Banco Digio MCP

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

Annotations indicate idempotentHint=true and destructiveHint=false; the description adds behavioral context such as the presence of a link when no args are given and the distinction between persistent and session-only login. It does not cover error handling or return format, but the key behaviors are disclosed.

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 mostly concise, front-loads the purpose, and efficiently describes two login methods. Minor redundancy ('log in in the browser, copy the access token') could be tightened.

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 is simple with one optional parameter and no output schema. The description covers the core functionality and two usage scenarios, making it adequate for an AI agent. Missing details like error responses are minor given the overall clarity.

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 0%, so the description fully compensates by explaining that 'token' is a JWT obtained from browser login, and how to use it for session-only login. This adds crucial meaning beyond the raw schema.

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

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

The description clearly states the tool's purpose: authenticating for IDE agents by logging in via browser and using an access token. It distinguishes itself from sibling tools (e.g., openfinance, marketplace) by focusing solely on authentication.

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 when-to-use guidance: recommending a permanent config-based approach over session-only token pasting. It also explains the two invocation modes (with or without token) and their outcomes.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds specific return behavior in two states, providing value beyond annotations.

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 concise with two sentences, front-loaded with the main purpose, and contains no unnecessary information.

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

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

Despite no output schema, the description fully explains the return values in key scenarios. It is complete for a simple status-checking tool with no parameters.

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 in the input schema, so schema coverage is 100%. Baseline score of 4 is appropriate as the description does not need to add parameter 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 clearly specifies the tool returns connection status and URLs, with two distinct scenarios. It distinguishes itself from sibling tools like 'authenticate' by focusing on status rather than performing authentication.

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 checking connection status and provides context on when to expect different outputs. It does not explicitly exclude other tools but the scenarios given help in decision-making.

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?

Annotations indicate non-read-only, open-world, non-idempotent, non-destructive. Description elaborates on write actions requiring permissions, invoke returning connect/checkout links, and the behavior of install vs invoke. No contradiction with annotations.

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 verbose and could be better organized (e.g., bullet points). However, it is front-loaded with critical information and every sentence adds value given the tool's complexity.

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

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

Given 13 parameters, no output schema, and multiple actions, the description covers discovery, installation, invocation, billing, and error handling. Missing details on return values are acceptable without 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?

Despite 0% schema coverage, the description provides meaningful context for most parameters: action enum values, arguments as JSON, and other key fields like mcp_id, tool_id, query. Some less common parameters (e.g., request_name, report_context) have minimal explanation but are still covered.

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 that this is the official mcp.ai marketplace for discovering and running MCPs/tools. It distinguishes itself from sibling tools by emphasizing its role as the primary entry point for finding capabilities.

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?

Explicit instructions on when to use this tool first over external registries. Provides a core flow (search → describe → invoke) and distinguishes between install (permanent) and invoke (one-off). Mentions workspace owner/admin requirement for writes.

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?

Description confirms destructive behavior (annotated as destructiveHint: true) by stating data deletion and unavailability. Adds value by mentioning the returned add_connection_url for reconnection. No contradictions with annotations.

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 concise sentences with the main action first, 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?

While the description covers the tool's effect and return value, the missing parameter definition reduces completeness. The simple one-parameter tool could benefit from specifying what 'item' represents (e.g., bank identifier).

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?

Parameter 'item' has no description in schema (0% coverage) and the description does not explain its meaning or expected format. For a tool with a single required parameter, this is a significant 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?

Clearly states the tool revokes Open Finance consent, deletes connection data, and returns a reconnection URL. Distinguishes from sibling tools like openfinance_list_connections or openfinance_force_sync.

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 vs alternatives, but the specific action of disconnecting a bank is implied by the tool name and description. Lacks explicit when-not-to-use or prerequisite info.

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 fully discloses that it forces a sync, polls up to 60s, returns final status, and handles error states like needs_action and timed_out. It also mentions that fresh data is ready when synced=true. The annotations (readOnlyHint=false, destructiveHint=false) are consistent with a non-destructive update 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 well-structured and front-loaded, but slightly lengthy. However, every sentence adds value, covering action, use case, parameters, return format, and error handling. A minor reduction for verbosity.

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 (force sync, asynchronous waiting, error states) and lack of output schema, the description provides a complete mental model: it explains the return structure (results, errors), key fields (status, executionStatus, lastUpdatedAt, synced), and how to handle errors (needs_action, timed_out). It also mentions alternatives like openfinance_get_item_status for re-checking.

