tmpstate

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

With no annotations, the description carries the full burden. It discloses key aspects: 24h TTL, no signup/keys, return values (db URL, admin URL, limits, expiry), and advice to persist URL. No contradictions. Could mention if database can be deleted, but creation is non-destructive.

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?

Three sentences, each adding value: core definition, return information, and usage advice. No wasted words, front-loaded with 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 no parameters and no output schema, the description covers creation, return values, and persistence advice. Could mention how to use the URL for subsequent operations, but adequate overall.

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?

No parameters exist, and schema coverage is 100%. The description adds context about what the tool produces without needing parameter details. Baseline for 0 params is 4.

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 it creates a temporary JSON database with specified constraints (24h TTL, no signup, no keys). It distinguishes from sibling tools like pro_create_database (paid) and extend_database (extends lifetime).

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?

Implied usage for temporary database needs, but lacks explicit when-to-use vs alternatives. For example, it does not mention that for persistent databases or extended TTL, one should use pro_create_database or extend_database.

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?

Without annotations, the description carries the full burden. It discloses quota counting but omits behavioral traits like permission requirements, atomicity, id generation, or error handling. More transparency is needed for a write 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, efficient sentence with a parenthetical. It is front-loaded with the primary action and is appropriately sized.

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

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

Given the complexity (3 required params, nested objects, no output schema), the description is minimal. It fails to mention response structure, error conditions, or how to use the db parameter appropriately, leaving significant gaps for an agent.

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

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

Schema coverage is 67% (db and data described, collection missing). The description adds no meaningful parameter details beyond the schema—'Insert a JSON object' is vague for the data parameter, and the db parameter's URL format is not clarified. The undocumented collection parameter remains unaddressed.

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 'Insert a JSON object into a collection' with a specific verb and resource. It clarifies that collections are created implicitly, distinguishing it from sibling tools like create_database or delete_document.

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 mentions quota implications ('Counts against the write and document quotas') but does not explicitly state when to use this tool versus alternatives like update_document. Usage context is implied but lacks explicit guidance.

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

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

No annotations exist, so description carries full burden. It states it's a read operation equivalent to GET $DB/__meta, but lacks details on error conditions, authorization requirements, or response format. Adequate but minimal.

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, concise sentence that front-loads the key concepts (usage, limits, tier, expiry) and references the equivalent endpoint. No unnecessary words.

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 simple tool with one parameter and no output schema, the description adequately conveys the purpose and key outputs. However, it could be improved by describing the return format or structure, which is especially important given no output schema.

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% for the single parameter 'db', which is described as 'The database URL returned at creation (or its bare s-... capability)'. The description does not add additional meaning beyond the schema, so baseline 3 applies.

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 retrieves usage, limits, tier, and expiry for a database, specifying it as equivalent to a GET endpoint. It distinguishes from sibling tools like create_database or get_document by focusing on database metadata.

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

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

No explicit guidance on when to use this tool versus alternatives like get_document or list_documents. The description implies it's for database-level status, but does not specify exclusions or prerequisites.

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

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

The description highlights 'Irreversible' as a key behavioral trait, which is critical for a deletion tool. However, with no annotations, it lacks details on permissions, authentication, side effects, 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?

One concise sentence with no wasteful words. The important points (action, scope, re-seed use case, irreversibility) are front-loaded.

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 output schema and no annotations, the description is minimal. It lacks explanation of return values, error conditions, prerequisites (e.g., database existence), and confirmation behavior.

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 50% (only 'db' has a description). The description adds no extra meaning for the 'collection' parameter (no description) and does not clarify parameters beyond 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 'Delete every document in a collection at once', specifying the verb (Delete) and resource (every document in a collection). It distinguishes from sibling tool 'delete_document' by targeting all documents at once, and adds context 'useful to re-seed'.

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 re-seeding, but does not explicitly state when not to use or directly compare with alternatives like delete_document. However, the sibling tool names provide implicit differentiation.

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

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

No annotations are provided, so the description must cover behavioral traits. It adds one useful fact ('Never blocked by quotas; frees a document slot'), but it omits other important details like irreversibility, authentication requirements, or what happens to associated 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 extremely concise (two sentences, 14 words) and front-loaded with the main action. No unnecessary words or redundancy.

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

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

The tool has no output schema and limited parameter info. The description does not explain return values, error cases (e.g., document not found), or side effects beyond quota slot freeing. It is minimally adequate for a simple delete but lacks completeness.

