Tiny (Olist Tiny)

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

Discloses important behaviors: browser login, permanent vs session-only connections, and no-args link generation. This complements the annotations (e.g., idempotentHint=true) without contradicting them, adding useful context beyond the structured metadata.

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 compact sentence that conveys multiple usage modes without excessive verbosity. The product context 'MCP.AI for IDE agents' adds minor background but does not waste space.

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

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

Given the simple schema (one optional string param) and no output schema, the description covers the core workflow effectively: login, token acquisition, and token usage. It omits only minor details like success/error responses, which are not essential for a straightforward authentication 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 description coverage is 0%, so the description carries the burden. It explains the optional 'token' parameter as a JWT obtained from browser login and clarifies the no-args case, giving meaning beyond the bare schema definition.

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

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

The description clearly states the tool's purpose: authenticating IDE agents via browser login and access token. It details the login flow and distinguishes itself from siblings like 'connect' and 'marketplace' by focusing specifically on authentication.

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

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

The description provides explicit usage scenarios: add token to config for permanent connection, paste token for session-only login, or call with no args to get the link. It does not mention alternative sibling tools, but the guidance is clear and practical.

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 cover read-only, idempotent, non-destructive behavior. The description adds value by disclosing conditional outcomes: `authenticated:true` with empty `pending[]` versus returning `connect_url` when credentials are missing. This goes beyond the annotation hints without contradicting them.

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

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

The description is two sentences with no filler. The first sentence front-loads the core purpose, and the second adds meaningful conditional detail about the two relevant states.

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 carries the burden of explaining return values, and it covers both main cases: all providers connected and credentials missing. It could elaborate on the meaning of `pending[]`, but the essentials are present for a simple status tool.

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

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

The tool has zero parameters, so the baseline of 4 applies. The description appropriately focuses on behavior and return values instead of parameter details, which is correct given the empty input 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 opens with a specific verb and object ('Returns connection status and URLs'), clearly identifying the tool's resource and output. It also implicitly distinguishes itself from sibling `authenticate` by describing a passive status check rather than an action.

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 conveys when the tool reports connected vs. missing-credential states, but does not explicitly say 'use this to check connection status' or contrast it with alternatives like `authenticate`. Usage is implied by the tool's purpose, but no explicit when/when-not guidance is provided.

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

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

The description adds significant behavioral context beyond annotations: invoke works even when MCP is not installed and runs one-off without bloating the toolkit; if credentials needed, invoke returns a connect link; if paid with empty wallet, returns checkout/top-up link and then retry. It also mentions installed_in_toolkit vs installed_in_workspace flags and permission requirements for writes. 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 (200+ words) but dense with useful information. It follows a logical structure: core flow, exceptions (invoke without install, links), permission requirements, and prompt library. Every sentence adds value, though it could be broken into bullets for easier parsing. It is not overly verbose for the tool's complexity.

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

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

Given the tool's complexity (14 actions, 23 params, two functional areas), the description is remarkably complete. It covers the core flow, edge cases (credentials, payment, not installed), permission scope, prompt library (search/get/publish with shareable links), and differentiates install vs invoke. It does not detail every action (like resume or cancel_reason), but the essentials are covered. Excellent for such a broad 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 23 parameters and 0% schema description coverage, the description must compensate. It explains the core parameters (action, mcp_id, tool_id, arguments) via the core flow, and mentions prompt-related params indirectly. However, it does not detail individual parameters like limit, query, immediate, tier_slug, cancel_reason, or prompt_vars. It provides high-level semantics for the main actions but not per-parameter detail, which is a moderate 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 the tool's role as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It explicitly covers capability requests like 'find an MCP that does X'. It also distinguishes from siblings by mentioning the prompt library and the core flow (search → describe → invoke). This is a specific verb+resource with clear scope and differentiation.

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: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', when to use list_tools, subscribe/cancel, report_bug, and request_mcp. It also explains the retry flow for connect/checkout links and states that writes require owner/admin. This is exemplary usage differentiation.

