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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a 'safe, validated interface' that validates parameters against Pydantic models and rejects extra fields. It mentions that 'some methods may have nested parameter structures' and provides examples of destructive operations (delete_user, delete_factor). However, it doesn't cover rate limits, authentication requirements, or error handling.

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

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

The description is appropriately front-loaded with the core purpose and key capabilities, but it includes extensive lists and examples that could be streamlined. The 'AVAILABLE METHODS' section and multiple examples add value but make the description lengthy. Every sentence earns its place, but the structure could be more concise by integrating examples more tightly or referencing external documentation earlier.

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 (2 parameters with nested objects, no output schema, no annotations), the description is largely complete. It covers purpose, usage, behavioral traits, and parameter semantics thoroughly. However, it lacks details on return values (since no output schema exists) and doesn't mention authentication or error scenarios. The reference to 'get_auth_admin_methods_spec' for full documentation helps mitigate gaps.

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

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

The input schema has 0% description coverage and only defines 'method' (string) and 'params' (object) without semantic details. The description compensates fully by listing all available methods with brief explanations (e.g., 'get_user_by_id: Retrieve a user by their ID'), providing detailed examples with parameter structures, and explaining that parameters must adhere to Python SDK specifications. This adds substantial meaning beyond the minimal schema.

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

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

The description clearly states the tool's purpose: 'Call an Auth Admin method from Supabase Python SDK' with a specific verb ('call') and resource ('Auth Admin method'). It distinguishes from siblings like 'get_auth_admin_methods_spec' (which retrieves documentation) and 'send_management_api_request' (which handles different API types). The bullet points further clarify capabilities like user management and authentication tasks.

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

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

The description provides explicit guidance on when to use this tool vs alternatives. It states to 'use the get_auth_admin_methods_spec tool' for complete documentation of methods and parameters, distinguishing it from that sibling. The 'IMPORTANT NOTES' section also outlines prerequisites like adhering to Python SDK specifications and validation rules, though it doesn't explicitly mention when not to use it.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's for executing high-risk operations, requires user confirmation, uses a confirmation ID from a previous error, executes the original query as-is, and includes a security note about 5-minute expiration. However, it doesn't detail potential side effects (e.g., data loss specifics) or error handling, leaving some gaps in full 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 well-structured with clear sections (HOW IT WORKS, STEPS, PARAMETERS, NOTE), making it easy to scan. Each sentence adds value, such as explaining the confirmation process and security constraints. It could be slightly more concise by integrating some details (e.g., merging the STEPS and PARAMETERS sections), but overall, it's efficient and front-loaded with the core purpose.

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

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

Given the tool's complexity (destructive operations, confirmation flow) and lack of annotations or output schema, the description does a good job of covering essential context: purpose, usage steps, parameters, and security notes. It addresses the high-risk nature and user interaction requirements. However, it doesn't specify what happens after execution (e.g., success/failure responses or side effects), which is a minor gap for such a critical tool.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaningful context for all three parameters: 'operation_type' is explained as 'Type of operation ("api" or "database")', 'confirmation_id' as 'The ID provided in the error message (required)', and 'user_confirmation' as 'Set to true to confirm execution (default: false)'. This goes beyond the schema's basic titles and enums, clarifying usage and requirements. A point is deducted because it doesn't elaborate on the implications of each operation_type choice.

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: 'Execute a destructive database or API operation after confirmation.' It specifies the verb ('execute'), resource ('destructive database or API operation'), and the key condition ('after confirmation'). The title 'confirm_destructive_operation' reinforces this, and it distinguishes itself from siblings like 'live_dangerously' or 'execute_postgresql' by focusing on confirmation of previously rejected high-risk 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 explicit guidance on when to use this tool: 'Use this only after reviewing the risks with the user.' It outlines a clear process (explain risks, get approval, use confirmation ID) and specifies prerequisites (confirmation ID from an error message). It also distinguishes usage from alternatives by noting that no retyping of queries is needed, which sets it apart from tools like 'execute_postgresql' or 'send_management_api_request' that might require full parameter input.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so comprehensively. It details safety modes (SAFE/UNSAFE), risk categorization (LOW/MEDIUM/HIGH/EXTREME), transaction handling restrictions, migration version control, confirmation flows for destructive operations, and important operational guidelines. This provides rich behavioral context beyond basic functionality.

