (which creates from import) or 'seed_layout_pattern' (which creates with initial content). It also doesn't mention prerequisites, such as whether authentication is required or if this creates a draft versus published level.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Delete' which implies a destructive mutation, but fails to specify whether the deletion is permanent, reversible, or requires specific permissions. No information on side effects, error conditions, or response format is given.

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 directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse 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?

For a destructive mutation tool with no annotations and no output schema, the description is incomplete. It lacks critical behavioral details (e.g., permanence, permissions) and does not explain what happens upon success or failure. Given the complexity and risk of deletion, more context is needed.

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

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

The input schema has 100% description coverage, with 'draftId' clearly documented. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Baseline 3 is appropriate since the schema adequately covers the single 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 action ('Delete') and the resource ('a locally saved draft snapshot'), making the purpose immediately understandable. It distinguishes from sibling 'delete_remote_draft' by specifying 'locally saved', but could be more explicit about the scope (e.g., 'local storage' vs 'remote server').

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 'delete_remote_draft' or 'clear_level', nor does it mention prerequisites (e.g., needing an existing draft). It implies usage for local drafts but lacks explicit 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool performs a deletion, implying a destructive mutation, but fails to mention critical aspects like permissions required, whether the action is reversible, potential side effects (e.g., impact on related data), or error handling. This is inadequate for a mutation tool with zero 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 a single, efficient sentence that front-loads the key information ('Delete a remote draft from Firebase by ID') with zero wasted words. It is appropriately sized for a simple tool with one parameter, making it easy for an agent to parse 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 destructive nature (deletion), lack of annotations, and absence of an output schema, the description is insufficient. It does not cover behavioral traits (e.g., irreversibility, auth needs), error responses, or what happens post-deletion. For a mutation tool with no structured safety hints, more context is needed to ensure safe and correct usage.

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

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

The input schema has 100% description coverage, with the 'draftId' parameter clearly documented as 'Draft ID to delete'. The description adds no additional semantic context beyond this, such as format examples or validation rules. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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

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

The description clearly states the specific action ('Delete'), resource ('a remote draft from Firebase'), and identifier ('by ID'), distinguishing it from sibling tools like 'delete_draft' (which likely handles local drafts) and 'list_remote_drafts' (which lists rather than deletes). It precisely communicates what the tool does without ambiguity.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as 'delete_draft' (for local drafts) or 'clear_level' (which might remove entire levels). It lacks context about prerequisites (e.g., needing an existing remote draft) or exclusions, leaving the agent to infer usage from the tool 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 are provided, so the description carries the full burden of behavioral disclosure. It states the tool exports data but doesn't clarify if this is a read-only operation, if it modifies state, what happens to the draft after export, or any rate limits or permissions required. For a 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse 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 has no parameters, no annotations, and no output schema, the description adequately covers the basic purpose. However, it lacks details on behavioral aspects (e.g., side effects, return format) and usage context, making it minimally viable but incomplete for optimal agent understanding in a complex environment with many sibling 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?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here, earning a baseline score of 4 as it doesn't need to compensate for any schema gaps.

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 ('Export') and the target resource ('current working draft as PuzzleData JSON'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'save_draft' or 'save_local_draft', which might have overlapping functionality but different output formats or 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 prerequisites (e.g., needing a loaded draft), exclusions, or comparisons to similar tools like 'save_draft' or 'export' variants that might exist in context, leaving usage context implied rather than 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?

With no annotations provided, the description carries full burden. It discloses 'Auto-solves' as a behavioral trait, which is valuable beyond the schema. However, it lacks critical information: whether this is a destructive/mutative operation, permission requirements, side effects on existing tiles, or what 'Auto-solves' entails (e.g., validation, solution checking).

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 with zero wasted words. It front-loads the core action ('Fill a rectangular region') and includes the key behavioral note ('Auto-solves') without unnecessary elaboration.

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 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks information on what the tool returns, error conditions, the scope of 'Auto-solves' (e.g., does it validate the entire level?), and how it interacts with other level-editing operations.

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

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

Schema description coverage is 100%, providing clear documentation for all 5 parameters (coordinates and tile type with enum). The description adds no parameter-specific semantics beyond what the schema already states, so it meets the baseline of 3 without compensating 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 specific action ('Fill a rectangular region'), the resource ('with a tile type'), and includes a behavioral trait ('Auto-solves'). It distinguishes itself from siblings like 'place_tile' (single tile) and 'clear_region' (removal) by focusing on batch filling of a defined area.

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 'place_tiles_batch' or 'clear_region'. It mentions 'Auto-solves' but doesn't explain if this is a prerequisite, side effect, or when it's appropriate compared to manual solving tools like 'solve_level'.

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 but lacks behavioral details. It doesn't disclose whether this is a read-only operation, if it requires authentication, rate limits, or error handling. The mention of 'optional PuzzleData' hints at response variability but doesn't fully describe behavior 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 a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words, though it could be slightly more structured by separating identification methods from response options.

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 read operation with full schema coverage but no annotations or output schema, the description is minimally adequate. It covers the basic purpose and response elements but lacks details on authentication, error cases, or example usage that would enhance completeness 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?

Schema description coverage is 100%, so the schema fully documents parameters. The description adds minimal value by implying parameters are used to identify the example and control response content, but doesn't provide additional semantics like usage examples or constraints beyond what's 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 action ('Get') and resource ('one campaign level example'), specifying it retrieves a single example with solution and optional PuzzleData. It distinguishes from the sibling 'list_campaign_examples' by focusing on a single item rather than listing multiple, though it doesn't explicitly name this sibling for 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 like 'get_level' or 'list_campaign_examples', nor does it mention prerequisites or exclusions. It only states what the tool does without contextual usage advice.

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 'Get' which implies a read operation, but it doesn't specify if this requires authentication, returns structured data, has rate limits, or involves any side effects. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without any fluff or unnecessary details. It is appropriately sized and front-loaded, making it easy for an agent to parse 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 complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavioral traits, usage context, or return values. For a tool in a server with many siblings, more guidance would improve completeness, but it's not entirely 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 tool has 0 parameters, and the schema description coverage is 100% (as there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for this dimension, as it doesn't introduce confusion or redundancy.

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 the resource 'comprehensive ice puzzle game rules and design guide', making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'interaction_faq' or 'get_tile_types', which might also provide game-related information, so it doesn't reach the highest 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. With many sibling tools related to game design and rules (e.g., 'interaction_faq', 'get_tile_types'), there is no indication of context, prerequisites, or exclusions, leaving the agent to guess based on 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 are provided, so the description carries full burden. It mentions 'details and visualization', hinting at output content, but doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires authentication, or how it handles errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 core action ('Get the current working draft level') and adds specifics ('with details and visualization'). There's no wasted verbiage, making it appropriately sized for its 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 0 parameters and no output schema, the description adequately states what the tool does. However, with no annotations and siblings like 'preview_level' that might overlap, it lacks completeness in clarifying uniqueness and behavioral context. It's minimal but functional for a simple retrieval tool.

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

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

The input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add param info, but that's unnecessary here. Baseline is 4 for 0 parameters, as the schema fully covers the absence of inputs.

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 the resource 'current working draft level', specifying it includes 'details and visualization'. It distinguishes from siblings like 'get_level_requirements' or 'get_campaign_example' by focusing on the current draft. However, it doesn't explicitly differentiate from 'preview_level' or 'visualize_level', which might offer similar visualization 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a loaded draft), exclusions, or compare to siblings like 'preview_level' or 'visualize_level'. The context is implied as retrieving draft data, but no explicit usage rules are given.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets' requirements, implying a read-only operation, but doesn't specify what the requirements entail, how they are returned, or any constraints like permissions or rate limits. This is a significant gap for a tool with zero 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 a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the description earns its place by conveying essential information.

