Safra MCP

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

The description reveals that setting a permanent token in config is non-expiring, and session login is per-session. It matches annotations (idempotentHint, destructiveHint false) and adds context about the token's lifetime.

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 effectively conveys the two methods, but it could be more structured (e.g., separate bullet points) and is slightly informal.

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 explains inputs and behavior but does not describe the output (e.g., format of the returned link) or error cases. Given the simplicity, it is 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?

The schema only defines 'token' as a string with no description. The description adds crucial meaning: omitting it yields a login link, including it authenticates. This compensates for 0% schema coverage.

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 for authentication (logging in) and specifies two methods: permanent via config or session via token. It targets IDE agents, but does not explicitly distinguish from sibling tools like 'connect'.

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 two ways to use the tool (with no args to get link, or with token to authenticate), but does not compare to alternative tools or indicate when to use which method.

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 meaningful context beyond annotations (readOnlyHint, idempotentHint) by explaining the different return states (authenticated vs connect_url) and the structure of pending[]. It 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?

The description is two sentences, front-loaded with the core purpose, and every sentence provides essential information without redundancy.

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

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

The description explains the return values (authenticated, pending, connect_url) sufficiently for a simple status tool, but does not cover potential error states or additional fields. With no output schema, it is fairly 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 no parameters, and schema coverage is 100%. Baseline for 0 params is 4, and the description does not need to add parameter information.

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 behavior for when all providers are connected (authenticated:true, empty pending[]) and when credentials are missing (connect_url). It distinguishes from sibling tools like `openfinance_list_connections` which likely list individual provider connections, by focusing on the overall toolkit connection state.

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 overall connection status, but does not explicitly state when to use this tool versus alternatives (e.g., `authenticate` or `openfinance_list_connections`). It lacks 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?

Beyond annotations, the description discloses important behavioral traits: invoke works even when the MCP is not installed and runs one-off without bloating the toolkit; it returns a connect link if credentials are needed and a checkout/top-up link if payment is required; writes require workspace owner/admin. Annotations (readOnlyHint=false, destructiveHint=false) are consistent with the described mutable operations, so 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 long, but it covers a multi-action tool with 23 parameters and a secondary prompt library. It is front-loaded with the core flow and avoids fluff, but it is dense and could benefit from bullet points or clearer section separation. Most sentences carry relevant information; the length is justified by complexity, though it is not as succinct as it could be.

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 23 parameters, no output schema, and the dual role of MCP marketplace plus prompt library, the description is quite thorough. It explains the core flow, edge cases (auth/payment links), permission model, and the install-vs-invoke decision. It omits details on some actions (e.g., resume) and parameters, but the breadth is strong. A full parameter-by-parameter breakdown would make it more complete but likely too lengthy.

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 must compensate. It does explain the central 'action' parameter by enumerating all enum values and their intended use (search, describe, install, invoke, prompt operations). It also explains tool_id, mcp_id indirectly in the core flow. However, many parameters (limit, query, arguments, immediate, prompt_vars, etc.) are not explicitly mentioned, though their meanings may be inferable. The description adds significant semantic value but does not fully cover all 23 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 this is the official mcp.ai marketplace, covering the in-platform catalog of every MCP/tool and the way to run them. It enumerates the full set of actions (search, describe, install, invoke, manage prompts, etc.) and differentiates from openfinance_* and other siblings by describing its role as a universal MCP discovery/runtime platform.

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 usage flow: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile ... so you pick the right tool_id → invoke RUNS that tool.' It clearly contrasts invoke vs install: 'Use install only to make an MCP PERMANENT ... prefer invoke for a single/occasional use.' Also states when to use list_tools, subscribe/cancel, report_bug, and request_mcp, plus permission requirements 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?

The description aligns with the destructiveHint annotation by stating data is deleted and unavailable. It adds context that a re-connection URL is returned, which is useful behavioral information 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 long, front-loading the core action and effects with no superfluous words.

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

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

For a destructive tool with one parameter and no output schema, the description covers the primary effect and return value but omits parameter details and potential side effects, making it marginally 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 schema has 0% coverage (no parameter descriptions), and the description does not explain the 'item' parameter. It only mentions 'for a specific bank', which is insufficient to understand what value to provide.

