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 creation operation but doesn't mention whether it requires specific permissions, what happens on success/failure, whether it's idempotent, or any rate limits. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps for the agent.

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 that efficiently communicates the core purpose. There's no wasted language or unnecessary elaboration. It's appropriately sized for a tool with a straightforward purpose, though the brevity comes at the cost of completeness 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?

For a mutation tool with no annotations, no output schema, and incomplete parameter documentation, the description is inadequate. It doesn't explain what happens after creation, what the response looks like, error conditions, or how this tool fits into the broader context of the Airtable-like system. The agent lacks crucial information to use this tool effectively.

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

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

Schema description coverage is 67%, with the 'field' object having detailed properties documented in the schema. The description doesn't add any parameter information beyond what's in the schema - it doesn't explain what 'base_id' or 'table_id' refer to, what field types are available, or provide examples. With moderate schema coverage, the baseline 3 is appropriate as the description doesn't compensate for the coverage gap.

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') and resource ('new field in a table'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'create_record' or 'create_table' by specifying it creates a field rather than a record or table. However, it doesn't specify what kind of field or provide additional context about the field types available.

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 (like needing a base and table first), when not to use it, or how it relates to sibling tools like 'update_field' or 'create_table'. The agent must infer usage from the tool name and schema 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. While 'Create' implies a write/mutation operation, the description doesn't address permissions required, whether the operation is idempotent, what happens on conflicts, or what the response contains. For a mutation tool with zero annotation coverage, this leaves critical behavioral traits unspecified.

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 core purpose without any fluff. It's front-loaded and wastes no words, making it easy to parse quickly. Every word earns its place in conveying the essential 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 (a mutation tool with 3 required parameters, no annotations, and no output schema), the description is incomplete. It doesn't address behavioral aspects like side effects, error conditions, or return values, nor does it provide usage context relative to siblings. For a tool that creates database records, more guidance is needed to ensure correct invocation.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters (base_id, table_name, fields) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain format expectations, constraints, or examples. Baseline 3 is appropriate when 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 clearly states the verb ('Create') and resource ('new record in a table'), making the purpose immediately understandable. It distinguishes from siblings like 'create_field' or 'create_table' by specifying 'record' rather than other database objects. However, it doesn't explicitly differentiate from 'update_record' in terms of creating vs. modifying existing records.

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 base and table), when to choose 'create_record' over 'update_record', or any constraints on usage. With multiple sibling tools available, this lack of contextual guidance is a significant gap.

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 action ('Create') without disclosing behavioral traits. It doesn't mention permissions required, whether the operation is idempotent, what happens on conflicts (e.g., duplicate table names), or the response format. 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 with zero waste. It's front-loaded with the core action and resource, making it easy to scan and understand quickly.

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

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

Given the complexity of creating a table with multiple parameters and no annotations or output schema, the description is inadequate. It doesn't cover behavioral aspects, usage context, or return values, leaving significant gaps for an AI agent to understand how to invoke this tool correctly.

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

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

The schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't explain relationships between parameters like how 'fields' relate to 'table_name'). Baseline 3 is appropriate when 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 clearly states the verb ('Create') and resource ('new table in a base'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_field' or 'create_record', which also create resources in bases, so it doesn't fully distinguish its specific 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing base), exclusions, or comparisons to siblings like 'create_field' (for adding fields to existing tables) or 'update_table' (for modifying tables).

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 is 'Delete,' implying a destructive mutation, but does not address critical aspects like whether deletion is permanent, requires specific permissions, has side effects, or provides confirmation. This is a significant gap for a destructive operation.

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

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

The description is a single, direct sentence with zero wasted words. It is appropriately sized and front-loaded, efficiently conveying the core action without unnecessary details.

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 and lack of annotations or output schema, the description is incomplete. It fails to address behavioral risks, return values, or error conditions, leaving the agent with insufficient information 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, clearly documenting all three parameters (base_id, table_name, record_id). The description does not add any meaning beyond the schema, such as explaining relationships between parameters or providing examples. Baseline 3 is appropriate as the schema handles 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 ('Delete') and resource ('a record from a table'), making the purpose immediately understandable. However, it does not differentiate from sibling tools like 'update_record' or 'create_record' beyond the verb, which would require more specificity about what distinguishes deletion from other 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. It does not mention prerequisites, such as needing an existing record, or compare it to siblings like 'update_record' for modifications. 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a read operation ('Get'), but doesn't mention permission requirements, error handling (e.g., what happens if ID doesn't exist), rate limits, or response format. This leaves significant gaps for a tool that interacts with data.

