Santander MCP

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

The description adds behavioral context beyond annotations: it discloses token handling, session lifetime (permanent vs session), and the effect of calling with no args. It aligns with idempotentHint=true and doesn't contradict annotations. Could mention failure scenarios.

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

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

The description is a single dense paragraph that front-loads the purpose and covers key usage points. It's concise but could benefit from structured bullet points for clarity. 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 (1 optional param, no output schema), the description covers the primary use cases (permanent config, session token, link generation). It lacks error handling or return value details, but these are less critical for an auth tool.

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

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

With 0% schema description coverage, the description fully compensates by explaining the token parameter (JWT, used for token paste) and the behavior when no args are provided (returns a link). This adds significant 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 defines the tool as the authentication mechanism, explaining the login process (browser login, token copy, permanent config vs session token). It effectively distinguishes from sibling tools by being the only auth-related tool, providing a specific verb and resource.

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

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

The description provides explicit guidance on usage: it recommends adding the token to config for permanent connection or pasting it for session-only login, and explains how to call with or without arguments. It doesn't specify when not to use, but no alternative auth tool exists 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 mark the tool as read-only and idempotent. The description adds value by explaining the response semantics for different connection states, providing behavioral 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?

Two sentences with no wasted words. The first sentence states the core function, the second explains conditional behavior. Well structured 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?

For a simple status tool with no parameters and no output schema, the description adequately covers the return behavior in two key scenarios. It is sufficient for an agent to use correctly, though the exact response format could be slightly more detailed.

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 the input schema coverage is 100%. The description does not need to add parameter info; 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 specifies the tool returns connection status and URLs, and distinguishes itself from sibling tools like 'authenticate' by describing conditional behavior. The verb 'Returns' is precise and the resource is a 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?

The description provides clear context on when to use the tool (checking connection status) and what to expect in two scenarios (all connected vs missing credentials). Although it does not explicitly mention alternatives or when not to use, the sibling toolset implies the distinction.

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

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

The description goes beyond annotations by detailing behaviors: invoke works one-off without installing MCP, returns connect/checkout links, install makes permanent, writes require admin. It explains the openWorldHint by stating it can run external MCPs. 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 front-loaded with the most critical info. Every sentence adds value, though some redundancy exists. Could be slightly more concise, but remains well-structured.

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

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

For a tool with 15 parameters and no schema descriptions, the description is remarkably complete. It covers discovery, invocation, installation, billing, permissions, and edge cases like missing credentials or empty wallet.

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?

Although schema coverage is 0%, the description adds meaning by explaining how key parameters (action, query, mcp_id, tool_id, arguments) are used in the workflow. Not every parameter is detailed, but the overall logic is clear.

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

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

The description clearly states the tool is 'THE official mcp.ai marketplace' for discovering and running MCPs/tools. It distinguishes itself from sibling tools which are specific actions (e.g., openfinance_*, report_bug, toolkit_info) by being the central hub for managing MCPs.

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 advises using this tool FIRST for any capability, before external registries. It outlines the core flow (search → describe → invoke) and explains when to use invoke vs install, including handling of credentials and billing. It also notes that write actions 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?

Annotations indicate destructiveHint=true, and the description adds valuable context: the data will no longer be available and a re-connection URL is returned. This goes 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?

Two sentences with no waste, front-loaded with the main purpose. Every word 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?

For a simple tool with one parameter and no output schema, the description covers the main effects well but lacks parameter clarity. The annotations help, but the missing parameter description is a minor gap.

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 and the description does not explain the 'item' parameter. The term 'specific bank' hints at its role, but it is insufficient for a tool with one unannotated 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 verb 'revokes' and specifies the resource 'Open Finance consent for a specific bank' and the action 'deletes the connection data'. It distinguishes from sibling tools like openfinance_list_connections by focusing on disconnection.

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

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

The description implies when to use the tool (to disconnect and remove data) but does not explicitly state when not to use it or provide alternatives. The context is clear but lacks exclusion 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?

Describes waits up to 60s, polling behavior, return structure including timed_out and needs_action. Annotations (readOnlyHint=false, destructiveHint=false) are consistent; description adds significant behavioral 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?