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 0%, but the description explains both parameters in detail: 'items' accepts item_id, connector_id, or connector_name, and omitting it syncs all banks; 'wait' defaults to true (blocking) but can be set false for fire-and-forget. This fully compensates for the lack of 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 explicitly states the action ('forces a re-sync'), the resource ('connections'), and key behavior ('waits for it to finish'). It distinguishes from siblings like openfinance_get_item_status by noting polling behavior and providing a clear use case.

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 gives specific when-to-use guidance ('when a balance or transaction list looks stale'), explains what it does NOT do ('without disconnecting/reconnecting'), and describes the optional 'wait' parameter for fire-and-forget usage. It implicitly contrasts with check-status 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?

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses critical behavioral traits: credit accounts may return a BALANCE_FETCH_ERROR with a structured warning instead of throwing, and the response shape is detailed as `{ results: [...], errors: [{ id, status, message }] }`. This adds significant value, especially given the lack of an output schema.

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 comprises three concise sentences, each serving a clear purpose: stating the primary function, providing usage constraints and error handling, and describing the response shape. No extraneous information is present, and the key details 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?

For a simple read tool with one parameter, no output schema, and clear annotations, the description covers all essential aspects: purpose, parameter constraints, error behavior, and response format. It is sufficiently complete for an agent to invoke the tool correctly without ambiguity.

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 only defines `account_ids` as an array of strings with no descriptions (0% coverage). The description compensates by specifying the valid range (1–50) and implying that these are account IDs from the system. This adds essential meaning beyond the bare schema.

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

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

The description explicitly states the tool 'Returns real-time balance payload per account id' and specifies the API endpoint. This clearly identifies the verb (returns), resource (balance), and scope (per account id), effectively distinguishing it from sibling tools like openfinance_get_accounts_detail or openfinance_list_accounts.

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 includes practical usage constraints: 'Pass `account_ids` as an array (1–50)' and explains error behavior for credit accounts with a structured warning. While it does not explicitly compare to sibling tools, the name and context make the primary use case clear, and the added details provide valuable guidance on when to expect warnings.

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?

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by explaining the batch output shape '{ results, errors }' and that it returns extended creditData, which is beyond what annotations provide.

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 two sentences, front-loaded with purpose, includes endpoint, parameter details, and output shape. Every sentence earns its place with no waste.

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?

Despite no output schema, the description explains the output format and parameter constraints fully. For a read-only detail retrieval tool with rich annotations, this is complete.

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

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

Schema coverage is 0%, but the description compensates by specifying the parameter is an array of strings with a size constraint (1-50). This adds crucial meaning beyond the schema's minimal definition.

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 'Returns full account objects including extended creditData' per ID, with a specific verb and resource. It distinguishes from siblings like openfinance_list_accounts by indicating this is for detailed retrieval per account.

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 says to pass 'account_ids' as an array of 1-50 IDs, implying usage when detailed accounts are needed. It lacks explicit when-not or alternatives, but the context of sibling tools provides 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?

Discloses important behavioral traits beyond annotations: Pluggy does not return a paid/status field, explains the meaning of payments in Brazilian Open Finance, and warns against assuming payment status. No contradiction with annotations.

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 comprehensive and front-loaded with purpose, but it is somewhat verbose. However, every sentence adds value, so it is still well-structured.

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

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

Given no output schema, the description explains the response shape ({ results, errors }) and lists fields. It also provides essential behavioral context, making it complete for the tool's simplicity.

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 single parameter bill_ids is thoroughly explained: it is an array, and the description suggests using openfinance_list_credit_card_bills to discover ids. Schema coverage is 0%, so the description fully compensates.

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 returns bill-level detail for credit card bills by ID, explicitly lists included fields and excludes individual transactions, and distinguishes itself from sibling tools like openfinance_list_transactions.

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 explicit when-to-use (bill-level detail), when-not-to-use (individual transactions, directing to openfinance_list_transactions), and prerequisites (use openfinance_list_credit_card_bills first to discover ids). Also warns about interpreting payments.

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?

Annotations already declare readOnlyHint=true, destructiveHint=false. Description adds concrete return structure details: object with status, executionStatus, connector metadata, and the bulk return shape { count, items }. No contradictions.

