Caixa Tem MCP

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

The description reveals behavioral traits beyond annotations: the token can be permanent (via config) or session-only (passed as argument), and calling with no args returns a link. This adds context about idempotency and non-destructiveness, consistent 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 relatively long but well-structured: it starts with the primary use case, then details options. Every sentence adds value, though minor redundancy could be trimmed. Front-loaded with key info.

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

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

For a tool with one optional parameter and no output schema, the description is complete. It covers the authentication flow, permanence options, and link retrieval, requiring no further clarification.

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

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

With 0% schema description coverage, the description fully compensates by explaining the token parameter: it is a JWT for session login, optional, and when omitted the tool returns a login link. This adds critical 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?

The description clearly states the tool's purpose: authentication for MCP.AI IDE agents. It specifies the resource (access token) and the action (logging in), and distinguishes from siblings like 'connect' by detailing a specific authentication flow.

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

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

The description provides explicit guidance on when to use each option: adding token to config for permanent connection, pasting token for session login, or calling with no args to get a login link. It clearly outlines the best practice and 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?

The description adds specific behavioral details beyond annotations (readOnlyHint, idempotentHint, destructiveHint) by describing response content in different states. 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 concise with two sentences, each providing essential information without redundancy or fluff.

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

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

The description fully explains the tool's purpose and output format, covering both connected and missing credentials cases. No output schema exists, so the description adequately informs the 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?

There are no parameters, so schema coverage is trivially 100%. The description does not need to add parameter information, and it does not attempt to do so.

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 connection status and URLs, with specific examples of different states. It distinguishes from sibling tools like 'authenticate' or 'openfinance_list_connections' by focusing on overall connectivity.

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 when to use the tool (to check connection status) and what output to expect in different scenarios. It does not explicitly mention when not to use it or provide alternative tools, but the context is clear.

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?

Disclosures write operations require owner/admin, explains return of connect/checkout links for auth/payment, and clarifies that invoke runs tools without installing. Consistent with annotations, adds substantial behavioral context.

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

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

The description is verbose (over 200 words) and contains long, run-on sentences. While it front-loads the purpose, the structure could be more compact and use bullet points for clarity.

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 (multi-action, many parameters, no output schema), the description covers the core workflow, edge cases (credentials, payments), and permissions requirements. It feels comprehensive for an agent to use correctly.

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

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

With 0% schema coverage, the description compensates by explaining the main 'action' parameter and its values, plus related parameters like mcp_id, tool_id, arguments, immediate. However, it does not detail all 13 parameters; some (e.g., limit, query, tier_slug) are only briefly mentioned.

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 is the official mcp.ai marketplace and serves as the entry point for finding and running MCPs. It distinguishes itself from siblings by being the primary tool to use before external registries.

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 'use THIS tool FIRST' and contrasts with install (permanent) vs invoke (one-off). Provides clear context for when to use marketplace vs other tools like list_tools, subscribe, etc.

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 destructiveHint=true, and the description confirms the data is deleted. No additional behavioral context (e.g., permissions, irreversibility) is added 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 concise sentences, front-loaded with the action and consequence. 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 simple destructive tool with one parameter, the description covers the key effects and return value. Lacks detail on parameter semantics but is otherwise sufficient.

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 'item' is not described in the schema (0% coverage) and the tool description does not clarify what 'item' refers to (e.g., bank ID, connection ID). This leaves ambiguity.

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

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

The description clearly states the action: revokes consent and deletes connection data for a specific bank. It 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?

The description implies when to use (to disconnect a bank) but provides no explicit guidance on when not to use or alternatives. It mentions a re-connect URL but doesn't clarify scenarios.

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 lack detail (readOnlyHint=false, destructiveHint=false). The description compensates fully by detailing the sync process, polling up to ~60s, return fields (status, executionStatus, lastUpdatedAt, synced), and error conditions (needs_action, timed_out). 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?