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

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

The description is well-structured with clear sections (OPERATION TYPES, MIGRATION HANDLING, SAFETY SYSTEM, etc.) but is quite lengthy. While most content is valuable, some redundancy exists (e.g., multiple mentions of UNSAFE mode requirements). The front-loading is good with purpose and immediate requirements, but the length may challenge quick comprehension.

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

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

Given the complexity of a database execution tool with 2 parameters, no annotations, and no output schema, the description provides exceptional completeness. It covers purpose, usage guidelines, behavioral traits, parameter semantics, safety systems, transaction handling, migration control, confirmation flows, and sibling tool relationships. This fully compensates for the lack of structured metadata.

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

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

With 0% schema description coverage for the 2 parameters, the description compensates well by explaining both parameters' semantics. It describes 'migration_name' in detail (format requirements, examples, what happens if not provided, sanitization, timestamp prefixing) and 'query' through extensive examples and requirements (semicolon termination, operation types). While comprehensive, it doesn't explicitly map all schema properties like the default value for migration_name.

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: 'Execute PostgreSQL statements against your Supabase database.' It specifies the exact action (execute) and resource (PostgreSQL statements/Supabase database), distinguishing it from sibling tools like call_auth_admin_method or send_management_api_request that handle different aspects of the system.

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

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

The description provides explicit guidance on when to use this tool versus alternatives. It includes a dedicated section 'WHEN TO USE OTHER TOOLS INSTEAD' that names specific sibling tools (call_auth_admin_method, send_management_api_request) and explains what operations they handle instead. It also provides detailed context about different operation types and their requirements.

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 describes what the tool returns ('comprehensive dictionary' with method details) and clarifies it requires no parameters, which is helpful. However, it doesn't mention behavioral aspects like whether this is a read-only operation, if it makes external API calls, potential rate limits, or error conditions.

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

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

The description is well-structured and front-loaded with the core purpose. Every sentence adds value: the first states what it does, the second details the return content, the third explains usage context, and the fourth clarifies no parameters needed. There is no wasted text.

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

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

Given the tool has 0 parameters, no annotations, and no output schema, the description does a good job explaining the purpose, return format, and usage context. However, it could be more complete by specifying the exact structure of the returned dictionary or any prerequisites, though the lack of output schema lowers the bar.

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 explicitly states 'No parameters required,' which reinforces this clearly and adds value by preventing parameter confusion.

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

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

The description clearly states the specific action ('Get Python SDK methods specification for Auth Admin') and resource ('Auth Admin methods available in the Supabase Python SDK'). It distinguishes from sibling tools by focusing exclusively on Auth Admin SDK methods, unlike broader tools like get_management_api_spec or get_schemas.

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

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

The description explicitly states when to use this tool ('useful for exploring the capabilities of the Auth Admin SDK and understanding how to properly format parameters for the call_auth_admin_method tool'), providing clear context and naming the specific alternative tool (call_auth_admin_method) it prepares for.

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

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

With no annotations provided, the description carries full burden and does an excellent job disclosing behavioral traits. It explicitly states this is a 'low-risk read operation that can be executed in SAFE mode,' describes what information is returned (endpoints, parameters, schemas, auth requirements, safety info), and explains the four different usage patterns. The only minor gap is lack of information about rate limits or pagination, but overall it provides comprehensive behavioral context.

