Airtable MCP

Server Quality Checklist

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Latest release: v3.2.8
Disambiguation4/5
Most tools have distinct purposes, but 'create' and 'upsert' could cause confusion as both handle record creation with overlapping functionality. The other tools target clearly different operations like webhooks, schema description, listing, and querying.
Naming Consistency4/5
The naming is mostly consistent with a verb_noun pattern (e.g., list_bases, create_webhook, refresh_webhook), but 'create', 'describe', 'query', and 'update' deviate by omitting the noun, creating minor inconsistency.
Tool Count5/5
With 11 tools, the count is well-scoped for an Airtable integration, covering core operations like CRUD, webhooks, schema management, and governance without being overwhelming.
Completeness4/5
The toolset provides strong coverage for Airtable operations, including CRUD, querying, webhooks, and governance. A minor gap exists in missing explicit delete operations for records or webhooks, but agents can likely work around this.
Average 3.2/5 across 11 of 11 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 5 commits in the last 12 weeks
- Last stable release on August 5, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 mentions 'upsert' and 'fieldsToMergeOn', implying a conditional create/update based on matching fields, but doesn't explain critical behaviors like mutation effects, error handling, idempotency, or the impact of parameters like 'dryRun' and 'conflictStrategy'. For a complex mutation tool with 8 parameters, this leaves significant gaps in understanding how it operates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is technically concise, but it's under-specified for a tool with 8 parameters and complex behavior. While it avoids unnecessary words, it lacks the detail needed for effective tool use, making it more of an incomplete summary than appropriately concise guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, mutation operation, no annotations) and the presence of an output schema, the description is inadequate. It doesn't explain the upsert logic, parameter roles, or behavioral traits, leaving the agent to rely heavily on the input and output schemas. For a mutation tool with rich parameters but 0% schema coverage, this description provides minimal context beyond the tool name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 8 parameters are documented in the schema. The description only references 'performUpsert.fieldsToMergeOn', which covers one aspect of one parameter. It doesn't explain the purpose of other key parameters like 'baseId', 'table', 'records', 'typecast', 'idempotencyKey', 'dryRun', or 'conflictStrategy', failing to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Upsert Airtable records' which provides a clear verb (upsert) and resource (Airtable records), but it's vague about what 'upsert' specifically means (insert or update based on matching criteria) and doesn't distinguish it from sibling tools like 'create' or 'update'. The mention of 'performUpsert.fieldsToMergeOn' hints at the matching mechanism but doesn't fully clarify the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'create' or 'update'. The description doesn't mention prerequisites, use cases, or exclusions. Without this context, an agent must infer usage from the tool name and parameters alone, which is insufficient for optimal selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'recent exceptions and remediation proposals' which implies a read-only listing operation, but doesn't specify whether this requires authentication, what format the exceptions are in, whether results are paginated (though cursor parameter suggests it might be), or any rate limits. The description adds minimal behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - just 6 words in a single sentence. It's front-loaded with the core purpose. While arguably too brief given the complexity of the tool (4 parameters, no annotations), every word contributes meaning without redundancy. The structure is simple but effective for such a short description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there's an output schema (which handles return values), no annotations, and 4 parameters with 0% schema description coverage, the description is incomplete. It covers the basic purpose but lacks parameter explanations, usage context, and behavioral details that would help an agent use this tool effectively. The presence of an output schema reduces the need to describe return values, but other gaps remain significant.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no information about any of the 4 parameters. With 0% schema description coverage, the schema only provides structural information (types, constraints, enums) without explaining what 'since', 'severity', 'limit', or 'cursor' actually mean in context. The description doesn't compensate for this gap at all - it doesn't mention parameters, their purposes, or how they affect the listing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose ('List recent exceptions and remediation proposals') which is clear but somewhat vague. It specifies the verb 'List' and resource 'exceptions and remediation proposals', but doesn't distinguish this from potential sibling tools like 'list_bases' or 'list_governance' that might handle different resources. The term 'recent' provides some temporal context 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.