The description is thorough and front-loaded with key behavior. Slightly verbose but every sentence adds value; no redundancy. A minor reduction in length could improve conciseness.

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 return structure ({ results, errors }) and key fields. It covers edge cases like needs_action and timed_out. For a moderately complex tool with polling, 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%, so the description must explain all parameters. It does: 'wait' (boolean, false for fire-and-forget) and 'items' (array of selectors like item_id, connector_id, or connector_name; omitting syncs all). This provides complete semantic context 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 the tool forces a bank to re-sync connections and waits for completion. It distinguishes itself from sibling tools like openfinance_get_item_status by specifying polling behavior and from disconnect/reconnect operations.

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

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

The description explicitly states when to use (stale balance/transaction list) and what not to do (no disconnect/reconnect). It provides alternatives: re-check with openfinance_get_item_status if timed out, and explains the wait parameter for fire-and-forget usage.

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

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds critical behavioral context: CREDIT accounts may return a Pluggy BALANCE_FETCH_ERROR with a structured warning instead of throwing, and the response shape is provided. This is comprehensive.

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 essential information. No fluff, 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 a single parameter, no output schema, and strong annotations, the description fully covers purpose, input constraints, error handling, and return shape. 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?

While schema description coverage is 0%, the description compensates by explaining the parameter 'account_ids' is an array of 1-50 account IDs. This adds meaning beyond the schema, though it could more explicitly validate the IDs format.

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 'Returns', the resource 'real-time balance payload per account id', and includes the endpoint path. It distinguishes from siblings like openfinance_list_accounts which list accounts rather than return balances.

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 practical guidance on input format (array of 1-50 account IDs) but does not explicitly mention when to use this tool versus alternatives like openfinance_get_accounts_detail or openfinance_list_accounts. No explicit when-not-to-use or comparison.

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 mark it as read-only and idempotent, and the description adds the batch response shape (`{ results, errors }`) and the extended creditData detail, going beyond the annotations' safety profile.

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 with no wasted words, front-loading the purpose and endpoint, then parameter and response shape.

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, the description adequately documents the return format (`{ results, errors }`), the parameter details, and the endpoint. All essential information for a single-parameter read tool is present.

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 the array size constraint (1–50) and the purpose of the single parameter, adding meaningful context that the schema lacks.

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 full account objects with extended creditData per ID, references the endpoint, and distinguishes from sibling tools by specifying 'full account objects' versus likely list-only variants.

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?

It explicitly requires passing `account_ids` as an array (1–50), implying batch usage. While it doesn't explicitly state when not to use or list alternatives, the sibling tool names like `openfinance_list_accounts` provide contextual 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?

Annotations indicate read-only, idempotent, non-destructive. Description adds batch return shape, clarifies that payments[] likely reference previous bill, notes missing paid status field. Exceeds annotation coverage.

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

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

Description is informative but slightly long (5 sentences). Every sentence adds value; however, it could be more compact. Structure is logical, with clear purpose upfront.

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 bears full burden. It specifies return fields, batch structure, and critical behavioral caveats about payments and paid status. Covers all needed context for correct usage.

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?

Single parameter bill_ids has 0% schema coverage, but description explains it's an array, how to get ids (via list tool), and batch shape. Fully 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?

Description explicitly states it returns bill-level detail by id, specifies included fields (financeCharges, payments) and explicitly excludes individual transactions. Differentiates from sibling tools like openfinance_list_credit_card_bills (discovery) and openfinance_list_transactions (itemized).

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: use openfinance_list_credit_card_bills first to find ids, use openfinance_list_transactions for itemized transactions. Explains tricky payment semantics and suggests alternative for paid status. No guidance missing.

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 mark the tool as read-only and idempotent. The description adds context about the return format (count/items vs. single status) and metadata, which goes beyond annotations without contradicting them.

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 packed with information, no redundancy. The purpose is front-loaded, and the usage variations are succinctly described.