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

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

Given the complexity implied by 'requirements for publishable levels' and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the requirements are, how they are structured, or what the return values look like, leaving the agent with insufficient context for effective 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 tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it doesn't introduce any confusion. A baseline of 4 is appropriate as it compensates adequately for the lack of 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 'Get requirements for publishable levels' clearly states the verb ('Get') and resource ('requirements for publishable levels'), making the purpose understandable. However, it doesn't differentiate from siblings like 'check_publish_readiness' or 'validate_quality_gate', which might have overlapping functionality, 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 provides no guidance on when to use this tool versus alternatives such as 'check_publish_readiness' or 'validate_quality_gate'. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on 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 are provided, so the description carries the full burden of behavioral disclosure. It states a read operation ('Get'), but doesn't mention any behavioral traits such as authentication requirements (implied by 'your'), rate limits, error handling, or what happens if the ID is invalid. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves beyond the basic 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 a single, efficient sentence that front-loads the core action ('Get one of your published marketplace levels') and specifies the key constraint ('by ID'). There is no wasted wording, and it directly communicates the essential information without unnecessary elaboration.

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 nested objects) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it lacks details on behavioral aspects (e.g., authentication, error cases) and return values. For a read operation, this leaves the agent with incomplete context, though the basic purpose is clear.

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 100% description coverage, with 'levelId' documented as 'Marketplace level ID'. The description adds no additional meaning beyond this, as it only repeats 'by ID' without elaborating on format, constraints, or examples. With high schema coverage, the baseline is 3, as the schema adequately handles parameter documentation.

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 ('your published marketplace levels'), specifying it retrieves a single level by ID. It distinguishes from siblings like 'get_level' (likely general) or 'list_my_published_levels' (multiple), but doesn't explicitly name these alternatives. The purpose is specific and actionable, though sibling differentiation is implied rather than explicit.

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 you need to retrieve a specific published level you own, as indicated by 'your published' and 'by ID'. However, it lacks explicit guidance on when to use this versus alternatives like 'get_level' (which might fetch any level) or 'list_my_published_levels' (for browsing). No exclusions or prerequisites are mentioned, leaving usage context somewhat vague.

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 what data is retrieved but doesn't cover aspects like whether this is a read-only operation, if it requires authentication, rate limits, or what the return format looks like. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse 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 simplicity (0 parameters, no output schema), the description is minimally adequate but lacks depth. It doesn't explain the return format or behavioral traits, which could be important for an AI agent to use it correctly, especially without annotations. However, for a straightforward data retrieval tool, it meets basic requirements.

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 with 100% schema description coverage, so the schema fully documents the absence of inputs. The description adds no parameter information, which is appropriate here, but since there are no parameters to explain, it doesn't need to compensate for any gaps, warranting a baseline score above 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 ('Get') and resource ('all tile types with behavior descriptions'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_game_rules' or 'get_level_requirements', which also retrieve game-related data, so it falls short of 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 prerequisites, context, or compare it to similar tools in the sibling list, leaving the agent to infer usage based on 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 are provided, so the description carries full burden. It states 'Import a level' which implies a write/mutation operation, but doesn't disclose behavioral traits such as whether it overwrites existing levels, requires authentication, has side effects, or returns confirmation. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence with zero waste—'Import a level from PuzzleData JSON'. It's front-loaded and appropriately sized for the tool's complexity, earning its place 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 no annotations, no output schema, and a mutation tool (import implies write), the description is incomplete. It lacks details on behavior, return values, error handling, or format specifics. For a tool that likely modifies game levels, more context is needed to guide the agent 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?

Schema description coverage is 100%, with the parameter 'puzzleData' documented as a 'PuzzleData JSON object'. The description adds minimal value beyond the schema by specifying 'from PuzzleData JSON', but doesn't explain the JSON structure or provide examples. Baseline 3 is appropriate as the schema handles most parameter documentation.

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 ('Import') and resource ('a level'), specifying it's from 'PuzzleData JSON'. It distinguishes from siblings like 'create_level' (new creation) and 'export_level' (opposite direction), though it doesn't explicitly contrast them. The purpose is specific and actionable.

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 like 'create_level' or 'load_draft', nor prerequisites (e.g., needing PuzzleData JSON format). The description implies usage for importing levels from JSON, but lacks explicit context or exclusions, leaving the agent to infer from sibling names 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 mentions 'quick-reference' outcomes, implying a read-only, non-destructive operation, but doesn't disclose behavioral traits like response format, potential rate limits, or whether it requires authentication. This leaves gaps in understanding how the tool behaves beyond its basic purpose.

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 states the purpose without unnecessary words. It is front-loaded with the core action ('Get quick-reference interaction outcomes'), making it easy to parse, though it could be slightly more structured for clarity.

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

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

Given the complexity implied by 'adjacent mechanic combinations' and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'interaction outcomes' entail, how they are formatted, or any prerequisites, making it inadequate for an AI agent to fully understand the tool's context and usage.

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

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

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the inputs. The description doesn't need to add parameter details, and it appropriately avoids redundancy. A baseline score of 4 is applied as it doesn't introduce confusion or omissions regarding 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 states the tool 'Get quick-reference interaction outcomes for adjacent mechanic combinations', which specifies a verb ('Get') and resource ('interaction outcomes'), but is vague about what 'adjacent mechanic combinations' means in this context. It doesn't clearly distinguish from sibling tools like 'get_game_rules' or 'simulate_move', which might also provide game-related information.

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

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

No guidance is provided on when to use this tool versus alternatives. With sibling tools like 'get_game_rules', 'simulate_move', or 'analyze_difficulty', the description doesn't specify scenarios where this tool is preferred, such as for quick checks versus detailed simulations, leaving usage context unclear.

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 mentions 'solver solutions' but doesn't clarify if this is a read-only operation, whether it requires authentication, rate limits, or what format the response takes. For a tool with no annotation coverage, this leaves significant behavioral gaps about safety, permissions, and output structure.

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

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

Single sentence efficiently conveys the core functionality with zero wasted words. It's front-loaded with the main purpose and includes key parameter implications without unnecessary elaboration.

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 read operation with 3 well-documented parameters but no output schema, the description adequately covers what the tool does. However, without annotations or output schema, it doesn't address response format, pagination, authentication needs, or error conditions. It's minimally viable but has clear gaps in behavioral 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 100%, so the schema already documents all three parameters thoroughly. The description mentions 'difficulty tier' and 'solver solutions' which map to the 'difficulty' and 'includeSolutions' parameters, but adds no additional semantic context beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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

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

The description clearly states the verb 'list' and resource 'campaign level examples', specifies filtering by 'difficulty tier (easy/medium/hard)', and mentions inclusion of 'solver solutions'. This distinguishes it from sibling tools like 'get_campaign_example' (singular) and 'list_drafts' (different resource).

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. While it's clear this lists campaign examples, there's no mention of when to use it instead of 'get_campaign_example' (singular retrieval) or how it relates to other listing tools like 'list_drafts' or 'list_my_published_levels'. The description only states what it does, not when to choose it.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe return format, pagination, sorting, or what constitutes a 'draft snapshot'. For a listing tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

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 gets straight to the point with no wasted words. It's appropriately sized for a simple listing tool and front-loads the essential information.

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

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

For a zero-parameter listing tool with no output schema, the description is minimally adequate but could be more complete. It identifies the resource but doesn't describe the return format or any behavioral characteristics. Given the simplicity of the tool (no parameters) and lack of annotations/output schema, it meets basic requirements but leaves room for improvement.

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 (schema coverage 100%), so the description doesn't need to compensate for parameter documentation gaps. The baseline for zero parameters is 4, as there are no parameters whose semantics need explanation beyond what the empty schema already indicates.