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

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

The description does not elaborate on side effects, idempotency, or safety beyond the annotations. It implies a reporting action but doesn't explain consequences or if repeated calls are problematic. Annotations cover some aspects, but the description adds minimal transparency.

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, concise and to the point. It avoids unnecessary verbosity while conveying the core purpose and a usage hint.

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

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

The description lacks details about expected input formats, the role of 'context', and any output or confirmation. It does not fully clarify what constitutes a valid report, leaving the agent with gaps in understanding.

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 description mentions 'conversation array' but the parameter is a string, causing ambiguity. It does not explain the 'context' parameter at all, and omits format or expected content for 'message'. Schema coverage is low.

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 sending feedback. It specifies the action (report) and the resource (bug/feature/feedback), making it 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?

It provides a hint to include the conversation array, but lacks explicit guidance on when to use this tool versus alternatives. No mention of prerequisites or situations that warrant its 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the specific output scope ('current versions'), but it does not disclose additional behavioral traits beyond what annotations already convey. No contradiction exists.

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, focused sentence with no redundant words. It conveys the entire purpose efficiently and is well-suited to such a simple 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 simplicity, empty parameter schema, and lack of output schema, the description fully covers what the tool returns (current versions). No additional context is necessary for an agent to invoke it 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?

This tool has zero parameters, and the schema coverage is 100%, so there are no parameter semantics to clarify. The description appropriately omits parameter details because none are 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 uses a specific verb ('Show') and a specific resource ('current MCP platform and adapter versions'). It clearly identifies the tool's function and differentiates it from sibling tools like authenticate or toolkit_info by focusing on version display.

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 usage context is implied: use this tool when you need to know the current platform or adapter versions. However, there is no explicit guidance about when not to use it or which alternative to choose, which would be more helpful given sibling tools like toolkit_info.

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

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

Annotations already signal a non-read-only, non-idempotent write operation, and the description's creation semantics align with them. It adds the endpoint and doc reference, but does not disclose details like duplicate handling, auth requirements, or expected response shape. 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 one compact, front-loaded sentence that states the action first, names the endpoint, summarizes common fields, and points to the official docs. Every element earns its place with no filler.

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

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

For a two-parameter create tool with no output schema, the description covers the main 'data' parameter and connects to official documentation. But it omits the meaning of 'account', any expected return value, and prerequisites, leaving moderate gaps for correct invocation and result interpretation.

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

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

Schema coverage is 0%, so the description must compensate. It explains that 'data' is a JSON string and lists common accepted fields (nome, tipoPessoa, cpf_cnpj, etc.), but leaves 'account' undefined and does not specify JSON encoding or required field combinations.

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

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

The description opens with 'Cadastra um contato' (registers a contact), giving a specific verb and resource. It clarifies the contact can be a client or supplier and names the underlying endpoint (contato.incluir.php), clearly distinguishing it from sibling get/list contact 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 creation purpose is implied by 'Cadastra' and the resource type, so the intended context is understandable. However, there is no explicit when/when-not guidance or reference to alternatives, and the optional 'account' parameter is not given any usage context.

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

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

Annotations already state readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds a note about bulk support via 'ids', which is useful. It does not mention errors, rate limits, or what happens on invalid ids, but given the annotations cover the main behavioral traits, this is acceptable.

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 short, two sentences, and front-loaded with the primary purpose. The bulk support note is concise and relevant. No fluff. It earns a high score for efficiency.

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

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

The tool has 3 parameters, one required, and no output schema. With annotations providing safety info, the description does not need to explain return values, but it should clarify the optional 'ids' and 'account' parameters. The current description only hints at bulk via 'ids', leaving 'account' unexplained. Given the simplicity of the operation (fetch by id), it is fairly complete, but the gap on parameters and no guidance on fallback or error handling suggests a slightly below-average score.