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 one-parameter schema and rich annotations, the description covers the main behavior. It could detail the status object fields, but it is sufficient for an AI agent to understand and invoke correctly.

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

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

With 0% schema coverage, the description compensates by explaining the effect of omitting vs. providing `item`. It does not describe the parameter type or format, but the functional meaning is clear.

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 current status of a bank connection with specific status values. It distinguishes between two modes: omitting `item` for all banks and passing `item` for a single bank, which differentiates it from 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 explicitly tells when to omit vs. pass the `item` parameter, covering both use cases. It does not mention when not to use it or suggest alternatives, but the guidance is clear and actionable.

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 adds significant context beyond the annotations (readOnlyHint, idempotentHint, destructiveHint false). It explains the behavior of the 'item' parameter, the meaning of fields like 'bank' and 'name', and cautions about connector-dependent balance interpretation. 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 well-structured with clear sections. It is front-loaded with the main purpose and uses bullet points to list return fields. Every sentence adds value, making it appropriately sized 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 (multiple account types, nested data, connector-dependent values, and no output schema), the description is thorough. It covers return fields, parameter behavior, and important caveats, ensuring the agent can 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?

The input schema has two parameters (item, type) with 0% schema description coverage. The description effectively explains the 'item' parameter (omit for all banks, pass for single) and implies filtering by 'type' through the return types (BANK/CREDIT). However, the 'type' parameter is not explicitly described in terms of its usage.

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 accounts for a bank connection, including BANK and CREDIT types with specific fields like balance, number, type, subtype, bankData, and creditData. It also distinguishes from siblings by directing users to openfinance_list_credit_card_bills for standardized bill amounts.

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

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

The description provides explicit guidance: omit 'item' to list accounts across all linked banks, pass 'item' for a single bank. It also warns that CREDIT balance is connector-dependent and advises using openfinance_list_credit_card_bills for standardized amounts, clearly indicating when to use 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, destructiveHint, and idempotentHint. The description adds valuable behavioral context: the tool returns cached data and describes the response structure, going 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 two sentences with no wasted words. It front-loads the main purpose and provides essential details without redundancy.

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

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

For a simple, parameterless tool with no output schema, the description fully explains the cache behavior, response fields, and tie-in to another tool. No gaps remain.

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?

There are no parameters (schema coverage 100%). The description adds no parameter information, but this is acceptable as baseline for 0-parameter tools 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 the tool returns Pluggy's transaction category taxonomy, specifying the endpoint and key fields. It distinguishes itself from sibling list tools by focusing on categories rather than transactions or 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 mentions caching and the use of category IDs by openfinance_update_transaction_category, which provides context. However, it does not explicitly state when to use this tool versus alternatives or 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?

Annotations already indicate read-only, idempotent, non-destructive. Description adds value by detailing returned fields and the add_connection_url. 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?

Single sentence that is concise and front-loaded with the core action. Every word 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?

For a no-parameter tool with no output schema, the description adequately lists returned fields. Could imply it returns a list, but overall sufficient.

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 schema coverage is 100%. Baseline of 4 applies; description adds no param info but none 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 explicitly states it returns saved bank connections with specific fields (connector_id, item_id, bank name, add_connection_url). Clearly distinguishes from sibling list tools like 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?

No explicit guidance on when to use vs alternatives, but the description implies its purpose among other list 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?

Extensive disclosure of derived fields, payment logic, connector-specific behavior, and warning conditions, all beyond the readOnlyHint and idempotentHint 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?

Dense with valuable information but lengthy; could benefit from structured formatting, though justified by 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?

Covers all essential aspects: fields, payment interpretation, connector limits, bulk support, and references to related tools, leaving no key 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?

Schema has 0% coverage; description explains include_open_bill and account_ids but omits details on page and page_size, leaving some 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?

Description clearly states it returns closed credit card bills, lists fields, and distinguishes from sibling tools like openfinance_list_transactions and openfinance_get_credit_card_bill.