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 'List all locally saved draft snapshots' clearly states the action (list) and resource (locally saved draft snapshots). It distinguishes from sibling tools like 'list_remote_drafts' by specifying 'locally saved', but doesn't explicitly contrast with other listing tools like 'list_campaign_examples' or 'list_my_published_levels'.

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. While 'locally saved' implies a distinction from remote drafts, there's no explicit mention of when-not-to-use scenarios or comparisons to other listing tools like 'list_remote_drafts' or 'list_my_published_levels'.

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 filtering, sorting, and pagination, but doesn't describe the return format, error conditions, rate limits, authentication needs, or whether it's a read-only operation. For a tool with no annotations, 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 a single, efficient sentence that front-loads the core purpose and lists key features without unnecessary words. Every element earns its place, making it appropriately sized for the tool's complexity.

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

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

Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic functionality but lacks details on output format, error handling, and usage context. Without annotations or output schema, more behavioral information would be beneficial.

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

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

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds minimal value beyond the schema by summarizing the parameter types ('status filter, sorting, and pagination'), but doesn't provide additional context or examples. This meets the baseline for high schema coverage.

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

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

The description clearly states the action ('List') and resource ('your marketplace levels'), making the purpose understandable. It distinguishes from siblings by focusing on published levels (vs. drafts or other operations), though it doesn't explicitly contrast with specific sibling tools like 'list_drafts' or 'get_my_published_level'.

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 'list_drafts', 'get_my_published_level', or other listing tools, nor does it specify prerequisites or context for usage.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List all remote drafts') but doesn't describe the return format (e.g., list structure, fields included), pagination behavior, error conditions, or any side effects. This leaves significant gaps for a tool that likely interacts with a database.

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 with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by specifying 'remote' and 'Firebase' for clarity.

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

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

Given the complexity (a listing tool for remote drafts), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what a 'remote draft' entails, the expected return format, or any behavioral nuances (e.g., sorting, filtering). This leaves the agent with insufficient context for reliable 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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, but it could have mentioned implicit parameters like authentication context. A baseline of 4 is applied for zero-parameter tools.

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

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

The description clearly states the verb 'List' and the resource 'remote drafts from Firebase', making the purpose specific and understandable. It distinguishes from siblings like 'list_drafts' by specifying 'remote' drafts, though it doesn't explicitly contrast with other listing tools like 'list_campaign_examples' or 'list_my_published_levels'.

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 prerequisites (e.g., authentication status), differentiate from similar tools like 'list_drafts' (which might list local drafts), or specify use cases (e.g., before deletion or publication).

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Load') but doesn't explain what 'load' entails—whether it's a read-only operation, if it modifies data, requires authentication, or has rate limits. This leaves critical behavioral traits unspecified 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 a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded and wastes no space, making it easy to parse 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'load' returns (e.g., draft data structure), potential errors, or behavioral aspects like side effects. For a tool with no structured context, this leaves significant gaps for an agent to use it 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 100% description coverage, with the parameter 'draftId' documented as 'Draft ID to load'. The description adds no additional meaning beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating value.

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

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

The description clearly states the action ('Load') and resource ('a draft from Firebase by ID'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'load_local_draft' or 'get_level', which also retrieve draft/level data, leaving room for ambiguity in tool selection.

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 'load_local_draft' or 'get_level', nor does it mention prerequisites like needing a valid draft ID. This lack of context makes it challenging for an agent to decide when this tool is appropriate.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool loads a draft but doesn't mention what 'load' entails (e.g., retrieves data for editing, requires specific permissions, or has side effects like caching). This leaves significant gaps in understanding the tool's behavior.

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 with no wasted words. It front-loads the key action and resource, making it easy to parse quickly without unnecessary elaboration.

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 is insufficient for a tool that likely retrieves data. It doesn't explain what 'loading' entails (e.g., returns draft content, metadata, or both) or any prerequisites, leaving the agent with incomplete context for proper 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 100% description coverage, with the parameter 'draftId' clearly documented. The description adds minimal value by implying the ID refers to a local draft, but doesn't provide additional context like format examples or constraints beyond what the schema already states.

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 ('Load') and resource ('locally saved draft snapshot'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'load_draft' or 'list_drafts', which would require mentioning it's specifically for local drafts rather than remote ones.

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 'load_draft' or 'list_drafts'. The description implies it's for local drafts but doesn't explicitly state when to choose it over other draft-related tools, leaving usage context unclear.

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 'Auto-solves,' which hints at automatic solving after the move, but fails to clarify critical aspects like whether this is a destructive operation (likely yes, as it moves tiles), what permissions are needed, or how errors are handled (e.g., invalid coordinates). This leaves significant gaps in understanding the tool's behavior.

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—just two short sentences that directly state the tool's function and a key behavioral trait ('Auto-solves'). There is no wasted language, and it is front-loaded with the core purpose, 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 complexity of a tile-moving operation in a level editor context, with no annotations and no output schema, the description is incomplete. It lacks details on side effects (e.g., whether the move affects game state permanently), error conditions, or what 'Auto-solves' entails (e.g., solving the level automatically after the move). This makes it inadequate for safe and informed use by 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 input schema has 100% description coverage, clearly documenting all four parameters (fromX, fromY, toX, toY) as coordinates. The description adds no additional semantic meaning beyond what the schema provides, such as coordinate ranges or units. According to the rules, with high schema coverage, the baseline score is 3, as the schema adequately handles parameter documentation.

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 ('Move'), the resource ('one tile/special element'), and the scope ('from one coordinate to another'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate this tool from similar siblings like 'place_tile' or 'simulate_move', which slightly limits its distinctiveness.

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 'place_tile' (for initial placement) or 'simulate_move' (for testing moves without changes). It also lacks information about prerequisites, such as whether a tile must exist at the source coordinates, leaving usage context unclear.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Auto-solves,' which hints at automatic solving after placement, but doesn't clarify what this entails (e.g., whether it triggers validation, affects game state, or has side effects). It lacks details on permissions, error handling, or interaction with other tools like 'solve_level'.

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 a single sentence that efficiently conveys the core action, tile types, location, and a key behavioral trait ('Auto-solves'). Every word serves a purpose, and it's front-loaded with the essential information.

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

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

Given the complexity of a tile placement tool with no annotations and no output schema, the description is incomplete. It lacks details on what 'Auto-solves' means in practice, how it interacts with other tools (e.g., 'solve_level'), error conditions, or the effect on the game state. For a mutation tool in a level-editing context, more behavioral context is needed.

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

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

The schema description coverage is 100%, so the schema fully documents the parameters (x, y, type). The description adds minimal value beyond the schema by implying placement at a position and listing tile types, but doesn't provide additional context like coordinate system details or tile behavior differences.

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 ('Place a tile') and specifies the resource (tile types: rock, lava, hot_coals, or spike) with the location constraint ('at position'). It distinguishes from siblings like 'place_tiles_batch' (batch operation) and 'remove_tile' (removal), but doesn't explicitly contrast with 'move_tile' (relocation) or 'test_placement' (testing).

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 'place_tiles_batch' for multiple placements, 'move_tile' for relocating tiles, or 'test_placement' for testing placements. It mentions 'Auto-solves' but doesn't explain how this affects usage compared to other tools that might not auto-solve.

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 'Auto-solves,' which hints at automatic solving behavior, but doesn't explain what this entails (e.g., validation, side effects, or performance implications). Critical details like permissions, idempotency, or error handling 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 extremely concise with just two short sentences ('Place multiple tiles at once. Auto-solves.'), front-loading the core purpose. Every word earns its place, with no redundant or verbose language.

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 batch operation with potential side effects ('Auto-solves'), no annotations, and no output schema, the description is insufficient. It lacks details on return values, error conditions, or the scope of 'Auto-solves,' leaving significant gaps for an AI agent to understand tool behavior fully.