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 redundancy. First sentence establishes purpose and values, second explains parameter usage. Perfectly front-loaded and 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 simple read-only tool with one optional parameter and no output schema, the description fully covers both input scenarios and expected return shapes. No gaps.

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

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

The only parameter `item` has 0% schema coverage, but the description fully explains its semantics: omitting it returns all banks, passing a value returns one bank. This compensates completely.

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

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

Description clearly states it returns bank connection status with specific enum values (UPDATED, UPDATING, LOGIN_ERROR, etc.). Distinguishes two usage modes (bulk vs single bank) which differentiates it from siblings like openfinance_list_connections.

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 instructs when to omit or pass the `item` parameter for bulk vs single bank status. While it doesn't explicitly mention alternatives, the context is clear enough for an agent to decide.

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?

Beyond annotations (readOnly, idempotent, not destructive), the description warns that the credit card balance is connector-dependent and should not be treated as the current bill. It also explains the meaning of fields like 'bank' vs 'name' and the response structure for different item usages.

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 comprehensive but could be slightly more concise. It is well-organized with clear explanations of different use cases and field meanings, but some sentences could be trimmed without losing information.

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

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

The description covers all necessary aspects: response fields, aggregation behavior, credit card balance caveats, and cross-references to a sibling tool. Given the absence of an output schema, it provides complete contextual information for an agent to use the 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?

Schema coverage is 0%, but the description explains the 'item' parameter's behavior (omit for all, pass for single) and the 'type' parameter's values (BANK and CREDIT). It adds meaning beyond the enum and type definitions.

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 that the tool returns accounts for a bank connection, listing BANK and CREDIT types with specific fields. It distinguishes between listing all accounts (omit item) and targeting a single bank (pass item), providing a specific verb and 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?

The description explicitly tells when to omit item for cross-bank listing and when to pass item for a single bank. It also directs users to openfinance_list_credit_card_bills for standardized bill amounts, providing clear alternatives.

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

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds useful context: caching for the adapter session, single aggregated response (no batch IDs), and the specific fields returned. This enriches understanding beyond annotations.

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 wasted words. All information is essential: what the tool does, caching, field details, language preference, and relationship to sibling. Front-loaded with key action verb 'Returns'.

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?

Despite no output schema, the description fully explains the return structure (id, description, descriptionTranslated, parentId, parentDescription). It also covers caching, session scope, and the singleton nature. This is complete for a taxonomy listing tool.

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

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

No parameters exist (schema coverage 100%), so baseline is 4. The description doesn't need to add parameter info, and correctly focuses on output structure.

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 returns Pluggy's transaction category taxonomy, specifies it's cached, and details the fields (id, description, descriptionTranslated, parentId, parentDescription). It explicitly links to sibling tool openfinance_update_transaction_category via the categoryId, distinguishing its purpose.

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

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

The description notes caching behavior (implying repeated calls are cheap) and recommends descriptionTranslated for pt-BR users. It doesn't explicitly state when not to use it, but the purpose is clear enough given the context of transaction categorization.

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?

Annotations already indicate readOnly, idempotent, non-destructive. Description adds that it returns fields and an add_connection_url for linking additional banks, which is useful context beyond annotations.

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

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

Single, concise sentence with verb front-loaded. 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?

Given no parameters and no output schema, the description sufficiently explains the tool's purpose and return fields. Complete for a simple list tool.

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

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

No parameters, so baseline score of 4 applies per rubric. No additional parameter info needed.

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 it returns saved bank connections and lists specific fields (connector_id, item_id, bank name, add_connection_url). Distinguishes from siblings like authenticate, connect, disconnect, 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?

No explicit guidance on when to use this vs alternatives; usage is implied by the name and description. Does not mention when not to use or specify 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?

Annotations already indicate readOnly, idempotent, non-destructive. The description adds rich behavioral details: connector asymmetry where open bill may not be available, the derived payment_status logic, that it returns a warning instead of failing if CREDIT_CARDS product is not enabled, and that include_open_bill is opt-in due to extra scan. No contradictions with annotations.

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 long but dense with essential information. It front-loads the main purpose and then details payment status, open bill, and connector asymmetry. Every sentence adds value, but the lack of clear section breaks (e.g., bullet points for different aspects) and the length could be slightly overwhelming. Still, it is appropriate for the complexity.

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

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

Given the complexity (5 parameters, no output schema, domain-specific payment semantics), the description covers all essential aspects: return fields, derived payment_status with matching logic, open bill structure, connector asymmetry, bulk support, cross-tool guidance, and warning behavior. It provides enough context for an agent to use the tool effectively without additional information.