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, including opt-in for open bill, interpreting payment_status, connector asymmetry, and when to use openfinance_list_transactions for itemized data.

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, idempotentHint, and destructiveHint. The description adds value by detailing error behavior (returns {total:0, results:[], warning} instead of throwing) and the structure of the response (fields like balance, amount, etc.), but does not mention pagination or rate limits.

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 dense paragraph that front-loads the core purpose and includes key details. It could be more structured (e.g., bullet points for parameters), but it is concise and informative without 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 output schema and 4 parameters, the description covers the response structure and error handling but fails to explain the input parameters, making it incomplete for an agent to fully understand how to invoke the tool correctly (e.g., pagination, filtering).

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%. The description does not explain the parameters item, page, type, and page_size. While it lists investment types in the response context, it does not clarify that 'type' is a filter parameter or explain pagination, leaving the agent to rely solely on 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 that the tool returns the investment portfolio for a connection with the INVESTMENTS product enabled, listing specific asset types (FIIs, stocks, ETFs, etc.) and fields. It effectively distinguishes the tool from siblings by focusing on the full portfolio rather than transactions or 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?

It specifies the prerequisite of having the INVESTMENTS product enabled and describes graceful error handling (returns empty result on 403). However, it does not explicitly compare to related tools like openfinance_list_investment_transactions or explain when to use this over others.

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, idempotentHint=true. The description adds value by detailing the returned data fields (quantity, value, expenses breakdown) and transaction types, going beyond annotations without contradicting them.

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 efficient sentences with no filler. Purpose is front-loaded, and each sentence adds value (return data, prerequisite, bulk support).

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 list tool with 4 parameters and no output schema, the description covers core purpose, prerequisite, and bulk option but lacks pagination details and explicit output structure beyond field listing. Adequate but not fully 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%, so description must compensate. It mentions investment_id implicitly and investment_ids for bulk, but does not explain page or page_size parameters, leaving them underspecified. Parameter names are somewhat self-explanatory, but explicit guidance is missing.

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 returns movement history for investment positions, listing specific transaction types (BUY, SELL, TAX, etc.) and fields. Distinguishes itself from sibling tools like openfinance_list_investments by specifying the prerequisite and from openfinance_list_transactions by focusing on investment-specific 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?

Explicitly instructs to use after openfinance_list_investments to obtain investment_id, and mentions bulk support with investment_ids for batched execution. Provides clear usage flow, though does not explicitly state when not to use or compare to all 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?

The description adds significant behavioral context beyond annotations: sequential querying with rate-limit spacing, return structure `{ results, errors }` per connection. Annotations already flagged read-only, idempotent, non-destructive, and the description does not contradict them.

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: the first states purpose, the second covers usage and behavior. Every sentence earns its place, and the key info is 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, the description mentions the return structure. It covers the main parameter thoroughly. Could elaborate on error handling or pagination, but it is sufficient 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?

With 0% schema description coverage, the description fully explains the `items` parameter: it accepts connection selectors (item_id uuid, connector_id, or connector_name) and its effect on the query. This adds crucial 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 verb 'lists' and the resource 'loan contracts per bank connection', including the API endpoint. It distinguishes from siblings by specifying that it deals with loans, a unique resource among the list 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 provides explicit guidance: pass `items` for specific connections or omit for all banks. It does not, however, mention when not to use this tool or provide alternatives, but the context is clear for agents.

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?

Adds significant context beyond annotations: explains pending/posted variability per connector, aggregation behavior with search_queries, error handling returning {total:0, results:[], warning, error}, and guidance on connection health. 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?

Well-structured and front-loaded, but somewhat verbose; could be slightly more concise while retaining all necessary 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?

Comprehensive for a complex tool with no output schema: covers purpose, usage, behavioral details, parameter semantics, error handling, and relationships with sibling tools. Minor gap: output format not detailed, but overall 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?

