Player's Bank MCP

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

Annotations indicate idempotentHint=true, destructiveHint=false, and readOnlyHint=false. The description adds context beyond annotations by explaining token usage, session vs permanent modes, and browser login flow. 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 a single paragraph but efficiently front-loaded with audience and purpose, then presents best practice and alternative usage. Every sentence adds value with no redundancy.

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

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

For a simple authentication tool with no output schema, the description covers input options and usage scenarios well. It lacks explicit info about return values (e.g., success message or token confirmed), but given the tool's straightforward nature, it is mostly 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 single parameter 'token' has 0% schema description coverage. The description fully explains its meaning: it's the JWT access token from browser login, optional, and can be omitted to get a login link. This adds necessary semantic meaning.

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

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

The description clearly states the tool's purpose: to authenticate for MCP.AI IDE agents. It uses specific verb 'log in' and 'authenticate' and distinguishes from sibling tools like 'connect' and 'marketplace', which are not authentication-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?

The description provides explicit guidance on when and how to use the tool: best practice to add token to config for permanent connection, or paste token for session-only login. It also explains how to call with or without the token parameter, and gives 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, idempotentHint, and destructiveHint, indicating a safe read operation. The description adds value by detailing the response structure (authenticated, pending, connect_url) and conditional behavior (credential-dependent), going beyond what annotations provide.

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

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

The description is two sentences, front-loaded with the main purpose, and all information is relevant. 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?

Given the tool has no parameters and no output schema, the description adequately explains the return values and conditions. It covers the main scenarios (all connected vs missing credentials), providing sufficient context for an AI agent to understand the tool's behavior.

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

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

The tool has no parameters, so the description does not need to add parameter information. Baseline score of 4 is appropriate as schema coverage is 100% and no additional semantics are required.

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: returns connection status and URLs. It differentiates behavior based on connection state (all providers connected vs missing credentials), making the purpose specific and actionable.

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 what the tool does but does not provide explicit guidance on when to use it over sibling tools like 'authenticate' or 'openfinance_provider_status'. The context is implied but not compared 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?

Beyond annotations, the description adds rich behavioral details: invoke works even without MCP installed, returns connect/checkout links, install makes permanent, and writes need admin. No contradiction with annotations.

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

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

The description is verbose and narrative, but it is front-loaded with the core purpose. Some redundancy exists; could be more concise. Still, it earns its length for the most part.

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 (13 params, many actions, no output schema), the description covers the overall flow, action behaviors, and error handling (links). Missing return value details but sufficient for core 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?

Schema coverage is 0%, so description must compensate. It explains the 'action' parameter (enum values) and overall flow, but does not detail most parameters (limit, arguments, tier_slug, etc.). Adequate but incomplete.

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 it is the official mcp.ai marketplace and defines its purpose as discovering, describing, and running tools. It uses specific verbs like 'search', 'describe', 'invoke', and distinguishes itself from 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?

The description provides explicit 'when to use' guidance, stating to use this tool first before any external registry. It differentiates between invoke and install, explains credential/payment handling, and notes that writes require workspace owner/admin.

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 behavioral context beyond annotations: it states that data will no longer be available and that a reconnection URL is returned. Annotations already indicate destructiveHint=true, so this reinforces and expands on that. 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 only two sentences, front-loaded with the core action. Every sentence adds value: purpose, consequence, and return value. No unnecessary words.

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

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

For a destructive tool with one parameter, the description covers the main action and outcome, including the return value. However, it lacks parameter documentation and does not explain which bank is affected (e.g., how 'item' is specified). With no output schema, more detail on the return value format 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?

The single parameter 'item' is not described in the schema or description. Schema coverage is 0%, and the description does not clarify what 'item' represents (e.g., bank ID, connection ID). The description fails to add meaning to the parameter.

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 revokes consent and deletes connection data for a specific bank. It uses specific verbs and resources, making the purpose obvious. However, it does not explicitly differentiate from sibling tools like openfinance_list_connections, which are about viewing connections rather than deleting them.