Usage Guidelines2/5
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. There's no mention of prerequisites, appropriate contexts, or comparison with sibling tools like 'query' or 'describe' that might handle similar data. The agent must infer usage from the tool name and description alone without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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' which hints at read-only behavior, but doesn't explicitly state that this is a safe read operation, what permissions are required, rate limits, error conditions, or what the output looks like. For a tool with 10 parameters and 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality. Every word earns its place by specifying the action, target, and key capabilities without any fluff or redundancy. It's appropriately sized for a tool with a clear primary function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (10 parameters, 0% schema coverage, no annotations) and the presence of an output schema, the description is incomplete. While the output schema may cover return values, the description doesn't address critical context like authentication needs, error handling, rate limits, or detailed parameter guidance. For a query tool with extensive filtering options, this leaves too much undefined for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning none of the 10 parameters have descriptions in the schema. The tool description only vaguely references 'filtering, sorting, and pagination' without explaining what parameters correspond to these features or their semantics. This fails to compensate for the complete lack of schema documentation, leaving parameters like 'filterByFormula', 'offset', and 'returnFieldsByFieldId' entirely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Query') and resource ('Airtable records') with specific capabilities ('filtering, sorting, and pagination'). It distinguishes from siblings like 'create', 'update', and 'upsert' which are write operations, but doesn't explicitly differentiate from 'describe' or 'list_bases' which might also retrieve data. The purpose is well-defined but could be more specific about what makes this query tool unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'query' over 'list_bases', 'describe', or other read operations, nor does it specify prerequisites or exclusions. The agent must infer usage from the tool name and parameters alone, which is insufficient for optimal selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Create' which implies a write/mutation operation, but doesn't cover permissions needed, whether the operation is idempotent, rate limits, or what happens on failure. 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.
Conciseness5/5
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 redundancy. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool ('Create') with no annotations and no output schema, the description is incomplete. It doesn't explain what a webhook is, what 'for a base' means, what data is returned, or error handling. Given the complexity implied by sibling tools and lack of structured data, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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, but since there are no parameters to explain, it meets the baseline of 4 for this scenario.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and target resource ('a new webhook for a base'), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'refresh_webhook' or 'update', which might also involve webhook operations, 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.
Usage Guidelines2/5
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 'refresh_webhook' or 'update', nor does it mention prerequisites or context for creating a webhook. It's a basic statement with no usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what the tool does but doesn't describe behavioral traits such as whether this is a read-only operation, if it requires authentication, potential rate limits, or what the output format looks like (e.g., list structure, pagination). This is inadequate 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's purpose without any wasted words. It is front-loaded with the essential information and appropriately sized for a simple listing tool with no parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a list of webhook objects, error handling), behavioral constraints, or how it interacts with the default base. For a tool with zero structured data coverage, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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. A baseline of 4 is applied since there are no parameters to document, and the description doesn't introduce unnecessary complexity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Airtable webhooks for the default base'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from sibling tools like 'list_bases' or 'list_exceptions', which would require mentioning what makes webhook listing unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 default base configured), when not to use it, or how it differs from other listing tools like 'list_bases' or querying operations. 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.
Behavior2/5
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. 'Refresh webhook expiration' implies a mutation operation that likely extends or renews something, but it doesn't disclose what permissions are needed, whether this is idempotent, what happens if the webhook doesn't exist, or what the response looks like. For a mutation tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 operation and gets straight to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool (implied by 'refresh') with no annotations and no output schema, the description is incomplete. It doesn't explain what 'refresh' actually means operationally, what the expected outcome is, or any error conditions. For a tool that presumably modifies system state, this leaves too many questions unanswered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 parameter situation. The description doesn't need to add parameter information, and it appropriately doesn't mention any parameters. This meets the baseline expectation for a zero-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('refresh') and the resource ('webhook expiration'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from potential sibling tools like 'create_webhook' or 'update' that might also affect webhooks, 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.
Usage Guidelines2/5
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 'create_webhook', 'list_webhooks', and 'update' available, there's no indication of when refresh_webhook is appropriate versus those other operations. The description is purely functional without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 indicates a read operation ('return'), but lacks details on permissions, rate limits, data format, or any side effects. 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.
Conciseness5/5
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 is 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, it lacks behavioral context (e.g., permissions, data format) and doesn't differentiate from siblings, leaving gaps in completeness for a read operation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 information, and it appropriately avoids redundancy. A baseline of 4 is given since no parameters are present.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('return') and resources ('governance allow-lists and PII masking policies'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'list_bases' or 'list_exceptions', 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.