With 0% schema coverage, the description fully compensates by explaining all 7 parameters: account_id/account_ids (bulk support), from/to (ISO YYYY-MM-DD), page/page_size (max 500), search_queries (case- and accent-insensitive substring match, OR semantics, aggregation up to 5000).

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 transactions for BANK or CREDIT accounts, distinguishes from siblings like openfinance_list_credit_card_bills by noting that for CREDIT accounts it is the only way to get itemized transactions and links to bills via creditCardMetadata.billId.

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 provides when-to-use (CREDIT accounts for itemized transactions), when-not-to-use (use openfinance_list_credit_card_bills for standardized open-bill total), and alternatives (e.g., check connection health if total is 0).

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 discloses the 5000-transaction cap per account with a truncation flag, the compact summary format for monthly granularity, and the behavior when 'item' is omitted. 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 dense but well-structured, starting with the main purpose and then detailing parameters and usage. Slightly verbose, but every sentence adds value, making it efficient for an AI agent.

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 6 parameters, no output schema, and complex behavior (truncation, granularity details, filtering), the description covers all aspects: return format, edge cases (all banks by omitting item), and operational limits. It is fully self-contained.

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?

All six parameters are explained in the description despite 0% schema coverage. 'from'/'to' are specified as ISO dates, 'item' accepts multiple identifiers, 'granularity' has monthly/raw with behavioral differences, 'type' filters account types, and 'top_n' is implied in top expenses/revenues. 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 clearly defines the tool as consolidated cash-flow analysis for a bank connection, resolving accounts internally and avoiding separate calls. It distinguishes from sibling tools like openfinance_list_accounts and openfinance_list_transactions by emphasizing one-call efficiency and specific use cases like 'fluxo de caixa' and 'maiores gastos/recebimentos'.

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 states when to use this tool (annual/monthly analysis, cash flow, etc.), explains when to set granularity to 'raw' vs 'monthly', and advises against calling openfinance_list_accounts first. Also clarifies how to target a single bank or all banks by omitting the 'item' 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?

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint. The description adds substantial behavioral detail: returns global indicator (none/minor/major/critical), degraded components, open incidents, and `your_banks_affected`. This goes beyond annotations and provides a clear picture of what the tool does and returns.

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 paragraph that is well-structured and front-loaded with the main purpose. It is informative but slightly verbose; every sentence adds value, but it could be more concise. Still, it achieves good readability.

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

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

Given the tool has no parameters and annotations cover safety, the description provides sufficient context about what it returns (global indicator, degraded components, open incidents, your_banks_affected). It is complete for its purpose, though it could mention any usage limitations or output format details. Overall 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 parameters, so the baseline is 4. The description does not need to add parameter semantics, and it correctly omits any parameter discussion. Schema coverage is 100% because there are no parameters.

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

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

The description clearly states that the tool checks the LIVE operational status of the Open Finance provider, distinguishing it from the sibling tool openfinance_get_item_status. The verb 'checks' and resource 'Open Finance provider' are 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?

The description provides explicit when-to-use guidance: use when data looks incomplete or stale despite a connection showing UPDATED. It also clarifies that the tool helps differentiate provider-side problems from connection issues, effectively guiding the agent on when to invoke this tool over 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?

Expands on annotations by detailing that it honors user's plan, returns a pre-selected connect_url, and that missing keywords returns a hint instead of full catalog. 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?

Concise for the amount of detail, well-structured with clear purpose, usage, and caveats, though slightly verbose in listing return fields.

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?

Provides sufficient context for a search tool: describes inputs, outputs, plan behavior, and use case. Lacks edge cases but overall 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?

Despite 0% schema coverage, description explains keywords as required and include_accounts for returning accounts, 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?

The description clearly states it searches bank connectors by name keywords, returns specific fields including a connect_url, and differentiates from sibling tools like listing all 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 says to call before connecting and provides guidance that keywords are required; however, it does not mention when not to use or compare to 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?