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

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

Schema description coverage is 100%, so the schema fully documents the 'tiles' parameter as an array of objects with x, y, and type properties. The description adds no additional meaning beyond implying batch processing, which is already clear from the schema's array structure. This meets the baseline for high schema coverage.

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

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

The description clearly states the action ('Place multiple tiles at once') and the resource ('tiles'), making the purpose understandable. However, it doesn't explicitly differentiate from its sibling 'place_tile' (single tile placement), which is a missed opportunity for full clarity.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'place_tile' for single placements or other tile-related tools. It lacks context about prerequisites, constraints, or typical scenarios for batch operations.

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 mentions 'Create or update' and 'shareable preview link,' which implies mutation and sharing capabilities, but doesn't disclose behavioral traits such as permissions needed, whether changes are reversible, rate limits, or what the output looks like. This is a significant gap for a mutation tool with zero 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 a single, efficient sentence that front-loads the key action and constraint. There is no wasted text, and it directly communicates the tool's purpose without unnecessary elaboration.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects, output format, and fails to fully guide usage relative to siblings. While concise, it doesn't compensate for the missing structured information, leaving gaps in understanding the tool's full 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 100%, so the schema already documents both parameters ('name' and 'description') as optional overrides. The description doesn't add any additional meaning beyond what the schema provides, such as examples or usage context for these overrides. Baseline 3 is appropriate when the schema handles parameter documentation adequately.

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 ('Create or update a shareable preview link') and the resource involved, distinguishing it from publishing operations. However, it doesn't explicitly differentiate from sibling tools like 'publish_level' or 'unpublish_level' beyond mentioning 'without publishing to marketplace,' which is good but not fully specific about alternatives.

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

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

The description implies usage for creating previews instead of publishing, but doesn't provide explicit guidance on when to use this tool versus alternatives like 'publish_level' or 'get_level.' It mentions 'without publishing to marketplace,' which gives some context but lacks detailed when/when-not scenarios 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool publishes a draft, implying a write/mutation operation, but doesn't specify permissions needed, whether it's reversible, rate limits, or what happens to the draft post-publish. This is insufficient for a mutation tool with zero 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 a single, direct sentence that efficiently conveys the core action without unnecessary words. It's front-loaded with the main purpose, making it easy to parse 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?

For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., side effects, error conditions), usage context relative to siblings, and output expectations, leaving significant gaps for an agent to operate 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 100% description coverage, clearly documenting both optional parameters ('name' and 'description'). The description doesn't add any extra meaning beyond the schema, such as default behaviors or constraints, but the schema provides adequate baseline information, justifying a score of 3.

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

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

The description clearly states the action ('publish') and the resource ('current draft as a marketplace level'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'unpublish_level' or 'save_draft', which would require more specific context about when to use each.

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 'save_draft' or 'unpublish_level', nor does it mention prerequisites such as having a draft ready or checking readiness with 'check_publish_readiness'. This lack of context leaves the agent without clear usage instructions.

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 mentions 'Analyze' but doesn't disclose behavioral traits such as whether this is a read-only operation, computational cost, output format, or any side effects. This leaves significant gaps for an agent to understand how the tool behaves.

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 directly states the tool's purpose without unnecessary words. It's front-loaded and every part contributes to understanding, making it highly concise and well-structured.

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 is incomplete. It lacks details on what the analysis returns (e.g., list of positions, paths, constraints), behavioral aspects, and how it fits among sibling tools. For a tool with potential complexity in movement analysis, this leaves too many gaps for effective 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?

Schema description coverage is 100%, with parameters 'x' and 'y' clearly documented as start coordinates. The description adds context by implying these coordinates define a starting point for reachability analysis, but doesn't provide additional semantics beyond what the schema already states, meeting the baseline for high coverage.

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

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

The description clearly states the action ('Analyze') and target ('all reachable landing positions from a starting coordinate'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'simulate_move' or 'simulate_playthrough' that might involve movement analysis, so it's not fully specific to sibling 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?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to movement and simulation (e.g., 'simulate_move', 'simulate_playthrough'), there's no indication of context, prerequisites, or exclusions for this analysis 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 are provided, so the description carries the full burden of behavioral disclosure. It states the action ('redo') but doesn't clarify what constitutes an 'operation' in this context, whether it's reversible, if it requires specific permissions, or what happens on failure (e.g., if nothing is undone). For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 directly states the tool's function without any wasted words. It's appropriately sized and front-loaded, making it easy to parse 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 that this is a mutation tool (implied by 'redo') with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or side effects, which are critical for an agent to use it correctly in a level-editing context with many sibling 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?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter details, so it meets the baseline of 4 for tools with no parameters, as there's nothing to compensate for.

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 ('redo') and the resource ('the most recently undone operation'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from its sibling 'undo', though the relationship is implied. This is clear but lacks explicit 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, such as 'undo' or other editing tools in the sibling list. It doesn't mention prerequisites (e.g., requiring an undone operation to exist) or exclusions, leaving usage context entirely implicit.

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. 'Remove the barrier' implies a destructive mutation, but it doesn't specify whether this action is reversible (e.g., via 'undo'), what permissions are required, or what the outcome entails (e.g., does it affect level solvability?). The description lacks critical behavioral details for a mutation tool with zero 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 extremely concise with a single sentence, 'Remove the barrier', which is front-loaded and wastes no words. For a tool with no parameters, this brevity is appropriate, though it may be too minimal for clarity. Every word serves a purpose, earning a high score for efficiency.

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, no annotations, and no output schema, the description is incomplete for a mutation operation. It fails to explain what a barrier is, how removal impacts the level, or what the result looks like. In a context with many sibling tools for level editing, this leaves significant gaps in understanding the tool's role and effects.

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 the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately avoids mentioning any. A baseline of 4 is applied since no parameters exist, and the description doesn't introduce confusion about inputs.

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 'Remove the barrier' is a tautology that essentially restates the tool name without adding meaningful context. While it does specify a verb ('Remove') and resource ('barrier'), it doesn't explain what a barrier is in this context or how this differs from similar tools like 'remove_tile' or 'remove_warp' among the siblings. The purpose is stated but remains vague without domain-specific clarification.

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?

There is no guidance on when to use this tool versus alternatives. Given the sibling tools include 'remove_tile', 'remove_warp', and 'remove_pressure_plate', the description fails to specify what distinguishes removing a barrier from removing other elements. No context, exclusions, or prerequisites are mentioned, leaving the agent without 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?

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Remove' implies a destructive mutation, but the description doesn't specify whether this is reversible (e.g., via undo), what permissions are required, or what happens to game state. For a mutation tool with zero annotation coverage, this is completely inadequate.

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 with zero wasted words. It's appropriately sized for a simple tool and front-loads the core action. Every word earns its place, making it easy to parse 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 this is a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'pressure plate' means in this game, what removal does to level state, whether changes are saved automatically, or what the tool returns. For a tile-editing operation in a level design context, more context is needed.

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

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

The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the input interface. The description doesn't need to explain parameters, and it correctly doesn't mention any. A baseline of 4 is appropriate for zero-parameter tools where the schema handles documentation.

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 'Remove the pressure plate' is a tautology that restates the tool name without adding meaningful context. While it specifies the resource ('pressure plate'), it doesn't explain what a pressure plate is in this game context or what removal entails. It distinguishes from siblings like 'remove_tile' or 'remove_barrier' only by naming a different tile type.

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 about when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., whether a pressure plate must exist), constraints, or relationships to sibling tools like 'set_pressure_plate' or other tile removal tools. The agent must 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?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a destructive action ('Remove') but doesn't specify if this is permanent, reversible via 'undo', or requires specific permissions. No details on side effects, error conditions, or response format are included, leaving significant gaps in understanding how the tool behaves.