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 wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information about what the tool does.

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 data retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what a 'record' contains, what format the response takes, or any behavioral aspects like error conditions. Given the complexity of interacting with a database-like system and the lack of structured metadata, 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 description mentions retrieving by 'ID' which maps to the 'record_id' parameter, but doesn't explain the purpose of 'base_id' and 'table_name' parameters or their relationship. With 100% schema description coverage, the schema documents all parameters adequately, so the description adds minimal value beyond what's already in the structured data.

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

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('a single record'), and specifies the key identifier ('by its ID'). However, it doesn't explicitly differentiate from sibling tools like 'list_records' or 'search_records' which also retrieve records but with different approaches.

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 'list_records' (for multiple records) or 'search_records' (for query-based retrieval). It mentions the ID requirement but doesn't explain when direct ID lookup is preferred over other 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it lists 'accessible' bases, implying some permission-based filtering, but doesn't specify what 'accessible' means, whether it requires authentication, or details about the return format (e.g., pagination, fields included). This leaves significant gaps 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 that directly states the tool's purpose without any wasted words. It's front-loaded and appropriately sized for a simple 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 tool's simplicity (0 parameters) but lack of annotations and output schema, the description is incomplete. It doesn't explain what 'accessible' entails, the format of returned data, or any behavioral aspects like error handling, making it inadequate for full agent understanding despite the low complexity.

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 appropriately doesn't discuss parameters, as there are none to explain, which aligns well with 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 verb ('List') and resource ('all accessible Airtable bases'), making the purpose immediately understandable. It doesn't distinguish from siblings like 'list_tables' or 'list_records', which would require mentioning it returns bases rather than tables or records, so it lacks full 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 like 'list_tables' or 'list_records'. It doesn't mention prerequisites, such as needing authentication or specific permissions to access bases, or any 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?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the action but does not disclose pagination behavior, rate limits, permissions needed, or output format. This is inadequate for a read operation with potential complexity.

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 is front-loaded and appropriately sized for a simple tool, making it easy to parse 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, no output schema, and a read operation with potential behavioral nuances (e.g., pagination, ordering), the description is incomplete. It fails to address key contextual aspects like return format or limitations, leaving significant gaps for agent understanding.

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

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

Schema description coverage is 100%, so the schema documents all parameters (base_id, table_name, max_records). The description adds no additional meaning beyond implying a table context, matching the baseline for high schema coverage without extra param details.

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

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

The description 'List records in a table' clearly states the action (list) and target resource (records in a table), distinguishing it from siblings like get_record (singular fetch) or search_records (filtered search). However, it lacks specificity about scope or format, 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 guidance is provided on when to use this tool versus alternatives like search_records or get_record. The description implies a basic listing operation but does not specify use cases, prerequisites, or exclusions, 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 action but doesn't describe key behaviors: whether this is a read-only operation (implied but not explicit), if it requires specific permissions, what the output format looks like (e.g., list of table names or full metadata), or if there are pagination/rate limits. For a tool with zero annotation coverage, this leaves significant gaps.

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

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

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action ('List all tables'), making it immediately scannable. Every word earns its place by conveying essential information without redundancy.

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

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

Given the tool's low complexity (single parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks context about behavioral traits, output format, or usage guidelines. For a simple list operation, this might suffice, but it doesn't provide enough information for confident tool selection in all scenarios.

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 single parameter 'base_id' clearly documented. The description doesn't add any meaning beyond what the schema provides (e.g., it doesn't explain what a 'base' is or where to find the ID). 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 verb ('List') and resource ('all tables in a base'), making the purpose immediately understandable. It distinguishes itself from siblings like list_bases (which lists bases) and list_records (which lists records within tables). However, it doesn't specify whether this includes hidden or system tables, which would make it 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 prerequisites (like needing a valid base_id), compare it to similar tools like list_bases, or indicate scenarios where other tools (like search_records for filtering) might be more appropriate. The agent must 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 action ('search') but doesn't describe key behaviors: whether it returns all matches or is paginated, if the search is case-sensitive or supports wildcards, what happens on no matches (empty list or error), or any rate limits. This leaves significant gaps for a tool with 4 required parameters.