Usage Guidelines2/5
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_bases' or 'list_exceptions', nor does it mention any prerequisites or exclusions. It simply states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the tool's function and detailLevel optimization, but doesn't describe important behavioral aspects like whether this is a read-only operation, what permissions are required, rate limits, error conditions, or what the output looks like. The description is insufficient for a mutation-sensitive agent to understand the tool's behavior fully.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with two sentences: the first states the purpose, and the second provides specific guidance about the detailLevel parameter. Every sentence earns its place with no wasted words, and the information is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there's an output schema (which means the description doesn't need to explain return values) and no annotations, the description provides adequate basic purpose and parameter guidance. However, for a tool with 6 parameters and 0% schema description coverage, the description should do more to explain parameter semantics and behavioral context to be truly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides meaningful context for the detailLevel parameter by explaining what each enum value returns, which adds significant value beyond the 0% schema description coverage. However, it doesn't explain the semantics of other parameters like scope, baseId, table, includeFields, or includeViews, leaving 5 of the 6 parameters without semantic explanation in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 describing Airtable base or table schema, which is a specific verb+resource combination. However, it doesn't explicitly distinguish this from sibling tools like 'list_bases' or 'query', which might also provide schema information in different contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage guidance by explaining how to use the detailLevel parameter to optimize context usage, which implies when to choose different detail levels. However, it doesn't explicitly state when to use this tool versus alternatives like 'list_bases' or 'query', nor does it provide exclusion criteria or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 reveals the dryRun workflow requirement, which is valuable behavioral context. However, it doesn't disclose other important traits like authentication needs, rate limits, error handling, or what constitutes a successful update. The description adds some value but 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that communicates the core purpose and a critical workflow requirement. Every word earns its place, with no wasted text. The structure is front-loaded with the main purpose followed by the important constraint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex update tool with 8 parameters, 0% schema coverage, no annotations, but with an output schema, the description is incomplete. The dryRun guidance is helpful, but it doesn't cover parameter meanings, error conditions, or behavioral expectations. The output schema helps with return values, but the description should do more given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 8 parameters, the description provides almost no parameter information. It mentions 'dryRun' implicitly in the workflow guidance, but doesn't explain any of the other 7 parameters (baseId, table, records, typecast, idempotencyKey, conflictStrategy, ifUnchangedHash). The description fails to compensate for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Airtable records'), making the purpose immediately understandable. It distinguishes from siblings like 'create', 'upsert', and 'query' by focusing on modifying existing records. However, it doesn't explicitly differentiate from 'upsert' which might also update records.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance about a prerequisite workflow ('requires diff-before-write via dryRun first'), which gives important context about when to use this tool. It doesn't mention alternatives like 'upsert' or 'create', but the dryRun requirement provides meaningful usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 mentions the 'dryRun' requirement, which is a behavioral constraint, but doesn't cover other important aspects like permissions needed, rate limits, error handling, or what happens on successful creation. It adds some context but 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.
Conciseness5/5
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 immediately follows with the critical usage requirement. There's zero waste—every word earns its place by providing essential information without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there's an output schema (which handles return values), the description doesn't need to explain outputs. However, for a mutation tool with 6 parameters, 0% schema coverage, and no annotations, the description is incomplete. It covers the dry-run requirement well but misses other contextual details like error conditions or side effects, making it only partially adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 6 parameters have descriptions in the schema. The description only mentions 'dryRun' implicitly and doesn't explain any other parameters like 'baseId', 'table', 'records', 'typecast', or 'idempotencyKey'. It fails to compensate for the lack of schema documentation, leaving most parameters semantically unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create Airtable records') and specifies the resource ('Airtable records'), which is a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from its sibling 'upsert' or 'update' tools, which likely handle similar record operations. The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance by stating 'requires diff-before-write via dryRun first,' which indicates a prerequisite workflow. This tells the agent when to use this tool (only after a dry run) and implies an alternative approach (using dryRun parameter). It gives clear context for proper invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the tool's read-only nature implicitly by using 'List', but lacks details on behavioral traits like pagination, rate limits, authentication requirements, or how 'accessible' is defined (e.g., user permissions). The description adds basic context but misses key 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List all accessible Airtable bases') and adds specific return details. Every word earns its place with no redundancy or waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no annotations, but has an output schema), the description is reasonably complete. It specifies the resource and return fields, and the output schema will handle return value details. However, it lacks context on access scope or behavioral constraints, leaving some gaps for a tool that lists resources.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 adds no parameter information, which is appropriate since there are none. Baseline is 4 for 0 parameters, as the description doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('List') and resource ('all accessible Airtable bases'), including what information is returned ('names, IDs, and permission levels'). It distinguishes from siblings like 'list_exceptions' or 'list_webhooks' by specifying the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving base metadata, but provides no explicit guidance on when to use this versus alternatives like 'describe' (which might get details for a specific base) or 'query' (which queries records within bases). No when-not-to-use or prerequisite information is included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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