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

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

No guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites, when not to use it, or suggest other tools for related tasks like listing connections before disconnecting.

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 mechanism (PATCH then poll), timeout (~60s), return fields (status, executionStatus, lastUpdatedAt, synced, needs_action, timed_out), and the effect of wait:false. No annotation 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?

Well-structured and front-loaded, but slightly verbose. Could trim some details without losing meaning, but overall efficient.

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

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

Covers purpose, usage, parameters, return values, and timeout behavior. No output schema, but return format is described adequately. No missing critical information.

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

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

With 0% schema coverage, description fully explains both parameters: 'items' as array of selectors with examples, and 'wait' as boolean for fire-and-forget. Also covers omitting items to sync all.

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 action ('forces re-sync'), resource ('one or more connections'), and timing ('NOW and WAITS'). Distinguishes from sibling tools by specifying when to use (stale data) and what it avoids (disconnecting/reconnecting).

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 when balance or transaction list looks stale. Provides alternatives: fire-and-forget with wait:false, and re-check with openfinance_get_item_status on timeout. Also explains scope: omit items to sync all.

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, and non-destructive behavior. The description adds valuable detail: real-time retrieval, potential BALANCE_FETCH_ERROR for CREDIT accounts with structured warnings, and the response shape with results and errors.

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

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

Three concise sentences: first states purpose, second adds parameter and error handling context, third describes response shape. 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?

Given the tool's simplicity (single parameter, no output schema), the description covers all necessary aspects: purpose, parameter constraint, error behavior, and response format, making it complete 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?

The input schema provides only the type (array of strings) with no description (0% coverage). The description adds the important constraint of 1–50 items, which aids correct invocation. No other parameter details 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?

Clearly states the tool returns real-time balance per account ID and specifies the endpoint. However, it does not explicitly differentiate from sibling tools like openfinance_list_accounts, though the purpose is distinct enough.

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: pass account_ids as an array with size 1–50, and notes error handling for CREDIT accounts. Does not explicitly state when not to use or list alternatives, but the guidance is sufficient.

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

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds context about returned fields (creditData) and batch error handling, which is useful but not critical beyond annotations.

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

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

The description is two sentences, front-loading the purpose and including the endpoint, parameter details, and response shape. Every sentence adds value 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 read tool with one parameter and no output schema, the description covers the action, input constraints, and response format sufficiently. No critical 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?

The input schema only defines account_ids as an array of strings with no description. The description adds that it must be an array of 1-50 IDs, providing essential constraints 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 full account objects including extended creditData for given account IDs, specifying the endpoint (GET /accounts/:id) and batch shape. It distinguishes from sibling tools like openfinance_list_accounts by focusing on detail retrieval per ID.

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

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

The description provides parameter guidance (array of 1-50 IDs) and output shape, but does not explicitly state when to use this tool versus alternatives like openfinance_list_accounts. Usage context is implied but not fully articulated.

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. The description adds context beyond annotations: batch response shape { results, errors }, notes that Pluggy does not return a paid/status field, and explains the semantics of payments array. 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?

Description is front-loaded with purpose, then dives into specific returned data and caveats. All sentences are informative, though the NOTE section could be slightly more concise. Overall, it's well-structured and 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?

Despite no output schema, the description fully explains the response shape (batch with results and errors), the fields returned, what is excluded (transactions, paid status), and how to get missing information. It also links to related tools and explains data interpretation. For a simple parameter tool, this is very 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 has 0% description coverage for the single parameter. The description compensates by explaining that bill_ids is an array of IDs, how to obtain them via the list tool, and that they must be passed as an array. This adds essential 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 returns bill-level detail for credit card bills by id, listing specific fields (financeCharges, payments with subfields). It distinguishes from sibling tools like openfinance_list_credit_card_bills (list only) and openfinance_list_transactions (itemized 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 advises to use openfinance_list_credit_card_bills first to discover IDs, and to use openfinance_list_transactions for itemized transactions. Also provides a critical caveat about the payments array representing previous bill payments, clarifying when not to assume paid 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 already declare readOnlyHint=true and idempotentHint=true, indicating a safe read operation. The description adds context about response structure (returns count/items or single status) but does not disclose additional behavioral traits like authentication needs 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?