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 revokes consent and deletes connection data for a specific bank. It is a precise verb-resource action ('disconnects a bank') and is distinct from sibling tools like force_sync or 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?

The description does not explicitly say when to use this tool versus alternatives. It mentions a re-connection URL, which hints at a use case, but lacks guidance on when not to use it or prerequisites.

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

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

Annotations indicate non-readonly, non-destructive. The description adds: waits up to ~60s, polls, returns detailed status (executionStatus, lastUpdatedAt, synced). It explains needs_action with reconnect_url and timed_out behavior, and confirms no disconnect/reconnect. 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?

The description is front-loaded with the key action and use case. It structures parameter details, return values, and edge cases logically. Slightly verbose around needs_action but remains efficient and well-organized.

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 use case, parameter options, return format (results, errors with status fields), error states (needs_action, timed_out), and follow-up actions. Despite no output schema, the description provides adequate detail for correct invocation and handling.

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. The description compensates fully: explains items accepts various selectors (item_id, connector_id, etc.) and that omitting it syncs all. Describes wait as boolean for synchronous vs. fire-and-forget. Adds meaningful context beyond 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 'forces re-sync' and the resource 'connections'. It specifies synchronous waiting and contrasts with sibling tools like openfinance_get_item_status. The purpose is unambiguous and 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?

Explicit when-to-use guidance: 'when a balance or transaction list looks stale'. It explains when not to use (no disconnect needed) and provides alternatives for timeout cases (openfinance_get_item_status). Parameter wait: false for fire-and-forget is also clarified.

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

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

Even though annotations already mark readOnlyHint and idempotentHint as true, the description adds substantial behavioral context: the balance is a snapshot anchored to the last upstream sync, stale data is normal, rows can degrade with realtime:false and warnings, and credit accounts may return BALANCE_FETCH_ERROR. This goes well beyond the annotations and makes runtime behavior predictable.

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 fairly long, but every sentence adds operational value: endpoint identity, freshness semantics, sync guidance, credit-card error behavior, degradation behavior, and response shape. The most important behavioral fact (snapshot not live read) 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?

With no output schema, the description provides the response envelope, error format, warning semantics, and degradation conditions. Given the single parameter and the read-only, idempotent annotation profile, nothing essential is missing for an agent to invoke and interpret 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%, so the description must compensate. It explains that account_ids must be passed as an array and constrained to 1–50 items, and it clarifies the per-account behavior including errors. It could add what constitutes a valid account ID, but for a single parameter the added meaning is strong.

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 opens with a specific verb and resource: 'Returns the latest available balance per account id (GET /accounts/:id/balance).' It immediately distinguishes itself from related tools like openfinance_list_transactions and openfinance_force_sync by explaining what this tool does and what it does not do.

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 explicit when-to-use and when-not-to-use guidance: if the balance is stale or disagrees with openfinance_list_transactions, run openfinance_force_sync and re-read. It also explains edge cases like credit accounts and upstream unavailability, so an agent knows how to interpret and act on results.

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, destructiveHint. Description adds critical behavioral info: batch shape with results/errors, and the provider_incident block with a caveat about unreliable data during provider outages. This goes beyond annotations and is essential for safe usage.

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 concise, front-loaded with purpose, and covers key points in a single paragraph. Could be slightly more structured but is 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?

Given no output schema, description explains return shape and provider_incident behavior. For a 1-param tool, it's fairly complete, though could clarify error handling or response format further.

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 1 parameter with no description (0% coverage). Description adds meaning by constraining the array size (1–50) and mentioning batch shape, compensating for the schema's lack of detail.

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 by id, specifying the GET endpoint and batch shape. It distinguishes from sibling tools like openfinance_list_accounts, which likely provides a list without detail.

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 pass account_ids as an array of 1–50, implying usage when needing detailed account info. Does not mention when not to use or alternatives, but 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?