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 has 0% description coverage, so description must compensate. It explains include_open_bill (default false, opt-in due to extra scan) and account_ids (bulk support). The required account_id is implied. However, page and page_size are not described at all, missing their purpose or defaults. While common pagination parameters are often understood, the description fails to explicitly address them, so not a perfect 5.

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 it returns CLOSED credit card bills for CREDIT-type accounts, with specific fields like dueDate, totalAmount, etc. Distinguishes from sibling tool openfinance_list_transactions for itemized purchases and openfinance_get_credit_card_bill for a single bill. The verb 'returns' with resource 'CLOSED credit card bills' is specific and unambiguous.

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

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

Explicitly tells when to use this tool: for bill-level summaries and derived payment_status; when not to use: to see itemized purchases use openfinance_list_transactions; also advises not to assume payment based on payments[] and to use include_open_bill instead of the credit account's balance. Provides extensive when-to-use and when-not-to-use 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so behavioral transparency is partially covered. The description adds significant value by detailing the error-handling behavior: returns a structured object with total, results, and warning instead of throwing on 403 or other upstream errors. This is beyond annotations and aids agent understanding.

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 efficient, front-loading the core purpose then listing return fields and error behavior in a single sentence. No redundant information; every part adds value. Well-structured for quick parsing.

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 (4 parameters, no output schema) and rich annotations (readOnlyHint, etc.), the description covers return data and error handling adequately. However, it lacks guidance on pagination (page, page_size) and the 'item' parameter (likely a connection identifier). The description is incomplete for an agent to invoke correctly without additional knowledge of the parameter semantics.

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

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

Schema description coverage is 0%, and the description does not explain any of the four parameters (item, page, type, page_size). The only hint is the list of investment types in the description, which loosely maps to the 'type' parameter's enum values. The description fails to compensate for the missing schema descriptions, leaving parameter meaning largely ambiguous.

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 returns the investment portfolio for a connection, listing specific asset types (FIIs, stocks, ETFs, etc.) and return fields. It uses a specific verb 'Returns' and distinguishes from sibling list tools by focusing on investments portfolio rather than accounts, transactions, or credit cards.

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 connections with INVESTMENTS product enabled but does not explicitly state when to use this tool versus alternatives like openfinance_list_investment_transactions. No exclusions or specific context beyond the product requirement are provided, leaving the agent to infer when it is appropriate.

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

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral context by detailing the output fields (quantity, value, netAmount, agreedRate, brokerageNumber, expenses breakdown) and bulk support. This goes beyond annotations without contradiction.

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 concise—two sentences in the first paragraph covering return details, and a second paragraph for usage. Every sentence adds value, with no redundancy. It is front-loaded with the core purpose and then provides context.

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

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

Given no output schema, the description adequately covers return fields and the prerequisite relationship with openfinance_list_investments. It mentions bulk support but lacks detail on pagination parameters (page, page_size) or what happens with invalid investment_ids. Still, it is largely complete for a read-only list tool.

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

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

With 0% schema description coverage, the description compensates by explaining that investment_id is the identifier from openfinance_list_investments and that investment_ids enables bulk execution. It does not describe page and page_size parameters, but these are common pagination parameters with implied meaning.

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 returns movement history for a specific investment position, listing transaction types (BUY/SELL/TAX/etc.). It distinguishes from sibling tool openfinance_list_investments by explicitly stating it should be used after that tool to obtain the investment_id.

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 context: 'Use after openfinance_list_investments to get the investment_id.' It also mentions bulk support with investment_ids, giving clear usage guidance. However, it does not explicitly exclude alternative tools or state when not 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?

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds that multiple connections are queried sequentially with rate-limit spacing and returns per-connection results/errors, providing useful behavior details beyond annotations.

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 concise sentences, front-loaded with the purpose. Every sentence adds value with no 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 simple input (one optional parameter) and no output schema, the description explains input, behavior, and output format sufficiently. Annotations cover safety. It is complete for the tool's 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?

Schema description coverage is 0%, but the description fully explains the `items` parameter: it is an array of connection selectors (item_id, connector_id, or connector_name) and that omitting it lists all banks. This adds complete meaning beyond the bare schema.

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

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

The description clearly states the tool lists loan contracts per bank connection, using a specific verb ('lists') and resource. It distinguishes from sibling tools like openfinance_list_accounts by focusing solely on loans.