Two sentences: first states main purpose and example statuses, second explains parameter usage. No extraneous content, perfectly 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 1 optional parameter, no output schema, and strong annotations, the description is complete. It covers usage variants and return format adequately.

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

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

Schema has 0% description coverage, but the description fully explains the param 'item': omit for all banks, pass for single. This adds essential meaning beyond the raw schema.

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

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

The description clearly states that the tool returns the current status of a bank connection, listing specific statuses like UPDATED, UPDATING, LOGIN_ERROR. It distinguishes between omitting 'item' (all banks) and passing 'item' (single bank), which differentiates it from sibling 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 explains when to omit vs pass the 'item' parameter, providing clear usage context. It does not explicitly say when not to use the tool or name alternatives, but the purpose is well-understood from the description.

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 behavioral context beyond annotations: explains aggregation behavior based on `item` parameter, the connector-dependent meaning of credit card balance, and the distinction between `name` and `bank` in responses. 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 information-dense but not overly verbose. It is structured logically: first the return fields, then naming nuance, then parameter usage, then warnings and alternatives. Could be slightly more concise, but remains clear.

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 fully explains return fields and structure (aggregated vs. root-level), warns about data interpretation, and references a complementary tool. Covers all necessary aspects for correct invocation.

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. Explains `item` behavior well (omit vs. provide), but does not explicitly state that `type` filters results to BANK or CREDIT accounts. The enum hints at this, but direct clarification 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?

The description clearly states that the tool returns accounts (BANK and CREDIT) with specific fields like balance, number, type, subtype, bankData, creditData. It also distinguishes between `name` and `bank`, and differentiates from sibling tool 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?

Provides explicit guidance on when to omit `item` (list all banks) vs. provide it (single bank), warns against misinterpreting credit card balance as the current bill, and directs to openfinance_list_credit_card_bills for standardized billing amounts.

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

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

Beyond annotations (readOnly, idempotent), the description adds valuable behavioral details: the response is cached for the adapter session, and it is a single aggregated response (no batch ids). This helps set expectations for freshness and pagination.

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

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

The description is well-structured and front-loaded with the core action, followed by output field details. It is slightly verbose but each sentence adds value, earning its place.

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

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

Given the tool's simplicity (no params, no output schema), the description is complete: it explains what it does, how it behaves (cached, single response), and the structure of each entry. No gaps are apparent.

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 zero parameters, so the default baseline is 4. The description adds meaning by explaining the output fields, but since no parameters exist, it fully compensates for the lack of schema details.

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

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

The description clearly states it returns Pluggy's transaction category taxonomy, cached per session. It mentions the relationship to another tool (openfinance_update_transaction_category), but does not explicitly differentiate it 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?

The description implies usage (to get categories before updating transactions) but does not explicitly state when to use or not use this tool. No alternatives are mentioned, and there is no guidance on when caching might be stale.

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 provide readOnlyHint=true, idempotentHint=true, destructiveHint=false, which already convey safety. The description adds that it returns specific fields and an add_connection_url, but does not disclose additional behavioral traits like rate limits or data freshness.

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 concise and front-loaded. Every word adds value: lists the return fields and the add_connection_url.

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 list tool with no output schema, the description adequately lists return fields. However, it omits details like pagination or response limits, which could be helpful given no output schema.

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

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

There are no parameters, and schema description coverage is 100% (empty schema). Baseline for zero parameters is 4. The description adds no parameter info, but none is 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?

The description clearly states it returns saved bank connections with specific fields: connector_id, item_id, bank name, and add_connection_url. The verb 'Returns' is precise, and the resource 'bank connections' distinguishes it from 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?

The description implies usage to view existing connections but does not explicitly state when to use this tool versus siblings like openfinance_list_accounts or openfinance_search_bank_connectors. No alternatives or exclusions are mentioned.