Front-loaded with key action and critical details. Slightly verbose but every sentence adds value. Could trim minor redundancies, but overall well-structured.

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

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

Despite no output schema, description details return fields (results, errors, status, executionStatus, lastUpdatedAt, synced, needs_action, timed_out). Covers edge cases and behavior comprehensively for a complex sync tool.

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

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

With 0% schema coverage, the description fully compensates. It explains items accepts item_id, connector_id, or connector_name, and that omitting items syncs all. Explains wait=false for fire-and-forget.

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

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

The description clearly states the tool forces a bank to re-sync connections and waits for completion. It distinguishes from siblings like openfinance_get_item_status by specifying polling behavior and mentions alternatives like fire-and-forget with wait=false.

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 guidance: use when a balance or transaction list looks stale. Provides when-not: 'needs_action' means user must reconnect. Also explains how to sync all banks by omitting items, and mentions wait=false for fire-and-forget.

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

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

Beyond annotations (readOnlyHint, idempotentHint), the description details degradation behavior, warning structures instead of errors, and response shape. This adds substantial behavioral context not captured in structured fields.

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, front-loaded with purpose, and every sentence adds value. No redundant or vague phrasing.

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 low complexity (single parameter, no output schema) and rich annotations, the description covers behavior, error handling, and response format adequately. Nothing essential is missing.

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 adds the array length constraint (1–50) and implies account_ids identify the accounts. However, it does not explain id format or provide more semantic meaning beyond what the schema offers.

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 real-time balance per account id, referencing the specific endpoint and input format (array of account_ids 1–50). It is distinct from sibling tools like list_accounts or get_accounts_detail, which serve different purposes.

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 expect degraded responses (e.g., financial institution unavailable) and special handling for CREDIT accounts, providing usage context. However, it does not explicitly contrast with alternatives like list_accounts or get_accounts_detail to guide selection.

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. Description adds important behavioral context about provider_incident block causing unreliable limits/balances, and describes batch result 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?

Concise, front-loaded with core purpose, followed by important usage details and warning. Every sentence adds value with no redundancy.

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

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

Given simple input and no output schema, description covers core behavior, batch shape, and exceptional condition (provider_incident). Could be considered complete for a read-only 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 only 1 parameter with 0% description coverage. Description adds meaningful constraint: array of strings, size 1-50. This compensates for missing schema descriptions.

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

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

Description clearly states it returns full account objects including extended creditData per ID, and distinguishes itself from sibling tool openfinance_list_accounts which likely returns a list without full details.

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?

Describes when to use: pass account_ids as an array (1-50). Warns about provider_incident affecting reliability. Does not explicitly state when not to use, 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?

Discloses batch shape, Pluggy's lack of paid/status field, payment semantics in Brazilian Open Finance, and not to reconstruct totals by billId. Adds significant context beyond readOnlyHint 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?

Somewhat long but every sentence is useful. Could be slightly more concise, but structure is clear and front-loaded with purpose.

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

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

Very comprehensive for a tool without output schema; covers return shape, limitations, payment semantics, cross-tool relationships, and warnings.

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

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

Only one parameter (bill_ids) with 0% schema coverage; description clarifies it's an array and advises to use list tool first to discover ids. Adds meaning 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?

Clearly states it returns bill-level detail (financeCharges, payments) by id, distinguishes from openfinance_list_transactions and 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?

Explicitly says when to use vs. alternative tools, provides prerequisite (discover ids via list), and warns about payments meaning and paid status caveats.

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 the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral details: it returns executionStatus and connector metadata, and describes the return format for both modes ({count, items} for all, or detailed status for a single bank). This adds value beyond the annotations.

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

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

The description is extremely concise, consisting of two sentences that front-load the main purpose and then explain the parameter behavior. Every word is informative, with no redundancy or extraneous content.

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

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

For a simple tool with a single optional parameter and no output schema, the description fully covers the necessary behavior: what it returns, the two usage modes, and the parameter effect. An agent can correctly invoke it in either mode without ambiguity.