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 explains how to use the tool: provide `items` for specific connections or omit for all. It mentions sequential querying with rate-limit spacing, but does not explicitly compare to alternatives or state when not to use it.

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

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

Beyond annotations (readOnlyHint, idempotentHint), the description adds critical behavioral traits: auto-pagination with 5000 ceiling and truncation warning, upstream-dependent CREDIT PENDING/POSTED behavior, error return format instead of throwing, and per-bank coverage variation. No contradictions with annotations.

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 long but well-structured with logical paragraphs (CREDIT specifics, pagination, detail, troubleshooting). Every sentence provides unique value, though some redundancy in explaining auto-pagination could be trimmed. Appropriate for the complexity.

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

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

Given the tool's complexity (8 params, no output schema), the description is remarkably complete. It covers all parameters, edge cases, behavioral differences per bank, troubleshooting, and references sibling tools. No gaps remain for typical use cases.

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?

Despite 0% schema description coverage, the description explains all 8 parameters in detail: date formats, search_queries semantics (case-insensitive OR substring match), pagination parameters, detail levels with what each includes, and bulk support via account_ids. Fully compensates for schema gaps.

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

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

The description clearly states it returns transactions for BANK or CREDIT accounts, and distinguishes itself as the ONLY way to get itemized credit card transactions. It contrasts with openfinance_list_credit_card_bills for bill totals, providing specific verb and resource with clear differentiation from siblings.

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?

Extensive guidance on when to use this tool vs alternatives (e.g., for CREDIT itemized transactions vs bills). It explains auto-pagination behavior, detail levels, error handling, and even troubleshooting steps for zero totals. Clearly states when to use default page vs manual pagination.

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?

Annotations indicate readOnlyHint, idempotentHint, destructiveHint but description adds important behavior: scan caps at 5000/account with truncated flag, and default granularity returns compact summary. No contradiction.

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?

Description is verbose but informative. It front-loads the main purpose but could be broken into bullet points for clarity. Every sentence adds value, but structure could be improved.

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?

With 7 parameters and no output schema, the description explains return values (compact summary fields including top_despesas/recebimentos, by_account) and caps conditions. Covers use cases adequately.

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 0%, so description must compensate. It explains all parameters: item (connector_id/name/item_id), from/to (ISO dates), granularity (monthly/raw), detail (compact/rich/raw), type (BANK/CREDIT). Top_n is implied but not explicitly linked; still adds significant meaning.

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 provides 'consolidated cash-flow analysis for a whole bank connection' in one call, resolving accounts internally. It distinguishes itself from siblings like openfinance_list_transactions by offering aggregated analysis.

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 says when to use (análise anual/mensal, fluxo de caixa, etc.), when not to use other tools (no need to call openfinance_list_accounts first), and how to set parameters like granularity and detail. Also explains omitting item for all banks.

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?

Discloses that the tool reads a public status page (non-destructive, idempotent) and lists return fields: global indicator, degraded components, open incidents, and flagging affected banks. No contradictions with annotations.

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 with purpose. Efficient but could be slightly more concise; still 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 no parameters and no output schema, the description fully covers what the tool does, when to use it, and what it returns (global indicator, components, incidents, affected banks). Complete for a zero-parameter tool.

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

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

No parameters exist, so baseline 4 applies. The description compensates by explaining the tool's input-less nature and what it returns.

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 checks the LIVE operational status of the Open Finance provider via its public status page. It differentiates from the sibling tool 'openfinance_get_item_status' by focusing on provider-side health versus connection status.

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: when data is incomplete or stale even though a connection shows updated, and helps differentiate provider-side problems from connection issues. Provides actionable context.

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

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

Discloses that it honors the user's plan (PF hides PJ), surfaces caveats for credential connectors, and never dumps the full catalog without keywords. Adds context beyond readOnlyHint and idempotentHint annotations without contradiction.

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?

Five sentences, each adding value. Could be slightly tighter but is well-structured with key information front-loaded. No 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?

No output schema, but description thoroughly explains return values (connector id, access, audience, connections, accounts conditionally, connect_url, caveat) and edge cases (missing keywords, plan restrictions). Sufficient for an AI agent.

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

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

With schema description coverage at 0%, the description compensates by explaining keywords[] as required search terms and include_accounts for returning accounts. Lacks default values but provides sufficient meaning for correct invocation.