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

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

The description is well-structured and appropriately sized, with clear sections for purpose, usage patterns, parameters, domains, and utility. While comprehensive, every sentence earns its place by adding value. The only minor issue is some redundancy in the safety statement at the end, but overall it's front-loaded with the core purpose and efficiently organized.

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 tool that returns API specifications with multiple usage patterns, and with no annotations and no output schema, the description provides complete context. It explains what the tool does, how to use it in different scenarios, what parameters mean, what domains are available, what information the specification contains, and safety considerations. This fully compensates for the lack of structured metadata.

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

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

With 0% schema description coverage (the schema only shows 'params' as an object with no properties documented), the description fully compensates by providing detailed parameter semantics. It explains all four optional parameters (path, method, domain, all_paths) with examples and clear descriptions of what each does. It also lists available domain values with explanations, effectively documenting what would normally be in the schema's enum or property descriptions.

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

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

The description clearly states the tool's purpose: 'Get the complete Supabase Management API specification' with specific details about what it returns (OpenAPI spec including endpoints, parameters, schemas, auth requirements, safety info). It distinguishes from sibling tools like 'get_auth_admin_methods_spec' by covering the entire Management API rather than just auth methods, and from 'send_management_api_request' by providing documentation rather than executing requests.

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

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

The description provides explicit usage guidelines with four distinct scenarios: 1) without parameters returns all domains, 2) with path and method returns specific endpoint spec, 3) with domain only returns all paths/methods in that domain, 4) with all_paths=True returns all paths/methods. It also explains when this tool is useful (understanding available operations, request formatting, unsafe mode requirements, response structures), giving clear context for when to use it versus alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('List'), implying it's non-destructive, but doesn't cover other important aspects like authentication requirements, rate limits, error handling, or what the output format 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 a single, efficient sentence that states exactly what the tool does with zero wasted words. It's front-loaded with the core purpose and includes key details (sizes and table counts) 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 simplicity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains what the tool returns (schemas with sizes and table counts), but without annotations or output schema, it doesn't specify the return format, data types, or any behavioral constraints. This is a minimal viable description.

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% (though empty). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for tools with no parameters. It appropriately doesn't mention any parameters.

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

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

The description clearly states the tool's purpose with a specific verb ('List') and resource ('database schemas'), along with what information is included ('sizes and table counts'). It distinguishes from siblings like 'get_tables' and 'get_table_schema' by focusing on schemas rather than tables. However, it doesn't explicitly differentiate from all siblings, so it's not a perfect 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'get_tables' or 'get_table_schema', nor does it specify any prerequisites or exclusions. The agent must 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 that this is a 'low-risk read operation' and can be executed in 'SAFE mode', which clarifies safety and behavioral traits. However, it lacks details on rate limits, permissions needed, or potential performance impacts.

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

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

The description is well-structured with a clear summary, bulleted details, and a dedicated safety note. It is appropriately sized, but could be slightly more concise by integrating the safety note into the main text.

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

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

Given no annotations and no output schema, the description does a good job explaining the tool's purpose, parameters, and safety. It lists the information returned (e.g., row counts, sizes), but could benefit from clarifying the output format or any limitations.

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

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

The schema description coverage is 0%, so the description must compensate. It explicitly defines the single parameter 'schema_name' with meaning ('Name of the schema to inspect') and examples ('public', 'auth'), adding significant value beyond the bare schema.

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

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

The description clearly states the verb ('List') and resource ('all tables, foreign tables, and views in a schema') with specific attributes ('sizes, row counts, and metadata'). It distinguishes from siblings like get_schemas (which lists schemas) and get_table_schema (which provides schema details for a single table).

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 inspecting database objects in a schema, but does not explicitly state when to use this tool versus alternatives like get_schemas or get_table_schema. No exclusions or prerequisites are mentioned, leaving some ambiguity in 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 and does well by explicitly stating 'This is a low-risk read operation that can be executed in SAFE mode.' It discloses safety profile and operational mode, though it could add more about rate limits, permissions needed, or response format.