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

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

The schema has only one optional string parameter 'item' with no description (0% coverage). The description compensates by explaining that omitting it returns status for all linked banks and passing it returns status for a single bank, thus adding clear 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 it returns the current status of a bank connection and lists example statuses. It distinguishes between two modes: omitting 'item' for all linked banks or passing 'item' for a single bank, making its purpose specific and differentiating it from sibling tools like openfinance_list_connections.

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

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

The description provides explicit guidance on when to omit or include the 'item' parameter, indicating context for batch vs. single retrieval. However, it does not explicitly state when not to use this tool or mention alternatives, though the sibling tools list provides implicit 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=true, idempotentHint=true, destructiveHint=false. Description adds value by detailing response shape ({ results, errors }) and parameter constraints, but doesn't mention rate limits or auth.

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?

Front-loaded with purpose and endpoint, lists many fields but is information-dense. Could be slightly more concise, but 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?

No output schema, but description explains batch response shape and lists key fields. Lacks exact structure of results object, but adequate for a read tool with clear annotations.

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 description compensates by explaining the only parameter (loan_ids) as an array of strings with size limit 1-50. Provides meaning beyond schema structure.

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

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

The description clearly states it returns full loan contract detail by ID, listing many specific fields. It distinguishes from sibling 'openfinance_list_loans' by advising use after listing for deep-dive.

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_loans to deep-dive on a specific contract.' Also specifies array size limit (1-50) and batch response shape, providing clear context for when to use.

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 declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, which the description does not contradict. The description adds valuable behavioral context: the meaning of credit balance is connector-dependent, the open billing cycle is defined by specific fields, and a provider_incident block may appear with unreliable data. This goes 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 moderately long but well-structured: it opens with the main purpose, then provides usage guidance with explicit parameter behavior, and ends with caveats about balance interpretation and provider incidents. Every sentence adds value, though it could be slightly more concise by removing redundant 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 only 2 optional parameters, no output schema, and moderate complexity (account types, bank data, credit data, incidents), the description covers all necessary aspects: return types, field meanings, parameter behavior, balance caveats, and incident handling. It is comprehensive for an agent to use correctly.

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

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

Schema description coverage is 0%, so the description must compensate. It explains the usage of `item` (omit for all banks, pass for single) and `type` implicitly through BANK and CREDIT mentions, but does not provide explicit parameter descriptions. The description adds meaning by describing how each parameter affects the response, but lacks structured explanation.

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

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

The description clearly states the tool returns accounts for bank connections, distinguishing between BANK and CREDIT types with specific data fields. It specifies the verb 'returns' and the resource 'accounts for a bank connection', and differentiates from siblings like openfinance_list_credit_card_bills by noting it provides balance, number, type, etc., versus that tool's standardized billing amounts.

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

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

The description provides explicit guidance on when to use the tool: 'OMIT `item` to list accounts across ALL linked banks at once' and 'Pass `item` to target a single bank.' It also warns against treating credit balance as the month's bill and directs users to openfinance_list_credit_card_bills for standardized open-bill amounts. This covers both inclusion and exclusion criteria.

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

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds valuable context: cached for session, single aggregated response, no batch 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?

Two sentences: first states main purpose and caching, second describes response structure. Every sentence earns its place. No wasted words.

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

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

For a tool with no output schema, the description explains all key return fields (id, description, translated, parent). Notes caching behavior. Complete given simplicity.

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

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

No parameters, so baseline 4. Description adds details about response fields (id, description, etc.), which is helpful 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?

Description clearly states it returns Pluggy's transaction category taxonomy, cached for the session. Specifies the API endpoint and differentiates from sibling tools by being the only category-listing tool.

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

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

Mentions caching (implying infrequent use) and that category ID is used by openfinance_update_transaction_category, guiding when to call this before updating. No explicit when-not, but sufficient for a simple read-only tool.

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

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

Annotations already declare readOnlyHint and idempotentHint, so the description adds value by specifying the returned fields and the add_connection_url, giving agents concrete expectations beyond the 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?

Single sentence, factual, no redundancy. Every word conveys necessary information.

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

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

No output schema, but the description lists key fields returned. This is adequate for a listing tool, though a mention of array output could 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?

No parameters exist (schema coverage 100%), so baseline is 4. The description correctly adds no parameter info since 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, add_connection_url). This distinguishes it from siblings that perform other operations like connect or sync.