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

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

The description is a single, efficient sentence with zero wasted words. It front-loads the core action ('search for records') and specifies the context ('in a table'), making it immediately clear. Every word earns its place, and there's 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?

Given the tool's complexity (4 required parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain the return format (e.g., list of records, error handling), search behavior, or how to interpret results. Sibling tools suggest a rich context (e.g., CRUD operations on bases/tables/records), but this description lacks necessary details 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%, so the schema fully documents all 4 parameters (base_id, table_name, field_name, value). The description adds no additional semantic context beyond implying a search operation, such as how the value parameter is used (e.g., exact match, substring). This meets the baseline for high schema coverage but doesn't enhance understanding.

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 ('search') and resource ('records in a table'), making the purpose immediately understandable. It distinguishes itself from siblings like 'get_record' (singular retrieval) and 'list_records' (unfiltered listing). However, it doesn't specify the scope or type of search (e.g., exact match, partial, case-sensitive), 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 like 'list_records' (for unfiltered listing) or 'get_record' (for retrieving a specific record by ID). It also doesn't mention prerequisites, such as needing to know the base and table structure first, which could be inferred from sibling tools like 'list_bases' and 'list_tables'.

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 an update operation, implying mutation, but doesn't mention permissions required, whether changes are reversible, rate limits, or what happens to existing field data. 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. It's appropriately sized and front-loaded, directly stating 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?

For a mutation tool with 4 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'updates' contains, how options are structured, or what the tool returns. Given the complexity and lack of structured data, 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?

The description doesn't add any parameter-specific information beyond what's in the input schema, which has 75% coverage. It doesn't explain the structure of 'updates' or clarify the purpose of IDs like 'base_id' and 'table_id'. Since schema coverage is moderate, the baseline score of 3 is appropriate, but the description doesn't compensate for the 25% gap.

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

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

The description clearly states the verb ('Update') and resource ('a field in a table'), making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'update_table' or 'update_record', which also perform updates on related resources in the same 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?

No guidance is provided on when to use this tool versus alternatives like 'update_table' or 'update_record'. The description lacks context about prerequisites (e.g., needing existing base/table/field IDs) or exclusions, leaving the agent to infer usage from the tool name and parameters alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a mutation operation but doesn't cover critical aspects like required permissions, whether updates are reversible, error handling for invalid inputs, or rate limits. This leaves significant gaps for a tool that modifies data.

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, clearly front-loading the core purpose. It's appropriately sized for a straightforward tool, 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 complexity of a mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits, error conditions, or what the tool returns, leaving the agent with incomplete 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?

Schema description coverage is 100%, so the input schema fully documents all four parameters (base_id, table_name, record_id, fields). The description adds no additional meaning beyond what's in the schema, such as explaining the structure of 'fields' or providing examples, which aligns with the baseline score when schema coverage is high.

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 ('Update') and target ('an existing record in a table'), which is specific and distinguishes it from siblings like create_record or delete_record. However, it doesn't specify what kind of updates are possible (e.g., field modifications) beyond the basic verb+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 like update_field or update_table, nor does it mention prerequisites such as needing an existing record ID. The description only states what it does, not when or why 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Update a table's schema,' implying a mutation operation, but fails to describe critical behaviors: whether it requires specific permissions, if changes are reversible, what happens to existing data, or error conditions. 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 wasted words. It is front-loaded with the core action and resource, making it easy to parse. Every word earns its place, achieving optimal conciseness without sacrificing clarity for the given content.

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 mutation tool (updating a table schema) with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits (e.g., side effects, permissions), usage context, and expected outcomes. While the schema covers parameters well, the overall context for safe and effective tool invocation is insufficient.

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 documentation (e.g., 'ID of the base,' 'New name for the table'). The description adds no additional meaning beyond the schema, such as explaining parameter interactions or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but no extra credit is earned.

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 ('Update') and the resource ('a table's schema'), making the purpose understandable. It distinguishes from siblings like 'update_record' or 'update_field' by specifying the table schema as the target. However, it doesn't explicitly mention what aspects of the schema can be updated (e.g., name, description), which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing base and table IDs), exclusions (e.g., not for updating table data), or comparisons to siblings like 'update_field' (for field-level changes) or 'create_table' (for new tables). 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.