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 (readOnlyHint, idempotentHint, destructiveHint) are consistent with the description. The description adds valuable behavioral context: payment_status derivation, connector asymmetry, warning behavior if CREDIT_CARDS not enabled, and that results are bill-level summaries. 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 long but well-structured: starts with core function, then important caveats, optional feature, and alternative tool references. Every sentence adds value, though it could be slightly more concise. The length is justified by 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?

Despite no output schema, the description details the return structure (payments[], payment_status, open_bill, future_bills, totals), explains derivation logic, covers edge cases (connector asymmetry, payment timing), and references sibling tools. High completeness.

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

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

Schema description coverage is 0%, but the description fully compensates by explaining the purpose and effect of each parameter: account_id/account_ids for bulk, include_open_bill with its default and return structure, and page/page_size for pagination. The meaning of include_open_bill is especially well-explained.

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 itself from siblings like openfinance_get_credit_card_bill and openfinance_list_transactions by specifying its scope (bill-level summaries, not individual transactions).

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

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

Provides extensive guidance: when to use include_open_bill (opt-in), when not to assume payments are for the current bill, how to interpret payment_status, and refers to openfinance_list_transactions for itemized purchases. Explains default behavior and connector asymmetry, helping the agent choose appropriately.

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

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

Beyond annotations (readOnly, idempotent), the description details error handling behavior, returning a structured response instead of throwing errors for disabled features. This adds value beyond annotations.

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

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

The description is a single paragraph of moderate length, listing many relevant asset types and fields. It is not overly verbose, though lacking structure like bullet points or sections.

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 covers return fields and error behavior, but fails to explain pagination (page, page_size) or filtering (type, item). This leaves gaps for an agent to use the tool correctly.

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

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

Schema coverage is 0% and the description provides no explanation of the four parameters (item, page, type, page_size). The description only lists return fields, leaving parameter semantics entirely undocumented.

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

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

The description clearly specifies the tool returns an investment portfolio with explicit asset types (FIIs, stocks, ETFs, etc.) and data fields. It is distinct from sibling tools like openfinance_list_investment_transactions which focuses on 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?

The description implies usage for retrieving portfolio data but does not provide explicit guidance on when to use this tool over siblings, nor does it state conditions or exclusions.

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 (readOnlyHint, idempotentHint, destructiveHint) already indicate safe read operation. Description reinforces by saying 'Returns' and adds behavioral details about output fields and bulk execution, which is consistent and adds value.

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 paragraphs, front-loaded with main purpose and key details. Efficient, though some redundancy could be trimmed. No wasted sentences.

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?

Returns field details are well described. Usage orientation with sibling tool is provided. Pagination is not explained, but for a list endpoint with no output schema, it's fairly complete. Annotations cover safety.

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 description must compensate. It explains investment_id and investment_ids well, but misses page and page_size parameters. Partial coverage, helpful for key params but incomplete.

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 movement history for a specific investment position, listing transaction types. Distinguishes from siblings like openfinance_list_investments (returns investments) and openfinance_list_transactions (general 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 says 'Use after openfinance_list_investments to get the investment_id.' This provides a clear usage context. Bulk support mention also guides usage. No explicit when-not-to-use, but context is sufficient.

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

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

Adds behavioral details beyond annotations: sequential querying with rate-limit spacing and response format per connection. Annotations already indicate read-only and idempotent; description complements well.

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: first states purpose, second explains parameters and behavior. Front-loaded, no redundant text.

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 purpose, parameter usage, behavior, and response format. No output schema needed given simplicity; description is 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?

Schema only defines items as array of strings; description explains they are connection selectors (item_id, connector_id, or connector_name). With 0% schema coverage, description fully compensates.

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

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

Clearly states the tool lists loan contracts per bank connection, specifying the HTTP method and endpoint. Distinguishes from sibling 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?

Provides clear guidance on using the 'items' parameter to select specific connections or omit for all, and mentions sequential querying with rate-limit spacing. Lacks explicit 'when not to use' but context is strong.

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 explains credit card pending/posted variations by connector, search_queries behavior (case-insensitive OR, aggregation up to 5000), error return format instead of throwing, bulk support, and the token cost and coverage variance of detail modes.