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

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

No explicit guidance on when to use versus alternatives. The purpose is implied (listing connections), but no exclusions or comparisons are given, leaving the agent to infer from 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 provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds extensive behavioral context: payment_status derivation logic, cycle date handling, connector asymmetry, warnings for bill_grouping_reliability and missing CREDIT_CARDS product. 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 very long and dense, mixing multiple concepts in a single paragraph. It lacks clear sectioning or bullet points. Important details like payment_status logic and connector asymmetry are buried, reducing readability. Not concise despite being informative.

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 the lack of output schema and parameter descriptions, the description covers a wide range of important behavioral details (payment_status derivation, open_bill opt-in, connector asymmetry, warnings) making it fairly complete for the tool's complexity. Minor gaps in parameter documentation slightly reduce 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?

Input schema has 5 parameters with 0% schema description coverage, so the description must compensate. It explains include_open_bill and account_ids (bulk) but omits descriptions for page, page_size, and account_id. Given the high schema coverage gap, this is insufficient.

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 a CREDIT-type account with specific fields (dueDate, totalAmount, etc.). It distinguishes from sibling tools like openfinance_list_transactions and openfinance_get_credit_card_bill, and uses a specific verb 'Returns' and resource 'closed 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?

Explicit guidance on when to use this tool vs alternatives: use openfinance_list_transactions for itemized charges, opt-in for open_bill, avoid summing transactions by billId. It also explains connector asymmetry and when to fall back to bank app. Provides clear 'IMPORTANT' and 'ALWAYS' directives.

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 discloses that the tool returns a specific error-like response (with total, results, warning) instead of throwing on errors. Annotations already provide readOnlyHint and idempotentHint, which align. 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 main purpose and enumerates asset types concisely. It includes error behavior in a compact way. Slightly long but well-structured.

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

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

Given no output schema, the description covers return structure and error handling. However, it lacks parameter explanations and does not mention pagination mechanics (page, page_size). For a tool with 4 optional parameters, this is incomplete.

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. However, it only lists result fields and does not explain the 4 input parameters (item, page, type, page_size) or how they filter/control pagination. This is a significant gap.

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

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

The description clearly states it returns the investment portfolio for a connection, listing specific asset types like FIIs, stocks, ETFs, etc. It uses a specific verb 'returns' and resource 'investment portfolio', which distinguishes it from sibling tools like openfinance_list_investment_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 indicates when to use (connections with INVESTMENTS product enabled) and what happens otherwise (returns a safe response with warning). It implies context but does not explicitly mention alternatives like openfinance_list_investment_transactions for transactions.

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 destructiveHint=false. The description adds value by detailing return fields (expenses, brokerage details) and bulk execution support, which goes beyond what annotations provide.

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

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

The description is two concise paragraphs, front-loading the main purpose and return structure, with no superfluous words. 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 no output schema, the description lists many return fields, providing sufficient detail. It fails to mention pagination behavior for page/page_size, but the overall completeness is high for a list tool with annotations.

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 investment_id (use after list_investments) and investment_ids (bulk support), but does not describe the page or page_size parameters, leaving their semantics unclear.

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 movement history for a specific investment position, listing transaction types like BUY/SELL/TAX. It distinguishes itself from siblings by specifying investment context and referencing openfinance_list_investments for sequential use.

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 provides clear context by advising to use after openfinance_list_investments and mentions bulk support with investment_ids. However, it does not explicitly state when not to use this tool versus alternatives like openfinance_list_transactions.

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 critical behavioral details: sequential querying for multiple connections, rate-limit spacing, and return format `{ results, errors }` per connection. 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 a single efficient paragraph with no redundant words. It front-loads the main action 'Lists loan contracts per bank connection' and adds details in a logical order. Every sentence earns its place.

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

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

Given the complexity of multiple connections and rate limiting, the description fully covers usage, behavior, and return format. No output schema exists, but the description explains the response structure. All necessary information is provided without gaps.