Annotations already provide readOnlyHint and idempotentHint, so the added value is purely complementary: the extra full-account scan cost of the opt-in, the transactions_basis semantics (bill_id vs date_window vs unavailable), the authoritative-total warning never to sum transactions, the batch { results, errors } shape, and the Pluggy/Open Finance payments-not-paid cross-bill subtlety. No contradiction with the safe, idempotent 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 every sentence earns its place, and it is well laundered: core return fields, then the OPT-IN feature, then the basis taxonomy, then warnings, then the batch shape. The staggered paragraph grouping makes a dense topic navigable and the container-specific caveat is front-loaded enough that an agent will hit it before acting.

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 there is no output schema, the description takes on the work of defining the response semantics, including the multiple transactions_basis modes and their confidence levels, the totalAmount authority rule, and the previous-bill payment caveat. The only unaddressed detail is the transactions_detail enum, but for a tool this complex, the practical guidance here is both complete and actionable.

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 carries the full burden, and it compensates well for three of the four parameters: bill_ids (discover via the list sibling), account_id (needed at opt-in time because the bill carries no account reference), and include_transactions (activates the transaction scan). One gap remains: the transactions_detail enum (compact/rich/raw) is never explained, leaving the agent to guess the meaning of those values.

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 opens with a specific verb+resource statement — "Returns bill-level detail for one or more credit card bills by id (GET /bills/:id)" — and enumerates the actual fields returned. It also differentiates itself from siblings by noting the bill payload itself has no transactions and that paid-status checks belong on openfinance_list_credit_card_bills.

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?

Usage context is explicit: use openfinance_list_credit_card_bills first to discover bill_ids, pass include_transactions plus account_id to opt into transaction stitching, and fetch transactions manually via openfinance_list_transactions when not opting in. It also gives an exclusion — do NOT use this tool's payments[] to infer paid status; prefer the sibling tool, which derives payment_status.

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 readOnly, idempotent, non-destructive. Description adds value by explaining return fields (status, executionStatus, connector metadata, reconnect_url) and behavior of reconnect_url, which reopens widget in UPDATE mode without disconnecting or consuming a slot.

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 plus a line on bulk support. Front-loaded with purpose, then usage details. No redundant 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?

Covers core functionality, modes, and return fields. Lacks details on error handling, rate limits, or pagination. For a read-only status tool, it is reasonably 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 explains 'item' for single bank, 'item_ids' for bulk, but does not clarify 'item_id' parameter. Adds meaning beyond schema, but could be more precise on parameter 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?

The description clearly states the tool returns the current status of a bank connection, lists possible statuses, and distinguishes between single bank and all banks modes. It also mentions bulk support via item_ids.

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 guidance on when to use 'item' for a single bank and omit for all banks, plus bulk support. However, it does not explicitly compare to sibling tools like openfinance_list_connections or give when-not-to-use conditions.

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 and idempotent. Description adds HTTP method (GET), batch shape {results, errors}, and limit of 1-50 IDs. 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?

Description is dense but front-loaded with purpose; each part is useful. Could be slightly more structured, but 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?

No output schema, but description covers return fields comprehensively (interestRates, charged fees, installments, etc.) and explains batch shape. Lacks error details but sufficient for a detail retrieval 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?

Schema has 0% description coverage. Description compensates by explaining loan_ids is an array with size constraint (1-50), adding value beyond 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?

Description clearly states it returns full loan contract detail by ID, lists many fields, and distinguishes from sibling tools by explicitly mentioning usage after openfinance_list_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?

Explicitly states when to use (after openfinance_list_loans), how to use (pass loan_ids as array 1-50), and describes batch response shape.

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

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

Even though annotations already set readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds substantial behavioral context beyond them: credit balance is not always the billed amount, bankData fields can lag until a force sync, provider_incident blocks mean values may be unreliable, and identity_notice requires deduplicating joint accounts by account number. This is exactly the kind of operational nuance an agent needs.

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 every block earns its place: core return, bank-name distinction, item usage rule, credit/bill semantics, stale-field warnings, incident notice, identity handling, and bulk support. It front-loads the most important purpose and filtering guidance before diving into caveats.