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 quite long but well-structured, starting with general purpose, then credit card specifics, parameter details, error handling, and detail modes. Every sentence adds value, though some could be more concise. Still, it's organized effectively for a complex tool.

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 (credit card nuances, multiple detail levels, bulk, search, error handling) and no output schema, the description provides comprehensive context. It covers return structure, integration with sibling tools, and edge cases like connection health checks.

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 all parameters: from/to as ISO dates, pagination limits, detail enum with detailed definitions, account_ids for bulk, and search_queries with matching semantics and truncation handling.

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 transactions for bank and credit accounts, distinguishes credit card behavior, and contrasts with siblings like openfinance_list_credit_card_bills and openfinance_list_accounts. It specifies that for credit accounts this is the only way to get itemized 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?

The description provides explicit guidance on when to use this tool versus alternatives, such as using openfinance_list_credit_card_bills for standardized open-bill totals and openfinance_get_item_status for checking connection health. It also advises narrowing date ranges if truncated results are returned.

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 details beyond what annotations provide: 'On a connection with many transactions the scan caps at 5000/account and flags truncated:true', explains the compact vs raw summary behavior, and describes the effect of the `detail` parameter. 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 and well-structured, leading with purpose and usage, then parameter details. However, it is somewhat lengthy and could be trimmed slightly (e.g., repeating examples). Still, every sentence adds value, so it earns a 4.

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 (7 parameters, no output schema), the description thoroughly explains the return structure: total entradas/saídas, monthly evolution, top expenses/revenues, per-account breakdown, and optional raw rows with enrichment options. It also covers error flags like truncation. Complete for effective 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?

With 0% schema description coverage, the description fully explains all parameters: `item` accepts connector_id, connector_name, or item_id; `from`/`to` are ISO dates; `granularity` defaults to 'monthly' (compact summary) vs 'raw'; `detail` options (compact, rich, raw) and their impacts; `type` filters by BANK or CREDIT; `top_n` controls the number in top expenses/revenues. This compensates completely for the schema 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 clearly states it provides 'consolidated cash-flow analysis for a whole bank CONNECTION over a period, in ONE call' and distinguishes itself by resolving accounts internally, saving the agent from needing to call openfinance_list_accounts first. The purpose is specific and unique among 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 explicitly tells the agent when to use the tool (e.g., for 'fluxo de caixa', 'maiores gastos/recebimentos') and what not to do ('you do NOT need to call openfinance_list_accounts first'). It explains that omitting `item` analyzes all linked banks. While it does not explicitly state when not to use it, the guidance is strong.

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

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds valuable behavioral details about the output (global indicator, degraded components, incidents, your_banks_affected) without contradicting 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 main purpose stated upfront, followed by usage scenarios and return details. It is slightly long but every sentence adds value, earning a 4.

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 (differentiating provider vs. connection health) and lack of output schema, the description is complete: it covers when to use, what it returns, and how it affects the user's banks. No gaps in context.

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, so schema description coverage is 100%. The description adds context about what the tool does, but since there are no parameters to document, a baseline of 4 is appropriate.

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

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

The description clearly states the verb 'Checks' and the resource 'LIVE operational status of the Open Finance provider'. It distinguishes this tool from the sibling 'openfinance_get_item_status' by specifying that it checks the provider's health, not the user's connection.

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 use this tool: 'whenever data looks incomplete or stale even though a connection shows UPDATED'. It also explains what the tool reveals (upstream outage) and contrasts with reconnecting a connection, providing clear alternatives.

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

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

Annotations already indicate readOnly and idempotent. Description adds value by disclosing plan-based filtering (PF plan hides PJ banks) and that empty keywords returns a hint instead of full catalog, which are behavioral traits 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?

Description is a single paragraph that is clear and informative without excessive verbosity. Could be slightly more structured (e.g., bullet points) but overall concise.

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

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

Despite no output schema, the description thoroughly explains return fields (connector id, access, audience, linked connections, connect_url) and behavior (plan filtering). It covers essential information for an agent to use the tool correctly.