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?

Perfectly structured with purpose statement, bulleted return details, parameter section, and safety note. Every sentence earns its place, and information is front-loaded with the core purpose first.

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 2 parameters and no output schema, the description provides good coverage of purpose, parameters, and safety. It could benefit from more detail about the return format or example output, but given the context signals, it's mostly complete.

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

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

Schema description coverage is 0%, so the description must compensate. It provides clear semantic meaning for both parameters with examples (schema_name: 'public', 'auth') and clarifies that 'table' is the specific table to inspect. This adds significant value beyond the bare schema.

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

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

The description clearly states the verb 'Get' and resource 'detailed table structure', specifying what information is returned (columns, keys, relationships). It distinguishes from sibling tools like get_schemas and get_tables by focusing on detailed structural metadata rather than lists of objects.

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

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

The description implies usage context through the parameter descriptions and safety note, but doesn't explicitly state when to use this tool versus alternatives like get_tables or execute_postgresql. It provides clear context for inspecting table structure but lacks explicit exclusions or named alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so comprehensively. It explains the safety modes in detail (SAFE vs. UNSAFE for both Database and API), describes risk levels (LOW, MEDIUM, HIGH, EXTREME), and explicitly states that the tool 'affects ALL subsequent operations for the specified service until changed again,' which is crucial behavioral context not evident from the schema alone.

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

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

The description is well-structured with clear sections (WHAT THIS TOOL DOES, SAFETY MODES EXPLAINED, etc.) and front-loads the core purpose. While comprehensive, some sections like OPERATION RISK LEVELS could be slightly more concise, but every sentence adds valuable context for a safety-critical tool.

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

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

For a tool with 2 parameters, 0% schema description coverage, no annotations, and no output schema, the description provides complete context. It explains what the tool does, when to use it, detailed behavioral implications, parameter meanings, examples, and important notes about persistence of the mode change. No additional information is needed for an agent to use this tool correctly.

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

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

With 0% schema description coverage, the description fully compensates by explaining both parameters in detail. It defines 'service' as 'api' or 'database' with clear explanations of what each service controls, and explains 'enable_unsafe_mode' as a boolean with default False, including specific examples of how to use both parameters together in different scenarios.

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 'switches between safe (default) and unsafe operation modes for either the Management API or Database operations,' providing a specific verb ('toggle'/'switch') and resources (API/Database). It distinguishes from siblings by focusing on safety mode configuration rather than direct operations like execute_postgresql or send_management_api_request.

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

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

The description explicitly states when to use this tool ('BEFORE attempting write operations or schema changes'), when not to use it ('Start in safe mode by default for exploration and analysis'), and provides clear alternatives (safe vs. unsafe modes). It also gives specific guidance on risk considerations and returning to safe mode after 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?

With no annotations provided, the description carries the full burden of behavioral disclosure and does so comprehensively. It explains the tool's operation ('makes a request to the Supabase Management API endpoint'), includes safety considerations (low-risk read operation, requires Personal Access Token, not available for local instances), and provides metadata structure details crucial for effective use. The 'HOW IT WORKS' and 'SAFETY CONSIDERATIONS' sections add significant value beyond basic functionality.

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

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

The description is well-structured with clear sections (PARAMETERS, HOW IT WORKS, EXAMPLES, METADATA STRUCTURE, SAFETY CONSIDERATIONS) that make information easy to find. While comprehensive, some sections like the detailed log collection list (10 items) could be more concise, though each serves a purpose in helping users select the right collection. The front-loaded purpose statement is clear and effective.

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 6 parameters, 0% schema coverage, no annotations, and no output schema, the description provides complete contextual information. It covers purpose, parameters with semantics, usage examples, operational mechanics, metadata structure, safety considerations, and even troubleshooting guidance ('NOTE FOR LLM CLIENTS'). This fully compensates for the lack of structured documentation elsewhere.