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 still covers the main response contents, account types, bank/connector fields, subtle balance semantics, provider-lag behavior, incidents, identity-notice deduplication, and batching. There is enough for an agent to call the tool correctly and to interpret the result accurately in a wide range of real Open Finance scenarios.

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

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

Schema description coverage is 0%, so the narrative carries full responsibility for parameter semantics. It effectively explains the distinction between omitting vs passing `item`, explains the `item` and` options, describes BANK/CREDIT categories, and says `item_ids` are accepted for batch execution. The only residual gap is that singular `item_id` is not explicitly explained and `type` is not explicitly framed as a filter, so it is very strong but not perfect.

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 states exactly what the tool does: returns accounts for bank connections, separating BANK and CREDIT accounts, and names the returned fields (balance, number, type, subtype, bankData, creditData) plus bank/connector identity. This is a specific verb+resource statement that makes the tool clearly distinct from account-balance, bill, transaction, and loan 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?

The description gives explicit when-to-use guidance: omit `item` when the user asks for 'my accounts/cards' across all linked banks, pass `item` to target a single bank connection, and use openfinance_list_credit_card_bills for standardized open-bill and pending-debt amounts. This is actionable decision support for an agent.

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 valuable context: cached per session, single aggregated response with no batch ids, and explicit field clarifications.

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 and well-structured: it states the function, explains the cached nature, lists each output field with its significance, and ends with a note on the response shape. Every sentence adds value.

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 zero parameters, rich annotations, and no output schema, the description adequately explains what the tool returns. It covers the fields but could briefly mention the hierarchical tree structure for 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?

No parameters exist, so schema coverage is 100%. The description naturally does not add parameter details, meeting the baseline for zero-parameter tools.

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, cached for the session. It references the endpoint and details the fields, distinguishing it from siblings by noting the id is used by openfinance_update_transaction_category.

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 before updating transaction categories, but does not explicitly state when to use or avoid this tool. It provides clear context without exclusionary 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 indicate readOnlyHint=true and destructiveHint=false. Description adds valuable context: reconnect_url opens widget in UPDATE mode, does not consume connection slot, no need to disconnect. This goes 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?

Information-dense single sentence with good structure (colon, em-dash). All sentences are earned, though slightly lengthy. Could be more concise but well-organized.

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 explains output fields and reconnect_url behavior adequately. Does not mention pagination, but for a list of saved connections it's likely acceptable.

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?

Input schema has no parameters, so baseline 4. Description adds meaning about the output fields (connector_id, item_id, etc.), though this is more about return values than 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?

Clearly states it returns saved bank connections with specific fields (connector_id, item_id, bank name, reconnect_url, add_connection_url). Distinguishes from siblings by detailing the purpose of reconnect_url vs add_connection_url.

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 context on when to use reconnect_url (re-authentication, MFA, LOGIN_ERROR, stale data) but does not explicitly compare with other listing tools like openfinance_list_accounts. Usage guidance is implied but not exhaustive.

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: true, etc.), the description adds critical behavioral context: payment semantics, derived payment_status, connector asymmetry, bill grouping reliability, and return structure. 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 long but well-structured with paragraphs and emphasis on key points. It front-loads the main purpose and then details nuances. Could be more concise with bullet points, but every part adds value given 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, annotations, and lack of output schema, the description is exceptionally complete. It covers return fields, derived fields, payment semantics, error conditions, cross-tool references, account echo block, and warnings about connector limitations.

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% so the description must compensate. It explains include_open_bill and account_ids in detail, but does not explicitly describe page/page_size parameters. However, the important parameters are well covered, adding significant value 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 returns closed credit card bills for CREDIT-type accounts, listing specific fields. It distinguishes from siblings like openfinance_get_credit_card_bill (singular) and openfinance_list_transactions (for individual transactions), and specifies it is bill-level summaries.

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 extensive guidance: when to use include_open_bill, connector asymmetry, payment status interpretation, and directs to other tools for transactions. It explicitly states when not to assume payment status and warns about cross-bill payment semantics.

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, destructiveHint. The description adds significant behavioral detail: error handling (returns {total,results,warning} instead of throwing), data integrity warnings for mass zeroing, and the flagging of suspect rows. 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 well-structured with a clear opening that states the purpose, followed by error handling and data integrity details. It is front-loaded but somewhat verbose in the data integrity section. Overall, it is informative without being overly long.