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, direct phrase with no wasted words, making it highly concise and front-loaded. Every word contributes to the core purpose, adhering perfectly to efficiency standards without unnecessary elaboration.

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 annotations and output schema, the description is insufficient for a destructive tool. It doesn't cover behavioral aspects like reversibility, permissions, or result format, nor does it differentiate from similar removal tools. For a tool that modifies game state, more context is needed to ensure safe and correct 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?

Schema description coverage is 100%, with the parameter 'positions' clearly documented as an array of x,y coordinates to remove. The description doesn't add meaning beyond this, such as explaining coordinate systems or validation rules, but the schema provides adequate baseline information, justifying a score of 3.

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

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

The description clearly states the action ('Remove') and the resource ('pushable rocks'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'remove_tile' or 'remove_barrier', which would require specifying what makes pushable rocks distinct, but the basic function is 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?

No guidance is provided on when to use this tool versus alternatives like 'remove_tile' or 'clear_region', nor does it mention prerequisites or context for removal. The description only states what it does, leaving the agent to infer usage scenarios from the tool 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 are provided, so the description carries full burden for behavioral disclosure. 'Remove' implies a destructive mutation, but the description doesn't specify whether this operation is reversible (e.g., via 'undo'), what permissions are needed, or what happens to adjacent tiles. This leaves significant behavioral gaps 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 a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and understandable without unnecessary elaboration.

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 destructive mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'remove' entails (permanent deletion? temporary removal?), whether there are side effects, what happens if positions are invalid, or what the tool returns. The context demands more completeness for safe agent 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?

Schema description coverage is 100% with the parameter 'positions' clearly documented as 'Positions to remove'. The description adds no additional parameter information beyond what the schema provides. With complete schema coverage, the baseline score of 3 is appropriate since the schema does the heavy lifting.

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 'Remove thin ice tiles' clearly states the verb ('remove') and resource ('thin ice tiles'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'remove_tile' or 'remove_barrier' that also remove different tile types, so it's not fully specific about what distinguishes this tool.

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. With sibling tools like 'remove_tile' (general removal) and 'remove_barrier' (specific barrier removal), there's no indication of when thin ice removal is preferred or required over other removal methods.

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 behavior. It states 'Remove any tile at position' (implying a destructive mutation) and 'Auto-solves' (suggesting it triggers a solve check after removal), but fails to detail critical aspects like permissions needed, whether changes are reversible, error conditions, or what 'Auto-solves' entails (e.g., validation or simulation). This leaves significant gaps 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 extremely concise with two short phrases ('Remove any tile at position. Auto-solves.'), front-loaded with the core action and followed by a behavioral note. Every word contributes meaning without waste, making it highly efficient and well-structured.

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 is incomplete for a mutation tool. It mentions removal and auto-solving but omits details on effects, return values, error handling, or interaction with other tools (e.g., 'undo'). For a tool in a level-editing context with many siblings, this lacks sufficient context for safe and effective 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 100% description coverage, with parameters 'x' and 'y' documented as coordinates. The description adds no additional semantic context beyond implying these specify the tile position, so it meets the baseline of 3 where the schema handles parameter documentation adequately.

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 ('Remove any tile') and the target ('at position'), which is specific and unambiguous. It distinguishes from siblings like 'remove_barrier' or 'remove_pressure_plate' by focusing on generic tiles, but doesn't explicitly differentiate from other tile-removal tools (e.g., 'remove_pushable_rock'), 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 implies usage when needing to remove a tile at specific coordinates, with 'Auto-solves' suggesting it triggers a solve check. However, it lacks explicit guidance on when to use this versus alternatives like 'remove_barrier' or 'clear_region', and doesn't mention prerequisites or exclusions, resulting in an implied but incomplete context.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Remove' implies a destructive operation, but it doesn't specify if this is reversible (e.g., via 'undo'), what permissions are needed, or what happens to associated data. This is inadequate for a mutation tool with zero 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 a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse 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?

For a destructive tool with no annotations and no output schema, the description is incomplete. It lacks details on side effects, error conditions, or return values, leaving significant gaps in understanding how the tool behaves in practice.

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

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

Schema description coverage is 100%, so the schema fully documents the single parameter 'warpId'. The description adds no additional parameter context beyond what's in the schema, resulting in the baseline score of 3 for adequate but not enhanced coverage.

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

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

The description clearly states the action ('Remove') and target resource ('a warp pair by ID'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'remove_barrier' or 'remove_tile' beyond the resource type, 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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or what happens after removal, leaving the agent with no usage context beyond the basic action.

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 renames without recreating, hinting at a mutation operation that preserves other draft properties, but fails to disclose critical behavioral traits such as permission requirements, whether the rename is reversible, error conditions (e.g., invalid names), or effects on draft state. This leaves significant gaps 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 a single, efficient sentence that front-loads the core action ('rename') and key constraint ('without recreating it'). There is no wasted verbiage, making it highly concise and well-structured for quick understanding.

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 is a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., side effects, error handling) and return values, which are crucial for safe invocation. While concise, it does not compensate for the missing structured information, leaving the agent with insufficient 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 input schema has 100% description coverage, with the 'name' parameter documented as 'New level name'. The description adds no additional semantic context beyond this, such as naming constraints or format details. With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately handles parameter documentation.

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 ('rename') and the target ('current working draft'), specifying it operates without recreation. It distinguishes from siblings like 'create_level' by focusing on renaming an existing draft, but doesn't explicitly differentiate from other draft-modification tools like 'save_draft' or 'delete_draft' in terms of 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 implies usage when renaming a draft is needed, but provides no explicit guidance on when to use this tool versus alternatives (e.g., 'save_draft' for saving changes, 'delete_draft' for removal) or prerequisites (e.g., requires an active draft). It lacks context on when-not scenarios or comparisons to sibling 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?

No annotations are provided, so the description carries full burden. It mentions the action ('Restore') and outcome ('ACTIVE status'), but lacks details on permissions required, whether the operation is reversible, rate limits, or what happens if the level is already active. For a mutation tool with zero annotation coverage, this is insufficient behavioral disclosure.

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 core action and outcome. There is no wasted wording, and it directly communicates the tool's purpose without unnecessary elaboration, making it highly concise and well-structured.

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 annotations, no output schema, and a simple input schema, the description is minimally complete. It covers the basic action but lacks details on behavioral aspects (e.g., error conditions, side effects) and output format. For a mutation tool, this leaves gaps in understanding the full context of 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?

Schema description coverage is 100%, with the single parameter 'levelId' fully documented in the schema. The description does not add any parameter-specific details beyond what the schema provides, but with only one parameter and high schema coverage, the baseline is elevated. No additional semantics are needed, so a score of 4 reflects adequate coverage without redundancy.

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 ('Restore') and target resource ('unpublished marketplace level'), specifying the outcome ('back to ACTIVE status'). It distinguishes from siblings like 'unpublish_level' (which changes status to unpublished) and 'publish_level' (which publishes a level), making the purpose unambiguous.

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

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

The description implies usage when a level is unpublished and needs reactivation, but does not explicitly state when to use this tool versus alternatives (e.g., 'publish_level' for new publishing, 'create_level' for new levels). No exclusions or prerequisites are mentioned, leaving some ambiguity about the exact context.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Restore' implies a mutation operation that changes state, but the description doesn't specify what gets restored (e.g., level configuration, game state), whether it requires specific conditions, what happens to unsaved changes, or what the expected outcome looks like. 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 a single, efficient sentence that immediately communicates the core function without any wasted words. It's perfectly front-loaded and appropriately sized for a tool with no parameters.

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 implied by 'solvable state' in a level-editing context, the absence of annotations and output schema, and the presence of many similar sibling tools, the description is insufficient. It doesn't explain what constitutes a 'solvable state', how it differs from other states, or what happens after restoration, leaving the agent with incomplete operational 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 tool has zero parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description appropriately doesn't waste space discussing parameters, maintaining focus on the tool's purpose. This meets the baseline expectation for parameter-less tools.