Discloses significant side effects beyond minimal annotations: overrides automatic categorization, creates Category Rules for future similar transactions, and describes batch error handling. 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?

Single paragraph, front-loaded with purpose, ends with batch shape. Informative but could tighten; still efficient 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?

Provides return shape, side effects, and parameter sources. Missing explicit auth/rate limit mentions, but given no output schema and sibling authentication tool, it is sufficiently 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?

Despite 0% schema description coverage, the description explains the items array structure and the source of each field (transaction_id from list, category_id from list), adding meaning beyond the bare schema types.

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 'Corrects the category of one or more transactions' with specific verb and resource, and distinguishes from sibling list tools by indicating it's a PATCH operation that modifies data.

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 mentions where to get transaction_id and category_id (from openfinance_list_transactions and openfinance_list_categories), and when to use (fix miscategorized transactions). Lacks explicit when-not-to-use but context implies correction-only purpose.

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 idempotent and not destructive. Description adds context by specifying the need for conversation for reproduction. 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 focused sentences: one for purpose, one for usage hint. 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?

Adequate for a simple bug report tool, but lacks description of the required 'message' field and expected response behavior. No output schema, so more detail on return value 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?

Only the conversation parameter is explained in description ('Include the conversation array...'). Required 'message' and optional 'context' are not described. With 0% schema coverage, description adds some value but not enough.

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 action (report) and resource (bug, missing feature, feedback). Distinct from sibling tools which are primarily finance-related.

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 context for use (reporting issues) and specific guidance on including conversation array. Lacks explicit when-not-to-use or 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 declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description confirms read behavior by stating what is shown but adds no further behavioral traits (e.g., whether it fetches from cache, performance). No contradiction, but no extra 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?

A single sentence that is front-loaded with the verb and resource, zero wasted words. Perfectly concise for a tool with no parameters.

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

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

With no output schema, the description should explain the return value structure. It only states that versions are shown but not their format (e.g., strings, objects). This is a gap for a completionist view. However, given the tool's simplicity, the impact is minimal.

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 is 100%. The rule for 0 parameters gives a baseline of 4. The description does not need to add parameter semantics.

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 'Show' and the specific resource 'current MCP platform and adapter versions', which is distinct from all sibling tools such as 'authenticate', 'connect', and various 'openfinance_' tools. No ambiguity.

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 (when version info is needed) but provides no explicit guidance on when not to use or alternatives. Since sibling tools are unrelated, this is acceptable but lacks explicit 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?

The description goes beyond the annotations (readOnlyHint, idempotentHint, destructiveHint) by detailing what specific information is returned (installed MCPs, connection status, catalog tool counts). Annotations already provide a safety profile; the description adds useful behavioral context about the output content.

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 conveys the tool's purpose efficiently. Every word earns its place; there is no extraneous information. It is front-loaded with the verb 'Returns' and immediately specifies the output content.

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

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

For a simple read-only status tool with no output schema and no parameters, the description adequately explains what the tool does and what it returns. However, it lacks details about the output format (e.g., JSON structure) and does not clarify if the result is a flat list or nested. Still, it provides enough context for an agent to decide to invoke the 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?

The input schema has no parameters (0 params, 100% coverage). The description correctly implies no input is needed. Since there are no parameters to document, the baseline of 4 is appropriate; the description adds no additional param information because none exists.

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 toolkit state including installed MCPs, connection status, and catalog tool counts. It uses specific nouns ('toolkit state', 'installed MCPs', 'connection status', 'catalog tools') and a verb ('returns'). None of the sibling tools perform this function, so it is well-differentiated.

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 provide explicit when-to-use or when-not-to-use guidance. It is implied that this is a read-only information tool for checking system status, but no alternatives or exclusions are mentioned. Given the sibling tools are all specific actions, the usage context is clear but not explicitly guided.

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