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 it searches bank connectors by name, returns connector details including id, access type, audience, linked connections, and connect_url. Distinguishes from siblings by positioning as a pre-connection step.

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 instructs to call this before connecting, mentions that keywords[] is required, and advises preferring Open Finance connectors due to caveats. Provides clear when-to-use and when-not-to-use 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?

Discloses key behavioral traits: recategorizing creates a Category Rule that affects future similar transactions (case-insensitive exact match). Describes batch response shape with { updated, results, errors } and per-item error handling. Adds significant context beyond annotations, which only indicate non-read-only, non-destructive, non-idempotent.

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

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

Single paragraph that front-loads the purpose. Contains multiple key pieces of information (param structure, side effect, batch response) without excessive verbosity. Could be slightly more structured (e.g., separate sentences), but overall efficient.

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?

Covers all necessary aspects for correct usage: purpose, parameter explanation, behavioral side effects, batch response shape. No output schema exists, but the description compensates by detailing the response. An agent can confidently invoke this tool based on the description.

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

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

Schema has 0% description coverage, but the description fully explains the items parameter structure (array of objects with transaction_id and category_id). Explains that transaction_id comes from openfinance_list_transactions and category_id from openfinance_list_categories, adding meaning 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?

Clearly states the tool corrects the category of one or more transactions. Explicitly mentions the HTTP method (PATCH) and endpoint. Distinguishes from sibling tools like openfinance_list_transactions and openfinance_list_categories by specifying where the IDs come from.

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 instructions on how to use it (pass items as an array of objects with transaction_id and category_id). Explains the effect: overrides automatic categorization and creates a Category Rule for future transactions. States it should be used to fix miscategorized transactions. Lacks explicit when-not-to-use or alternatives, but the context is sufficient.

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?

Annotations indicate idempotentHint=true and destructiveHint=false, so the description's mention of 'report' implies a safe write operation. The description does not add further behavioral detail beyond what annotations provide, but there is no contradiction. Adequate, but could elaborate on outcome (e.g., ticket creation).

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 two sentences, front-loading the purpose and providing a key usage instruction. Every sentence adds value with no 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?

With no output schema and 0% schema description coverage, the description is minimal. It does not cover return behavior, authentication, or what happens after reporting. For a feedback tool, this lacks necessary context for an agent to understand the full impact.

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

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

Schema description coverage is 0%, meaning none of the 3 parameters have descriptions. The description only mentions 'conversation array' but does not explain the 'context' or 'message' fields or their formats. The description fails to compensate for the lack of 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's purpose: report a bug, missing feature, or send feedback. It uses specific verbs and resources. Among siblings focused on finance and authentication, this tool's purpose 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 provides a clear context for use (bug/feature/feedback) and a specific instruction to include the conversation array for reproduction. However, it does not explicitly state when not to use or compare to alternatives, though siblings are unrelated.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that the output is version info, but no further behavioral traits beyond what annotations cover. Does not contradict annotations.

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

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

Single sentence, no wasted words. Front-loaded with the action and resource. Perfectly concise for the tool's simplicity.

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?

Low complexity, empty schema, annotations cover safety. No output schema, but description adequately states what is returned. A bit sparse on return format, but acceptable given simplicity.

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 (schema coverage 100% empty). Description doesn't need to add parameter info. 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 shows 'MCP platform and adapter versions'. The verb 'Show' and resource 'versions' are specific. This distinguishes it from sibling tools which are finance-related or authentication.

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 alternatives or when-not-to-use guidance, but the tool's purpose is self-evident. In context of siblings, it's the only version tool, so usage is clear. Lacks exclusion criteria.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds specific behavioral context about what data is returned (installed MCPs, connection status, catalog counts), beyond the annotations.

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 sentence that front-loads the purpose and key output details. Every part is informative and there is no waste.

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, the description fully explains what is returned (installed MCPs, connection status, catalog counts). For an info tool with zero parameters and rich annotations, this is complete.

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

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

The tool has zero parameters and schema coverage is 100%. With no parameters, the description doesn't need to add parameter semantics. 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 the tool returns current toolkit state including installed MCPs, their connection status, and catalog tool counts. It uses a specific verb ('Returns') and distinguishes itself from sibling tools like 'show_version'.

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 it is for getting an overview of the toolkit state, but does not explicitly state when to use it versus alternatives. No exclusions or when-not-to-use guidance is provided.

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