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

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

Given 0% schema description coverage for 6 parameters, the description compensates exceptionally well. It provides detailed explanations for each parameter including required status, default values, format specifications (especially for the complex 'filters' array), and practical examples showing how to use them. The 'AVAILABLE LOG COLLECTIONS' section effectively documents the valid values for the 'collection' parameter despite no enum 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 tool's purpose as 'Retrieve logs from your Supabase project's services for debugging and monitoring' with specific verb ('retrieve') and resource ('logs'), and distinguishes it from siblings like 'execute_postgresql' or 'retrieve_migrations' by focusing on log retrieval across multiple services rather than database queries or migration history.

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

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

The description provides clear context for when to use this tool (debugging and monitoring Supabase services) and mentions it provides 'access to the same logs available in the Supabase dashboard's Logs & Analytics section,' giving users a familiar reference point. However, it doesn't explicitly state when not to use it or name specific alternatives among the 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?

With no annotations provided, the description carries full burden and does well by disclosing the SAFE mode operation, pagination behavior (limit/offset defaults), and pattern matching behavior for name_pattern. It doesn't mention rate limits, authentication needs, or error conditions, but provides solid behavioral context.

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

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

Well-structured with purpose statement, return format details, parameter explanations, and safety note. Every sentence earns its place with no redundancy. The information is front-loaded with the core purpose first.

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 no annotations and no output schema, the description provides good completeness: clear purpose, detailed parameter semantics, safety context, and return format details. It could mention authentication requirements or error scenarios, but covers the essential context well.

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

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

With 0% schema description coverage, the description fully compensates by explaining all 4 parameters in detail: default values, constraints (max: 100), and behavioral semantics (especially the ILIKE pattern matching with automatic wildcards for name_pattern). This adds significant value beyond the bare schema.

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

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

The description clearly states the verb ('Retrieve') and resource ('list of all migrations a user has from Supabase'), with specific details about what information is returned. It distinguishes itself from sibling tools like 'retrieve_logs' or 'get_tables' by focusing specifically on migrations.

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

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

The description implies usage through the SAFE mode note and parameter explanations, but doesn't explicitly state when to use this tool versus alternatives like 'retrieve_logs' or 'get_schemas'. No explicit when-not-to-use guidance or named 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 the full burden of behavioral disclosure and does so comprehensively. It details the safety system with risk categories (LOW, MEDIUM/HIGH, EXTREME, BLOCKED), explains the default SAFE mode, specifies that write operations require UNSAFE mode, describes confirmation requirements for destructive operations, and mentions automatic injection of the {ref} parameter.

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

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

The description is well-structured with clear sections (REQUEST FORMATTING, PARAMETERS, PATH PARAMETERS HANDLING, EXAMPLES, SAFETY SYSTEM, SAFETY CONSIDERATIONS) but is quite lengthy. While every section adds value, it could be more concise by integrating some safety information more tightly with usage guidance.

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 5-parameter API request tool with no annotations and no output schema, the description provides complete context. It covers purpose, usage, parameters, safety considerations, examples, and references to related tools, leaving no significant gaps for an agent to understand and use this tool correctly.

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

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

With 0% schema description coverage for 5 parameters, the description fully compensates by providing detailed parameter explanations. It defines each parameter's purpose, provides examples of valid values, explains how path parameters work with placeholders, and gives concrete usage examples showing all parameters in action.

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 as 'Execute a Supabase Management API request' and specifies it provides 'programmatic access to manage your Supabase project settings, resources, and configurations.' This is a specific verb+resource combination that distinguishes it from sibling tools like execute_postgresql or get_management_api_spec.

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

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

The description provides explicit guidance on when to use this tool versus alternatives, directing users to 'use the get_management_api_spec tool' for endpoint details and 'use the get_management_api_safety_rules tool' for safety specifics. It also clearly explains when write operations require enabling UNSAFE mode via live_dangerously.

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