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

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

The schema only defines `items` as an array of strings with 0% coverage. The description compensates fully by specifying the format: each element must be a connection selector (item_id uuid, connector_id, or connector_name). 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 the tool lists loan contracts per bank connection using GET /loans, distinguishing it from sibling tools like openfinance_list_accounts and openfinance_list_transactions. The verb 'list' and resource 'loan contracts per bank connection' are specific.

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 the `items` parameter (specific connections) vs omit it (all banks), and explains sequential querying with rate-limit spacing. This helps the agent choose the 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?

Beyond annotations (readOnlyHint, idempotentHint), the description discloses critical behaviors: auto-pagination up to 5000 with truncation, search aggregation limits, per-connector variations for CREDIT pending/posted, provider_incident block, error handling returning a structured object, and detail levels affecting token usage. 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 lengthy but well-structured and front-loaded with purpose. Every paragraph adds value, covering credit card specifics, filters, pagination, error handling, detail options, and troubleshooting. While concise for the complexity, it could be slightly trimmed without losing clarity, but remains highly effective.

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

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

Given the tool's complexity (8 parameters, no output schema), the description is exceptionally complete. It describes the response shape (account echo, transactions, provider_incident), error conditions, bulk support, detail levels, and cross-references sibling tools for further context. Everything an agent needs to select and use the tool correctly is covered.

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 each parameter in detail: from/to as ISO dates, search_queries for substring match, page and page_size for pagination (including default behavior), detail levels and their added fields, and the account_id/account_ids for bulk. It also provides usage nuances like the 5000-aggregation for search.

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

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

The description clearly states it returns transactions for bank accounts (BANK or CREDIT type) and distinguishes from sibling tools by specifying that for CREDIT accounts it is the only way to get itemized transactions. It also highlights the relationship to openfinance_list_credit_card_bills for bill totals, making the purpose and scope unambiguous.

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

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

The description provides explicit guidance on when to use this tool versus alternatives, such as using openfinance_list_credit_card_bills for total debt, avoiding summing transactions by billId, and checking connection health when total is 0 for CREDIT accounts. It also explains when to use openfinance_list_accounts for statement dates. Additionally, it clarifies pagination options and search behavior.

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 behavior. The description adds valuable context: transaction scan caps at 5000/account with truncation flag, provider incident block, and behavior when item is omitted. 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 and front-loaded with the core purpose. Every sentence adds value, though some grouping of related details could improve conciseness slightly.

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 (compact summary fields, raw rows, truncation, provider_incident). It covers behavior for different granularities and filters, making it complete for an agent to invoke correctly.

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

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

Schema description coverage is 0%, but the description fully compensates by explaining all parameters: item accepts multiple identifier formats, from/to are ISO dates, granularity and detail defaults and effects, type filter, and top_n implicit in top categories. This exceeds baseline of 3.

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 performs consolidated cash-flow analysis for a bank connection, resolving accounts internally. This differentiates it from sibling tools like openfinance_list_transactions (per-account) and openfinance_list_accounts (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 provides explicit use cases ('análise anual/mensal', 'fluxo de caixa') and notes that calling openfinance_list_accounts first is unnecessary. However, it does not explicitly mention when not to use this tool or name alternatives for different 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 mark the tool as read-only and idempotent. The description adds detailed behavioral information: returns a global indicator, degraded components, open incidents, and flags incidents affecting connected banks. It discloses the full scope of output 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 relatively long but well-structured: it front-loads the main purpose, then gives usage guidance, then return details. Every sentence adds value, though it could be slightly more concise. Still, it earns a 4 for being informative without fluff.

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

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

Given no parameters and no output schema, the description completely covers what the tool does, when to use it, and what it returns. It also distinguishes from a sibling tool, making it fully self-contained for correct agent 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?

The input schema has zero parameters, so schema coverage is 100%. The description does not need to explain parameters, and it adds no unnecessary detail. Baseline for 0 params is 4, and this is appropriately scored.

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 identifies the tool as checking the LIVE operational status of the Open Finance provider, distinguishing it from the sibling `openfinance_get_item_status`. It specifies the resource (provider health) and action (check), making the purpose unmistakable.

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 the tool: when data looks incomplete or stale despite an UPDATED connection. It explains how it helps differentiate provider-side problems from connection issues, effectively setting usage context and implying 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 (readOnlyHint, idempotentHint), the description details return fields, caveats for non-Open-Finance connectors, plan-based filtering, and that it never dumps the full catalog. No contradictions with annotations.