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 'Restore the latest known solvable state' clearly states the action (restore) and target (latest known solvable state), which is specific and meaningful. However, it doesn't explicitly differentiate from sibling tools like 'undo' or 'restore_published_level', which might have overlapping restoration functions in this level-editing 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?

The description provides no guidance on when to use this tool versus alternatives. In a context with many sibling tools including 'undo', 'redo', and 'restore_published_level', there's no indication of prerequisites, timing, or comparative use cases for this specific restoration operation.

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 discloses authentication needs, which is useful behavioral context. However, it doesn't cover other traits like whether the operation is idempotent, what happens on failure, or if it overwrites existing drafts, leaving gaps 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 a single, efficient sentence that front-loads the core action ('Save the current draft') and adds essential context ('to Firebase (requires authentication)'). Every word earns its place with no redundancy or fluff.

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 is minimal but covers key aspects: purpose and authentication. However, it lacks details on behavioral outcomes (e.g., success/failure responses, side effects) and doesn't fully compensate for the absence of structured data, making it adequate but 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?

With 0 parameters and 100% schema description coverage, the baseline is 4. The description doesn't need to add parameter details, and it appropriately doesn't mention any parameters, focusing on the tool's purpose and constraints instead.

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 ('Save') and the target ('the current draft'), specifying the destination ('to Firebase'). It distinguishes from sibling tools like 'save_local_draft' by mentioning Firebase, but doesn't explicitly contrast with all siblings (e.g., 'publish_level').

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 saving a draft to Firebase, with a prerequisite ('requires authentication'), but doesn't specify when to use this versus alternatives like 'save_local_draft' or 'publish_level'. No explicit when-not scenarios or detailed alternatives 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?

With no annotations provided, the description carries full burden. It states the action is a 'save' operation but doesn't disclose behavioral traits like whether this overwrites previous local drafts, requires authentication, has rate limits, or what happens on failure. The phrase 'snapshot' implies a point-in-time capture but lacks 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?

The description is a single, efficient sentence that front-loads the core action ('save a snapshot') and includes essential qualifiers ('current draft', 'local MCP memory'). There is zero wasted verbiage or redundancy.

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

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

Given the tool's simple nature (0 parameters, no output schema, no annotations), the description is minimally adequate. However, it lacks context about the draft's state (e.g., what constitutes 'current'), persistence characteristics, or how this integrates with sibling tools like 'load_local_draft', leaving gaps in operational 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 tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and it doesn't need to compensate for any schema gaps.

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 ('save a snapshot') and resource ('current draft'), specifying the storage location ('in local MCP memory'). It distinguishes from sibling tools like 'save_draft' (which likely saves remotely) and 'load_local_draft' (which retrieves).

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 'save_draft' or 'list_drafts'. It mentions 'local MCP memory' but doesn't explain why one would choose local over remote storage or when this operation is appropriate.

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 applying a pattern and bootstrapping design, but lacks details on permissions, side effects (e.g., how 'clearExisting' interacts with existing layouts), or response format. This is inadequate for a mutation tool with zero 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 a single, efficient sentence that front-loads the core action and purpose without any wasted words. It's appropriately sized for the tool's complexity.

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

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

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address behavioral traits, usage context, or output details, leaving significant gaps for the agent to operate 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?

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond implying the tool applies patterns for layout design, which aligns with the schema but doesn't provide extra context like examples or edge cases.

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

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

The description clearly states the action ('apply') and the resource ('starter rock skeleton pattern') with the purpose 'to bootstrap solvable layout design'. It's specific about what the tool does, though it doesn't explicitly differentiate from siblings like 'suggest_skeleton_layout' or 'create_level'.

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. The description doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the purpose 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. It discloses a critical behavioral trait ('kills if pressure plate not activated'), which is valuable context beyond basic parameters. However, it lacks details on permissions, rate limits, or response format, leaving gaps 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 a single, efficient sentence that front-loads the core action and includes a crucial behavioral note. There's no wasted verbiage, making it highly concise and well-structured for quick understanding.

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 is moderately complete: it states the action and a key consequence. However, it lacks details on permissions, error handling, or return values, which are important given the tool's potential destructive nature ('kills').

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

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

Schema description coverage is 100%, so the schema already documents the two parameters (x and y coordinates). The description doesn't add any meaning beyond this, such as coordinate ranges or units, but meets the baseline since the schema handles parameter documentation adequately.

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 ('Set barrier position') and resource ('barrier'), making the purpose specific. However, it doesn't explicitly differentiate from sibling tools like 'remove_barrier' or 'set_pressure_plate', which would be needed for 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 like 'remove_barrier' or 'set_pressure_plate', nor does it mention prerequisites or context for usage. The mention of 'kills if pressure plate not activated' hints at a consequence but doesn't frame it as usage 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 full burden for behavioral disclosure. It mentions the goal can be placed 'on edge/wall', which adds some context about placement constraints. However, it doesn't address important behavioral aspects like whether this overwrites existing goals, requires specific permissions, affects game state validation, or has any side effects on other level elements.

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 (8 words) and front-loaded with the core functionality. Every word contributes meaningful information, with zero wasted text or redundancy. The parenthetical adds useful constraint information 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?

For a tool that modifies game/level state (implied by 'Set'), the description is insufficient given no annotations and no output schema. It doesn't explain what happens after setting the goal, whether there are validation rules, what the tool returns, or how it interacts with other level elements. The context of sibling tools suggests this is part of a level editor system, but the description doesn't leverage that 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 100% with both parameters ('x' and 'y') clearly documented as coordinates in the schema. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline expectation but doesn't provide extra value regarding coordinate systems, units, or constraints.

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 ('Set') and the resource ('goal position'), with additional context about placement options ('can be on edge/wall'). It distinguishes from obvious siblings like 'set_start' by focusing on the goal, but doesn't explicitly differentiate from other positioning tools like 'place_tile' or 'move_tile'.

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 about when to use this tool versus alternatives. The description doesn't mention prerequisites, timing considerations, or relationships with other tools like 'set_start' for player positioning or 'place_tile' for general tile placement.

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 that 'Elements outside new bounds are removed,' which is a critical side effect, but doesn't cover other aspects like whether this operation is reversible, requires specific permissions, or affects other level properties. More context on the mutation's impact is needed.

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

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

The description is extremely concise—two sentences that are front-loaded with the main action and a crucial side effect. Every word earns its place, with no wasted information, 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 (a mutation with side effects), no annotations, and no output schema, the description is minimally adequate. It covers the basic action and a key behavioral trait but lacks details on permissions, reversibility, or error handling, leaving gaps for safe 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?

Schema description coverage is 100%, with both parameters ('width' and 'height') well-documented in the schema. The description doesn't add any additional meaning beyond implying the parameters define new grid dimensions, so it meets the baseline for high schema coverage without extra 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 verb ('Resize') and resource ('the level grid'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'clear_level' or 'clear_region' that might also affect grid elements, though the core action is distinct.

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

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active level), exclusions, or related tools like 'clear_level' for full resets, 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 full burden for behavioral disclosure. It states this sets a par value but doesn't explain what happens after setting (e.g., whether it validates against current level state, affects difficulty calculations, or requires saving). For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding the tool's effects.

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

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

The description is a single, efficient sentence that gets straight to the point without unnecessary words. However, it could be slightly more front-loaded by immediately clarifying what 'par' represents in this context.

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

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

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'par' means in this game context, how it relates to level design, what validation occurs, or what the tool returns. Given the complexity implied by sibling tools like 'analyze_difficulty' and 'solve_level', more context about this tool's role would be helpful.