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

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

Schema description coverage is only 33% (only 'db' has a description). The description does not elaborate on any parameter beyond what is already in the schema. For instance, 'id' and 'collection' remain undocumented.

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 'Delete one document,' which is a specific verb-resource pair. It distinguishes from sibling tools like delete_collection and create_document.

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 given on when to use this tool versus alternatives. There is no mention of prerequisites, such as ensuring the document exists or user permissions, nor any comparison with update_document or other related tools.

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

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

No annotations exist, so description carries full burden. It discloses return types (pricing table or checkout URL) and behavior on frozen databases. Lacks details on potential side effects, but sufficient for a payment-related tool.

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

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

Three sentences, front-loaded, no filler. Each sentence adds value: first explains base behavior, second gives usage rule, third covers edge case.

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?

No output schema, but description explains return types. Covers all key cases (with/without plan, expired). Does not mention errors or authentication, but acceptable for this scope.

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 coverage is 50% (db described, plan only enum). Description adds meaning for 'plan' by explaining the two scenarios. For 'db', repeats schema info but sufficient. Compensates for missing schema descriptions.

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

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

The description clearly states the tool extends database lifespan, distinct from siblings like create_database or pro_* tools. It specifies two modes (pricing table vs. checkout URL) and handles expired databases.

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?

Explicitly describes when to use each mode (without plan vs. with plan) and warns against unauthorized purchases. Also notes applicability to expired databases, distinguishing it from other 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, the description provides basic behavior: it reads a document by ID and notes the return structure (.data). It lacks details on error handling (e.g., missing ID), authentication, or idempotency, but for a read operation it is minimally adequate.

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

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

Two sentences with no wasted words. The first sentence states the core purpose, and the second adds an important structural detail. Excellent front-loading and brevity.

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?

The description covers the essential purpose and return structure, but lacks details on error scenarios, parameter constraints, or differentiation from list_documents. Given no output schema and 3 parameters, it is adequate but not thorough.

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% (db and id have descriptions, collection does not). The tool description does not elaborate on any parameter meaning beyond the schema, failing to compensate for the missing collection description.

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 reads one document by ID, with a specific verb ('Read') and resource ('document'). It adds the detail that stored fields are under '.data', which differentiates it from sibling tools like update_document or list_documents, though not explicitly.

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

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

No explicit guidance on when to use this tool versus alternatives. The description does not mention prerequisites, conditions, or when not to use it. Sibling tools like list_documents or create_document are not referenced.

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 provided; description carries full burden. Discloses response shape and paging behavior (documents under .data, cursor-based pagination). Could improve by stating idempotency or read-only nature explicitly.

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

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

Two sentences, no fluff. Every sentence adds value: listing purpose, ordering, response shape, and paging instructions.

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?

No output schema, so description explains return values thoroughly (collection, items fields, next_cursor). Covers paging usage. Lacks mention of error cases or collection existence check, but adequate given 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?

Adds meaning beyond schema by describing response shape and explaining how to use cursor. Ordering 'oldest first' is not in schema. Schema coverage is 75%, and description compensates well.

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?

Clearly states verb 'list' and resource 'documents in a collection', with ordering 'oldest first'. Distinguishes from sibling tools like get_document, delete_document, etc.

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?

Implies usage by mentioning required parameters (db, collection) and paging, but lacks explicit guidance on when to use this tool over alternatives like get_document or create_document.

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

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

No annotations are provided, so the description carries full burden. It discloses key behavioral changes (TTL removed, quotas raised, overage consent) but does not mention error cases, prerequisites, or post-conditions like whether the operation is reversible or what happens if the database is already Pro.

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

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

Two sentences with zero waste. The first sentence front-loads purpose and effects; the second adds a necessary behavioral note. Every sentence earns its place.

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 three parameters, no output schema, and no annotations, the description explains core functionality and key effects but lacks details on error handling, return values, prerequisite database state, and the exact behavior of the 'accept_overage_usd' parameter.

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 coverage is 67% (2 out of 3 parameters described). The description adds context for overage consent but does not explicitly explain the 'accept_overage_usd' parameter format or relationship. The parameter semantics are partially enhanced but not fully.

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 'Attach' and the resource 'existing free/extended database' with key effects (same URL, same data, TTL removed, quotas raised). It distinguishes from siblings like pro_create_database and extend_database via naming and context.

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

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

The description implies when to use (upgrade existing free/extended to Pro) and references pro_create_database for overage consent, but does not explicitly state when not to use or compare to alternative tools like pro_create_database or extend_database.

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?

Even without annotations, the description fully discloses that cancellation schedules deletion of all databases and requires a confirmation step. It mentions the response includes concrete dates, increasing 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?