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

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

The description is dense but each sentence provides value. Could be slightly more concise, but overall well-structured with front-loaded purpose.

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

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

Despite no output schema and 0% parameter schema coverage, the description covers all relevant behaviors, return fields, and edge cases (caveat, plan filtering). Complete for an agent to invoke correctly.

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

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

With 0% schema coverage, description fully compensates: explains keywords[] (mandatory, example given) and include_accounts (adds accounts to results). Both parameters are semantically clear.

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

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

The description clearly states the tool searches bank connectors by name and lists specific returned fields. It distinguishes itself from siblings like 'connect' and 'marketplace' by emphasizing its role as a pre-connect lookup.

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 'Call this BEFORE connecting' and explains when to prefer Open Finance connectors. Also notes that keywords[] is required and returns a hint otherwise, preventing misuse.

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

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

The description goes far beyond annotations by explaining the side effect of creating a Category Rule for future similar transactions and detailing the batch error handling behavior. This provides critical context for an AI agent.

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 is information-dense, covering purpose, usage, side effects, and return format. Every sentence adds unique value, though it could be slightly more structured.

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

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

Given the tool's complexity (batch update with side effects), the description covers input requirements, behavioral implications, and output structure (including per-item error handling). No output schema exists, but the description explicitly provides the return format.

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 effectively explains the items parameter structure and the origin of transaction_id and category_id from sibling tools, compensating for the lack of schema documentation.

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 one or more transactions' using a specific HTTP method and resource path. It distinguishes itself from sibling list tools 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 specifies when to use the tool (to fix miscategorized transactions) and provides clear instructions on how to construct the items array using IDs from two other tools. However, it does not explicitly state when not to use it or mention 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 indicate idempotentHint=true, readOnlyHint=false, destructiveHint=false, which the description does not contradict. The description adds no additional behavioral details like side effects or storage, but given annotations, it provides minimal extra 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?

The description is a single sentence that includes purpose and a key usage hint. It is front-loaded and contains no unnecessary words, earning its place efficiently.

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 bug-report tool with no output schema, the description covers the basic purpose and a key parameter. It lacks details on expected outcome, confirmation, or how the report is processed, leaving some gaps but minimally 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 coverage is 0%, so description must compensate. It mentions the conversation parameter and its purpose, but does not explain the message or context parameters. The param names are somewhat self-explanatory, so the description adds partial 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?

The description clearly states the tool is for reporting bugs, missing features, or feedback, using a specific verb and resource. It distinguishes itself from sibling tools like openfinance operations, as this is the only tool for general feedback.

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 advises including the conversation array for reproduction, which gives clear context on tool usage. It does not explicitly mention when not to use or alternatives, but siblings are all financial, making the use case obvious.

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=true, idempotentHint=true, destructiveHint=false. Description adds that it returns 'current MCP 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 sentence with no wasted words. Verb 'Show' is front-loaded. Highly 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 sufficiently explains the return value ('current MCP platform and adapter versions'). Low complexity (0 params) means no further context needed.

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

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

No parameters, so baseline 4 per rubric. Description adds no parameter info, but none needed.

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

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

Description clearly states verb 'Show' and specific resources 'MCP platform and adapter versions'. Distinguishes well from sibling tools, which are mostly about openfinance operations, authentication, etc.

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

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

No explicit when-to-use guidance, but context makes it obvious: it's a simple version check. No alternative version tool exists among siblings, so usage is implicitly 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 provide readOnlyHint, idempotentHint, destructiveHint. Description adds specific return content details (installed MCPs, connection status, catalog counts) 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 sentence, no unnecessary words. Front-loaded with purpose and scope.

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 enumerates the three key pieces of returned data. Sufficient for a simple informational 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; baseline 4 as per rubric since 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 explicitly states it returns toolkit state: installed MCPs, connection status, and catalog tool counts. Verb 'Returns' plus specific resource items makes purpose very clear.

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

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

Implied usage as a state introspection tool, but no explicit guidance on when to use vs alternatives or when not to use.

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