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

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

Given the complexity of the tool and the absence of an output schema and parameter descriptions, the description covers many aspects: asset types, response fields, error handling, and data integrity. It lacks some details on pagination parameters and the distinction between 'item' and 'item_ids', but is still quite 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 input schema has 6 parameters with 0% description coverage. The description only adds value for 'item_ids' (bulk support) and does not explain 'item', 'page', 'type', 'page_size', or 'item_id'. With low schema coverage, the description should compensate but fails to define most 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 it returns the investment portfolio for a connection, listing specific asset types (FIIs, stocks, etc.). It distinguishes itself from sibling tools like list_investment_transactions by focusing on the portfolio snapshot.

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 bulk support via item_ids and explains behavior when INVESTMENTS is not enabled (returns a warning instead of throwing). However, it lacks explicit guidance on when to use this tool versus other list tools, and does not state prerequisites or typical usage 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 already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds behavioral detail beyond annotations: it lists transaction types, return fields (quantity, value, expenses breakdown), and bulk execution. No contradictions, and it enriches the behavioral 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?

Two concise sentences in the first paragraph and a single sentence for usage guidance. Every sentence adds value: describes output, states prerequisites, and mentions bulk support. No fluff, and key information 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?

With 4 parameters, no output schema, and 0% schema coverage, the description covers the main parameter and return structure well. It omits pagination parameters but given the read-only list nature, pagination is somewhat standard. Still, a bit more detail on page/page_size would make it 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 description coverage is 0%, so the description must compensate. It explains investment_id (required) and investment_ids (bulk). However, it does not describe page and page_size parameters. While the main parameters are covered, the pagination parameters are missing, which is a gap.

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

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

The description uses a specific verb ('Returns') and clearly identifies the resource ('movement history for a specific investment position'). It lists transaction types and fields, and distinguishes from sibling tools like openfinance_list_investments by stating it's used after that tool. This is explicit and avoids 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 explicitly states to use after openfinance_list_investments to get the investment_id, providing clear sequencing context. It also mentions bulk support with investment_ids. However, it does not specify when not to use or mention alternatives, but the guidance is sufficient for correct invocation.

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 value beyond readOnlyHint, idempotentHint: describes sequential per-connection execution, rate-limit handling, and return format. 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 tightly written sentences. First front-loads purpose, second explains parameter, third covers alternatives and return format. No superfluous 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?

Covers core usage, parameter behavior, return format per connection. Lacks mention of potential errors or prerequisites (e.g., authentication status). Still strong for a list operation.

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 description fully explains `items`: array of connection selectors with three types (item_id uuid, connector_id, or connector_name) and behavior when omitted. Adds meaning far beyond empty 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 it lists loan contracts per bank connection with specific HTTP endpoint (GET /loans). Distinguishes from sibling tools like openfinance_list_accounts by focusing 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?

Explicitly explains when to pass `items` and when to omit for all banks. Mentions sequential querying with rate-limit spacing. Does not formally contrast with tools like openfinance_get_loan_detail, but 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?

The description discloses non-trivial behaviors not available from annotations: scheduled-installment ordering, auto-pagination vs manual pagination, per-connector inconsistencies, provider_incident blocks, and graceful error return shape. All of this adds value beyond the readOnly/idempotent hints.

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 very long and dense, and includes some repeated nuances around billId/Nubank inconsistencies. However, the critical information is front-loaded, and the length is largely justified because the tool has many edge cases and the schema provides no per-parameter descriptions.

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 still covers return shape, account echo, pagination, truncated warning, scheduled_count, detail modes, and failure behavior. It addresses both normal and error flows, so an agent has enough context to invoke the tool correctly across varied credit and pagination scenarios.

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

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

Schema description coverage is 0%, but the description compensates thoroughly: from/to formats, search_queries semantics, page/page_size behavior including defaults and maximums, detail modes, account_id, and bulk account_ids are all explained with operational context. No parameter is left undocumented.