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

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

Schema coverage is 0%, but description adds meaning for 'keywords' (required, array of strings) and 'include_accounts' (triggers returning accounts). However, it does not fully compensate for lack of schema documentation, and there is a slight inconsistency with keywords being marked as required in description but not in 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 the tool searches bank connectors by name, returns details including a connect URL, and distinguishes from listing all connectors by emphasizing keyword search.

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

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

Explicitly instructs to call this tool BEFORE connecting to get a one-click link, providing clear context for when to use it. Does not explicitly mention alternatives but implies when not to use (not for dumping the whole catalog).

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 side effect (teaching Pluggy, creating Category Rules), batch behavior (per-item errors don't fail whole batch), and return format. Annotations are consistent (readOnlyHint=false).

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, but slightly verbose due to detailed side-effect explanation. All sentences are meaningful.

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 input, output, side effects, error handling, and data sources. No output schema exists, so description compensates fully. Complete for a batch mutation 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 no descriptions (0% coverage). Description adds full context: array structure, source of IDs, batch behavior, and side effect. This is high added value.

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

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

Clearly states verb 'Corrects' and resource 'category of one or more transactions' with HTTP method. Distinguishes from siblings by referencing openfinance_list_transactions and openfinance_list_categories for 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?

Explicitly tells when to use (fix miscategorized transactions), provides data source tools, and explains the side effect of creating Category Rules. 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 already indicate this is not read-only (readOnlyHint=false) and is idempotent (idempotentHint=true). The description adds that the conversation array should be included for reproduction, which is a usage detail rather than behavioral disclosure. It does not describe any side effects or required permissions 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, with no wasted words. The first sentence states the purpose, the second provides a crucial usage hint. It is appropriately sized 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 the tool has 3 parameters, no output schema, and annotations present, the description is somewhat minimal. It explains the purpose and gives one usage hint, but does not cover return values, error cases, or what happens after reporting. It is adequate but could be more comprehensive.

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 3 parameters with 0% documentation coverage. The description adds meaning for the 'conversation' parameter by specifying its purpose (include recent messages for reproduction). However, it does not clarify 'context' or 'message' beyond their schema definitions.

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

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

The description clearly states the tool's purpose: reporting bugs, missing features, or feedback. It uses specific verbs ('Report') and identifies the resource (bug/feature/feedback). Among the sibling tools, this is the only feedback tool, so it distinguishes itself well.

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 guidance on when to use this tool: to report bugs, missing features, or send feedback. It also gives a usage hint to include the conversation array. However, it does not explicitly state when not to use it or mention any alternative 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?

Annotations already indicate read-only, idempotent, non-destructive. Description adds that it reveals platform and adapter versions, which is useful context beyond annotations.

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

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

Single concise sentence, no waste.

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

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

For a zero-parameter, simple read tool, description fully covers behavior and output (version info). No output schema required.

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; schema coverage is 100%. Description adds no parameter-specific info, but none is needed.

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

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

Description clearly states it shows current MCP platform and adapter versions. Distinguishes well from siblings which are mostly financial 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?

No explicit when-to-use or alternatives, but for a simple version info tool the purpose is self-explanatory. Could be improved by noting it's useful for debugging or verifying setup.

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, idempotentHint, and destructiveHint. The description adds value by specifying the exact content of the return (MCPs, connection status, catalog tools), which is behavioral 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 concise sentence that is front-loaded with the main action and includes specific details. No unnecessary words.

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

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

Given zero parameters, full annotation coverage, and no output schema, the description sufficiently explains what is returned (installed MCPs, connection status, catalog tool counts). No missing information for this simple info tool.

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

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

No parameters exist; the input schema is empty with 100% coverage. The baseline for zero-parameter tools is 4, and description does not need to add param info.

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 function: returns current toolkit state including installed MCPs, their connection status, and catalog tool counts. The verb 'returns' and specific resource 'toolkit state' make the purpose unambiguous and distinct 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 implies usage for checking toolkit status, but does not explicitly state when to use this tool versus alternatives or provide any exclusions. No guidance on prerequisites or context.

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