Two sentences, front-loaded with the main action, each sentence essential. No wasted words.

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

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

For a destructive action with a two-step process, the description covers consequences, response format, and user confirmation requirement. No gaps given the lack of output schema.

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 coverage is 100%, and the description adds context for the confirm parameter (pass only after approval) but does not significantly extend beyond the schema's own 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 cancels the Pro subscription at period end and schedules deletion of all databases. It uses specific verbs and distinguishes from siblings by emphasizing the destructive consequence.

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 two-step usage: call without confirm first, show consequences, then retry with confirm only after user approval. However, it does not name an alternative tool for non-destructive actions.

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 fully carries the burden. It discloses key behaviors: immediate persistence of the pro_token, the human payment flow in a browser, cost, and included databases. This goes well beyond minimal expectations.

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

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

Two sentences with zero wasted words. The first sentence front-loads the core purpose and key details; the second adds a critical usage constraint. Perfectly concise.

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

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

For a zero-parameter tool with no output schema and no annotations, the description covers all essential information: action, cost, resources, persistence behavior, and usage constraint. It is fully adequate.

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 zero properties, so schema description coverage is 100%. The description adds no parameter details because there are none, but it doesn't need to. Baseline 4 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 it mints a Pro account token and Stripe subscription checkout URL, specifying cost ($8/mo) and included resources (3 always-on databases). It uses specific verbs (mint, persist) and clearly distinguishes from sibling tools like pro_cancel or pro_attach_database.

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 warns 'Never start checkout without the user's explicit request,' providing a strong usage guideline. It does not explicitly list alternatives, but the constraint itself offers clear direction for when to use this tool.

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

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

Despite no annotations, description fully discloses expected behavior: cost implications, return of confirmation_required with exact price, and need for explicit user consent.

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

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

Two tightly written sentences that convey all necessary information without redundancy; front-loaded with 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?

Completely covers the tool's behavior for a billing-gated creation tool: cost implications, required user interaction, and parameter usage flow.

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?

Adds critical context beyond the schema definitions, explaining the intended workflow for accept_overage_usd (only used after user approval) and optional nature of pro_token.

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?

Explicitly states it creates a new always-on database owned by the Pro account, clearly distinguishing it from the sibling create_database tool.

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

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

Provides clear when-to-use guidance, including the billing flow: relays price to user, gets approval, then retries with accept_overage_usd parameter.

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 adds value by disclosing that URLs are never stored server-side and that the agent must match ids to persisted URLs. It also lists returned fields. However, it doesn't discuss rate limits, idempotency, or other behavioral traits.

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

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

Two concise sentences with no wasted words. Front-loaded with the main purpose, then adds critical context about URL storage.

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 simple listing tool with no output schema, the description adequately covers what is returned (ids, usage, limits, expiry) and the reconciliation purpose. Could mention if results are paginated or ordered, but not essential.

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 coverage is 100% with one parameter (pro_token). The schema already explains its format and optionality. The description adds no additional parameter semantics beyond what the schema provides.

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 it lists Pro account databases with specific fields (ids, usage, limits, expiry). It provides a specific use case (reconcile persisted db URLs). However, it does not explicitly differentiate from sibling list tools like list_documents, though the resource (databases) is distinct.

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

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

The description implies usage for fresh sessions to reconcile URLs but doesn't give explicit when-to-use or when-not-to-use guidance, nor does it reference alternatives like database_status or pro_create_database.

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 discloses the merge behavior (shallow, overwrite, no deletion) and quota impact. However, it does not specify behavior if document is missing, whether the operation is idempotent, or any error conditions. Still, it provides substantial transparency beyond the baseline.

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

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

Two sentences, front-loaded with key behavior, no unnecessary words.

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 required parameters and no output schema, the description covers merge semantics and quota but omits usage context, error handling, and parameter details. Given sibling diversity, more guidance on when to use this tool would improve completeness.

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

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

Schema coverage is 50%, with only two of four parameters having descriptions in the schema. The tool description does not add any additional parameter-level information, leaving 'id' and 'collection' unexplained. Description should compensate but doesn't.

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?

Description clearly states the tool shallow-merges a patch into a document, specifying that top-level keys overwrite and keys are never deleted. This distinguishes it from create, delete, and read operations among sibling tools.

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

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

The description does not explicitly state when to use update_document versus alternatives like create_document or delete_document. While the merge semantics imply usage for updates, there is no direct guidance on prerequisites or when not to use it, making it moderately clear.

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