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

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

The description opens with a specific verb and resource: 'Returns transactions for a bank account (BANK or CREDIT type).' It further distinguishes the tool as 'the ONLY way to get itemized transactions' for credit accounts, helping separate it from sibling tools like openfinance_list_credit_card_bills.

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 names alternatives and gives the decision rule: use openfinance_list_credit_card_bills for a standardized open-bill total, openfinance_list_accounts for closing/due dates, and openfinance_get_item_status when a zero credit account suggests sync failure. This far exceeds basic usage 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?

The description adds significant behavioral context beyond annotations: it discloses a 5000-transaction cap per account with a truncated flag, the provider_incident block for incomplete data, and the effect of granularity and detail parameters on output. Since annotations already mark the tool as readOnlyHint and idempotentHint, the description enriches transparency 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 front-loaded with the key value proposition and is well-structured, but it is somewhat lengthy due to detailed parameter explanations and multiple use-case examples. While every sentence adds value, it could be slightly more concise without losing essential 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?

Given 9 parameters and no output schema, the description provides comprehensive coverage: input semantics, output structure (compact summary fields: total entradas, saídas, saldo_liquido, por_mes, top_despesas/recebimentos, by_account), raw output details, truncation behavior, and provider incident impact. It leaves no major gaps for an AI agent to select and invoke 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?

Despite 0% schema description coverage, the description thoroughly explains all 9 parameters: item (accepts connector_id, connector_name, or item_id), from/to (ISO dates), granularity (monthly vs raw with meaning), detail (compact/rich/raw meanings), type (BANK or CREDIT), top_n, item_id, and item_ids (batch support). It also specifies defaults like granularity:'monthly' and the purpose of each enum value, fully compensating 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 that this tool provides 'Consolidated cash-flow analysis for a whole bank CONNECTION over a period, in ONE call.' It distinguishes itself from siblings like openfinance_list_accounts and openfinance_list_transactions by highlighting that it internally resolves accounts and fans out transactions, eliminating the need for separate calls. This makes the purpose specific and 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 explicitly explains when to use this tool vs. alternatives, stating 'you do NOT need to call openfinance_list_accounts first nor carry account_id uuids between calls.' It provides use cases like 'análise anual/mensal', 'fluxo de caixa', and guidance on granularity ('Set granularity:"raw" to ALSO get every consolidated transaction'). It also mentions limitations (5000/account cap with truncated flag) and the provider_incident block, giving comprehensive usage 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?

Annotations already declare readOnlyHint and idempotentHint, so the description adds value by detailing the output: global indicator, degraded components, incidents, and 'your_banks_affected', and noting it's live from a public page.

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 but relatively long; however, every part is relevant and well-structured. Slightly verbose but not wasteful.

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 explains the return value and usage context, making it 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?

No parameters exist; schema coverage is 100%, so no additional param info needed. Baseline 4 is appropriate.

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

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

The description clearly states it checks the 'LIVE operational status of the Open Finance provider', distinguishing it from the sibling 'openfinance_get_item_status' by specifying it's provider health, not 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 says when to use (data incomplete/stale despite updated connection) and what it helps to discern (provider-side problem vs connection issue), with no exclusions needed.

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. The description adds behavioral context: returns connector details, a connect_url, and caveat warnings for non-Open-Finance connectors. It also explains plan behavior. This goes beyond the 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?

The description is comprehensive but somewhat verbose, with some redundancy (e.g., the required nature of keywords is stated twice). It could be more concise while retaining essential details.

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

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

Given no output schema and only two parameters, the description fully covers inputs, outputs, usage context, and special behaviors (caveats, plan restrictions). It leaves no obvious gaps for the agent to understand 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?

Schema coverage is 0%, but the description explains keywords (required array of strings) and include_accounts (boolean to include accounts). Since only two parameters exist, the description compensates well by providing functional 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 searches bank connectors by name using a keywords array, and specifies what is returned. It distinguishes itself from siblings by mentioning it should be called before connecting, making its role unique among the 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?

Provides explicit guidance: call this before connecting, keywords are required, and notes plan-dependent behavior. However, it does not explicitly mention when not to use this tool or compare with alternatives beyond the implicit context that this is the search step.