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

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

Schema description coverage is 100%, with the single parameter 'par' fully documented in the schema as 'Par move count (must be positive integer)'. The description adds no additional parameter information beyond what's already in the structured schema, meeting the baseline expectation when schema does the heavy lifting.

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 ('Set explicit par') and the target ('for the current draft'), providing a specific verb+resource combination. However, it doesn't differentiate from the sibling tool 'set_par_to_shortest' which appears to serve a similar purpose, missing an opportunity for clear 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?

No guidance is provided about when to use this tool versus alternatives like 'set_par_to_shortest' or other parameter-setting tools. The description lacks context about prerequisites (e.g., needing a loaded draft) or typical scenarios for setting a custom par value.

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 mentions solving and setting par, implying computational work and mutation, but doesn't specify whether this requires a solvable level, what happens if solving fails, whether changes are saved automatically, or any performance/rate limit considerations. The description is minimal and leaves critical behavioral aspects undefined.

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 directly states what the tool does without any fluff or redundancy. Every word earns its place, and the information is front-loaded with no unnecessary elaboration.

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 implied by 'solve' operations in a level-editing context, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'par' represents in this game context, what 'shortest path length' means, what format the result takes, or any error conditions. For a computational/mutation tool in this domain, more context is needed.

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

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

The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't waste space discussing parameters, maintaining focus on the tool's purpose. A baseline of 4 is appropriate for zero-parameter tools where the schema handles documentation completely.

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 ('solve and set par') and the target ('current solver shortest path length'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'set_par' or 'solve_level', which might have overlapping functionality in this level-editing 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?

The description provides no guidance on when to use this tool versus alternatives like 'set_par' (which likely sets par manually) or 'solve_level' (which might solve without setting par). There's no mention of prerequisites, timing, or contextual constraints for this operation.

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 that setting the position 'deactivates barrier', which hints at a side effect, but doesn't cover critical aspects like whether this is a mutation, requires permissions, has rate limits, or what happens on failure. This leaves significant gaps for a tool that likely modifies game state.

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 core action and includes a relevant side effect ('deactivates barrier'). There is no wasted verbiage, making it highly concise and well-structured.

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 annotations and output schema, and the tool's likely role in modifying game state (inferred from sibling tools like 'set_barrier'), the description is incomplete. It doesn't explain the return value, error conditions, or broader behavioral context needed for safe and effective 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 100% description coverage, with clear documentation for 'x' and 'y' as coordinates. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without adding 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 verb ('Set') and resource ('pressure plate position'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'remove_pressure_plate' or 'set_barrier', which would be needed for 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 like 'remove_pressure_plate' or 'set_barrier', nor does it mention prerequisites or context. It only states the action and an effect ('deactivates barrier'), which is insufficient for usage decisions.

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. 'Set' implies a mutation, but it doesn't disclose behavioral traits like whether this overwrites existing start positions, requires specific permissions, or affects game state. The description is minimal and lacks crucial context 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 a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly, though this brevity contributes to gaps in other dimensions.

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, no output schema, and a mutation tool with behavioral implications, the description is incomplete. It doesn't cover what happens on invocation (e.g., success response, error cases) or how it interacts with other tools, leaving significant gaps for the agent to navigate.

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

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

Schema description coverage is 100%, with clear descriptions for 'x' and 'y' as coordinates. The description adds no additional parameter semantics beyond implying these coordinates define a position, which is already evident from the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 'Set the player start position' clearly states the action (set) and resource (player start position). It's specific about what it does, though it doesn't explicitly differentiate from sibling tools like 'set_goal' or 'place_tile' which might also position game elements.

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 prerequisites (e.g., needing a level loaded), exclusions, or related tools like 'set_goal' for other positions, leaving the agent to infer usage from context 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 states the tool 'simulates' a move, implying a read-only or predictive operation, but doesn't clarify if it modifies any state, requires authentication, has side effects, or what the output looks like (e.g., success/failure, new position). This is inadequate for a tool with potential game logic implications.

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 core action ('simulate a single slide move'). There's no wasted wording, making it easy to parse quickly. However, it could be slightly more informative without losing conciseness, such as hinting at the game context.

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

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

Given the complexity of game simulation tools and the lack of annotations and output schema, the description is incomplete. It doesn't explain the simulation's purpose (e.g., testing moves without affecting state), expected outputs, or how it integrates with other tools like 'get_game_rules'. For a tool that likely impacts game logic, this leaves significant gaps for an agent.

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

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

The input schema has 100% description coverage, with clear parameter definitions (direction with enum, fromX, fromY). The description adds no additional meaning beyond the schema, such as explaining coordinate systems or default behaviors. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 tool 'simulates a single slide move from a position', which clarifies the action (simulate) and resource (slide move). However, it's vague about what 'slide' refers to (likely a game element like a tile or character) and doesn't distinguish it from similar tools like 'move_tile' or 'simulate_playthrough', leaving ambiguity in its specific role.

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. It doesn't mention prerequisites, context (e.g., game state), or compare it to siblings like 'move_tile' (which might perform actual moves) or 'simulate_playthrough' (which might simulate multiple moves). This lack of differentiation makes it hard for an agent to choose appropriately.

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 mentions 'simulate' but doesn't disclose behavioral traits such as whether it's read-only or mutates state, what the simulation output includes (e.g., success/failure, positions), or any side effects like rate limits. This leaves the agent guessing about critical 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?

The description is a single, efficient sentence with no wasted words, making it easy to parse. However, it's front-loaded but under-specified—it could benefit from slightly more detail without losing conciseness, as it currently feels too brief for clarity.

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

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

Given no annotations and no output schema, the description is incomplete for a simulation tool. It lacks context on what the simulation entails (e.g., game mechanics, level state), expected outputs, or error conditions. For a tool that likely interacts with game levels (based on siblings), this leaves significant 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?

Schema description coverage is 100%, with the 'moves' parameter fully documented in the schema as an array of enum strings. The description adds no meaning beyond this, as it doesn't explain the purpose of the moves (e.g., directional inputs for a game) or constraints (e.g., maximum length). Baseline 3 is appropriate since the schema does the heavy lifting.

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 'Simulate a full sequence of moves' states the verb ('simulate') and resource ('sequence of moves'), but it's vague about what exactly is being simulated (e.g., a game level, character movement, puzzle solution). It doesn't distinguish from sibling tools like 'simulate_move' (single move) or 'solve_level' (find solution), leaving ambiguity in scope.

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. For example, it doesn't clarify if this is for testing level designs, predicting outcomes, or debugging, nor does it mention prerequisites like needing a level loaded first. The agent must infer usage from context 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 full burden but offers minimal behavioral insight. It hints at computational aspects ('BFS solver') and outputs ('unsolvable diagnostics'), but doesn't disclose critical traits like whether it modifies the level, requires authentication, has rate limits, or what the diagnostics entail. For a zero-parameter tool with no annotation coverage, 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, dense sentence that efficiently conveys the core functionality without waste. It's front-loaded with the main action ('Run BFS solver') and includes key features concisely. Every word earns its place, making it highly effective for its length.

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 implied by 'BFS solver' and 'diagnostics', along with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., solution path, solvability status) or behavioral constraints, leaving significant gaps for the agent to infer. For a solver tool in a level-editing context, this is inadequate.

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 adds no parameter-specific information, which is acceptable since there are no parameters to document. It doesn't detract from the schema's completeness.

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 ('Run BFS solver') and target ('on current level'), with additional context about features like 'direction balance and unsolvable diagnostics'. It distinguishes from siblings like 'simulate_move' or 'simulate_playthrough' by focusing on automated solving rather than manual simulation. However, it doesn't explicitly differentiate from all potential solving-related tools, keeping it at a 4 instead of 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 prerequisites (e.g., needing a level loaded), exclusions (e.g., not for editing), or compare to siblings like 'analyze_difficulty' or 'validate_quality_gate'. This leaves the agent without context for 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?