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 are minimal (all false), so the description carries the full burden. It discloses that recategorizing creates a Category Rule for future similar transactions, which is a significant behavioral trait beyond the basic update. It also describes the batch error handling and output shape.

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 each sentence adds value. It is structured: purpose, parameter details, behavioral side effect, and error handling. A bit verbose but not wasteful.

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 one parameter (array of objects) and no output schema, the description thoroughly explains input format, side effects, and output shape. It is complete for an agent to select and invoke 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 description coverage is 0%, so the description adds full meaning. It explains that 'items' is an array of { transaction_id, category_id } and tells the agent where to obtain each ID from other tools. No additional parameters exist.

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 corrects the category of transactions using PATCH, specifying the resource and action. It distinguishes itself from sibling tools like openfinance_list_transactions and openfinance_list_categories by focusing on updating categories.

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 (fix miscategorized transactions) and provides sourcing for parameters (transaction_id from openfinance_list_transactions, category_id from openfinance_list_categories). It doesn't explicitly state when not to use, but the use case is specific and no alternatives are obvious among siblings.

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 idempotentHint=true and destructiveHint=false, conveying safety traits. The description adds no behavioral context beyond these annotations, such as whether the report creates a ticket or triggers notifications.

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 succinct with two sentences. The first delivers purpose, the second provides actionable instruction. No unnecessary words or repetition.

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 feedback tool with 3 parameters and no output schema, the description covers the basic intent and a key usage tip. However, it omits what happens after reporting (e.g., confirmation, ticket creation) and any limits or side effects.

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

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

The schema has 0% description coverage, so the burden falls on the free-text description. It clarifies the 'conversation' parameter's purpose ('recent messages for reproduction') but does not explain 'context' or 'message' parameters in any detail.

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: reporting a bug, missing feature, or feedback. It uses a specific verb ('Report') and identifies resources. While it distinguishes from financial siblings by category, it does not explicitly differentiate from other non-financial 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 instructs users to include the conversation array, which is a useful guideline for proper reproduction. However, it lacks guidance on when to use this tool versus alternatives (e.g., when not to report bugs) and does not mention any 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 declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds specificity by naming the exact data returned (MCP platform and adapter versions), which is valuable context 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?

Single sentence of 9 words with no superfluous information. Perfectly concise and 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 zero parameters, no output schema, and annotations covering safety, the description fully specifies what the tool does and returns. 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?

No parameters, so schema coverage is 100%. The description correctly does not need to add parameter info. Baseline 4 for zero parameters 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?

Description clearly states the tool shows 'current MCP platform and adapter versions' with a specific verb and resource. It distinguishes itself from siblings because no other sibling tool provides version information.

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 retrieving version info. While no explicit when-not-to-use or alternatives are given, the tool's simplicity and lack of parameters make guidance less critical. A brief mention of when to use (e.g., 'Use to verify deployed versions') could improve it but not required.

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 detail beyond the annotations by listing the components of the returned state, which is valuable since there is no output schema. The annotations already declare readOnlyHint=true and destructiveHint=false, and the description is consistent, confirming a safe read-only operation without contradicting 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, tightly written sentence that front-loads the core purpose ('Returns the current toolkit state') and then quickly enumerates the specific data points. Every phrase adds value, and there is no redundancy or filler.

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 0-parameter, read-only info tool, the description is complete: it specifies the return content in enough detail to understand what the tool provides. It could optionally mention the format or typical use case, but given the simplicity and annotation coverage, the description sufficiently fulfills its role.

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 accepts zero parameters, so the input schema is trivially complete. The description correctly does not discuss parameters, and the baseline for 0-param tools is 4, with no need for parameter clarifications.

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

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

The description clearly states the tool's purpose with a specific verb ('Returns') and resource ('current toolkit state'), and enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like openfinance_list_accounts or 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 provides clear context on what information the tool returns, which implies when to use it (e.g., to assess connectivity or tool availability). While it doesn't explicitly mention alternatives or when not to use it, no sibling tool offers similar functionality, so the absence of exclusions is not a significant gap.

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