No annotations are provided, so the description carries the full burden. It states 'without modifying the current draft,' indicating it's a read-only or non-destructive operation, which is useful. However, it doesn't disclose other behavioral traits such as output format, rate limits, authentication needs, or whether it's idempotent, leaving significant gaps for a tool 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 a single, efficient sentence that front-loads the core purpose ('Suggest starter rock skeleton plans') and adds a key constraint ('without modifying the current draft'). Every word earns its place, with no redundancy or unnecessary elaboration.

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 (suggestion generation), no annotations, no output schema, and 100% schema coverage, the description is minimally adequate. It covers the purpose and non-destructive nature but lacks details on output format, error conditions, or integration with other tools, leaving room for improvement in 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?

Schema description coverage is 100%, with the single parameter 'difficulty' fully documented in the schema (enum values and default). The description adds no parameter-specific information beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without compensating 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: 'Suggest starter rock skeleton plans' (verb+resource). It distinguishes from siblings by specifying 'without modifying the current draft,' which contrasts with modification tools like add_pushable_rock or place_tile. However, it doesn't explicitly differentiate from other suggestion tools like suggest_stop_points.

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: 'without modifying the current draft' suggests this is for planning or ideation phases. However, it lacks explicit guidance on when to use this versus alternatives like seed_layout_pattern or other suggestion tools, and no prerequisites or exclusions are mentioned.

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 'suggests' placements, implying it's a read-only or advisory operation, but doesn't clarify if it modifies the level, requires specific permissions, or has side effects. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 clearly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with every part contributing directly to understanding 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?

Given the tool's moderate complexity (3 parameters, no annotations, no output schema), the description is minimally adequate. It covers the basic purpose but lacks behavioral details, usage context, and output information. With no annotations or output schema, the description should do more to compensate, but it only meets the minimum viable threshold.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters (fromX, fromY, direction) with descriptions and enum values. The description doesn't add any parameter-specific details beyond what's in the schema, such as coordinate units or how direction affects suggestions. Baseline 3 is appropriate when schema does the heavy lifting.

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: 'Suggest blocker placements to stop a slide at intermediate points.' It specifies the action ('suggest'), the resource ('blocker placements'), and the context ('to stop a slide at intermediate points'). However, it doesn't differentiate from sibling tools like 'set_barrier' or 'remove_barrier' that might also involve barrier/blocker manipulation.

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 prerequisites, when not to use it, or how it relates to sibling tools like 'set_barrier' or 'simulate_move' that might affect slide behavior. Usage is implied only by the purpose statement.

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 discloses key behavioral traits: it's a dry-run (non-modifying) operation that both places a tile and solves. However, it doesn't mention what 'solve' entails (e.g., success/failure output, computational limits) or any side effects like temporary state 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?

Single sentence with zero waste—every word earns its place. Front-loaded with the core action ('Dry-run placing one tile and solve'), followed by the critical constraint ('without modifying the draft').

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 and no output schema, the description adequately covers purpose and usage but lacks details on behavioral outcomes (e.g., what 'solve' returns, error conditions). Given the complexity of a combined placement-and-solve operation, more context on output would be helpful.

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

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

Schema description coverage is 100%, so the schema already documents all parameters (x, y, type with enum). The description adds no additional parameter semantics beyond implying they're used for tile placement. Baseline 3 is appropriate when schema does the heavy lifting.

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 ('Dry-run placing one tile and solve') and resource ('the draft'), distinguishing it from siblings like 'place_tile' (which likely modifies) and 'solve_level' (which solves without placement). It explicitly mentions 'without modifying the draft' to differentiate from mutation tools.

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

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

It explicitly states when to use this tool ('Dry-run... without modifying') versus alternatives like 'place_tile' (which would modify) or 'solve_level' (which solves without placement testing). The 'without modifying' clause provides clear 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?

No annotations are provided, so the description carries full burden. While 'undo' implies mutation/reversal, it doesn't disclose what constitutes an 'edit operation', whether it's reversible (via 'redo'), what happens if no edits exist, or any permissions needed. For a mutation tool with zero annotation coverage, 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 with zero wasted words. It's front-loaded with the core action and target, making it immediately understandable.

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 is incomplete. It doesn't explain what 'edit operation' encompasses, what the tool returns, or error conditions. Given the complexity of undo operations in a level editor context, more behavioral context is needed.

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

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

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose.

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 ('undo') and the target ('last edit operation'), providing a specific verb+resource combination. However, it doesn't differentiate from its sibling 'redo', which would be helpful for distinguishing between these closely related operations.

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, nor does it mention prerequisites like requiring an edit history to be available. With many sibling tools for editing operations, explicit usage context would be valuable.

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 'soft-delete,' which hints at non-destructive behavior, but doesn't clarify if the action is reversible, requires specific permissions, or has side effects (e.g., affecting level visibility). This leaves significant gaps 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 a single, efficient sentence that front-loads the core action ('Unpublish (soft-delete)') and resource, with zero wasted words. Every part earns its place by clarifying the operation and scope.

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 is incomplete. It lacks details on behavioral traits (e.g., reversibility, permissions), output format, or error handling, which are crucial for safe agent invocation given the tool's potential impact.

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

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

Schema description coverage is 100%, so the schema already documents both parameters ('levelId' and 'reason') adequately. The description adds no additional meaning beyond what the schema provides, such as explaining the 'reason' parameter's impact or format details, meeting the baseline for high coverage.

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

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

The description clearly states the action ('Unpublish (soft-delete)') and resource ('one of your marketplace levels by ID'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_draft' or 'restore_published_level', 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 (e.g., 'delete_draft' for drafts or 'clear_level' for local levels), nor does it mention prerequisites like needing a published level. It only implies usage by specifying 'your marketplace levels,' which is minimal context.

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

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

No annotations are provided, so the description carries the full burden. It mentions 'Run... checks' but doesn't disclose behavioral traits such as whether this is a read-only operation, if it modifies data, what permissions are needed, or how results are returned. The term 'checks' implies analysis, but specifics like output format or error handling 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 a single, efficient sentence that front-loads the purpose ('Run canonical parity/quality checks') and lists specific examples. It avoids unnecessary words, though it could be slightly more structured (e.g., separating examples with commas). Every part contributes to understanding the tool's scope.

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 is incomplete. It specifies what checks are run but lacks details on behavior, results, or usage context. For a validation tool with potential side effects or complex outputs, more information is needed to guide an AI agent 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?

Schema description coverage is 100%, so the schema fully documents the single parameter 'requirePar'. The description adds no parameter-specific information beyond what's in the schema, but it implies the checks relate to parity/quality, which aligns with the parameter's purpose. Baseline 3 is appropriate as the schema handles parameter documentation.

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 ('Run') and the type of checks ('canonical parity/quality checks'), with specific examples listed (par-shortest, timeout rule, warp parity, hot coals shortcut diagnostics). It distinguishes this tool from siblings by focusing on validation rather than creation, editing, or analysis, though it doesn't explicitly name alternatives.

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

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

No explicit guidance is provided on when to use this tool versus alternatives. The description lists specific checks but doesn't indicate context (e.g., after level creation, before publishing) or exclusions. Sibling tools like 'check_publish_readiness' or 'analyze_difficulty' might overlap, but no comparison is made.

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 shows ASCII art, implying a read-only display operation, but doesn't disclose any behavioral traits like whether it requires a loaded level, if it's idempotent, or what happens on errors. For a tool with no annotations, this is insufficient to inform safe usage.

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, clear sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for the tool's complexity, making it easy to parse 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 (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks context on usage, behavioral details, and output format. Without annotations or output schema, more completeness is needed for safe agent invocation, but it meets a basic threshold.

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