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

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

Schema description coverage is 0%, meaning the description does not explain any parameters. The schema itself defines 'id' and 'ids' (with anyOf types) and 'account', but the description only mentions 'id' and 'ids' indirectly via bulk support. The description adds minimal value beyond the schema: it doesn't explain that 'account' might be needed or what formats are expected. Since there is 0% coverage, the description should compensate, but it does not, so a low score is warranted.

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

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

The description states it retrieves a contact by id, which is a clear verb+resource. However, it does not explicitly distinguish from sibling tools like tiny_list_contacts (which lists contacts) or tiny_create_contact, though the 'Detalha um contato' (details a contact) implies a single-item fetch. It lacks a clear statement that this is for fetching a single contact vs a list, so it is adequate but not exemplary.

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

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

The description mentions bulk support for batched execution via 'ids', which gives some usage context. However, it does not provide explicit guidance on when to use this tool versus alternatives like tiny_list_contacts when you need multiple contacts, or tiny_get_contact for a single contact. No exclusions or alternative recommendations are given, so it's clear but minimal.

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, so safety is covered. The description adds the bulk execution capability, which is a behavioral trait beyond annotations. It doesn't describe return format or error handling, but given annotations, this is acceptable.

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 short sentences, front-loaded with purpose, then bulk support. Minimal 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 simple getter with safety annotations, the description covers purpose and bulk capability. However, it omits the account parameter and has no examples or return info. Given schema coverage 0%, it could be more 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 no descriptions, so the description must explain params. It explains 'id' and 'ids' but not 'account'. Thus it partially compensates for the lack of schema descriptions.

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

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

The description uses the verb 'Detalha' (details) and specifies the resource 'nota fiscal' (invoice) by id, clearly distinguishing from list_invoices which would retrieve multiple. The reference to the underlying script adds specificity.

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 mentions bulk support indicating when to use it for batch retrieval, but doesn't compare to list_invoices or state when not to use it. No explicit alternatives 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?

With annotations declaring readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the safety profile is already clear. The description adds the bulk execution capability, which is important behavioral info beyond the annotations. It doesn't mention return format, but given the read-only nature, that's acceptable.

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 concise: two sentences, front-loaded with the core action and endpoint, and a second line for bulk support. 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?

It's a simple read operation with no output schema, and the annotations cover safety. The description is sufficient for an agent to invoke it correctly: specify an id or ids. The `account` parameter is not mentioned, but it's likely optional context. Given the complexity, this is adequate.

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

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

Schema description coverage is 0%, so the description carries the burden. The description mentions `id` and bulk support via `ids`, which adds meaning to parameters beyond the schema. However, it doesn't explain `account` or the format of `id` (string/number), but the schema already shows types. Since the description says 'by id' and 'ids for batched execution', it covers the key parameters.

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

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

The description clearly states it details an order by `id`, and the mention of 'pedido.obter.php' ties it to a specific endpoint. It distinguishes itself from sibling tools like tiny_list_orders (which lists orders) by focusing on a single order detail. However, it doesn't explicitly contrast with other get_* tools (get_contact, get_invoice) but that's clear from the resource name.

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 mentions bulk support and refers to 'pedido.obter.php', which gives some context. It doesn't explicitly state when to use this over tiny_list_orders or other get_* tools, but the purpose is clear. No exclusions or alternatives are mentioned, so this is adequate but not explicit.

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?

Given the annotations already declare readOnlyHint and idempotentHint, the description adds value by disclosing the bulk support behavior (accepting an array of ids for batched execution) and referencing the underlying script. This is beyond what annotations provide, though it does not cover other aspects like auth or error handling.

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. The first sentence front-loads the core purpose, and the second adds the bulk capability. There is no fluff or redundant information, making it highly 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?

The description covers the main functionality (getting product details) and mentions batch support, but it leaves the 'account' parameter unexplained and does not describe the return format or any limitations. Given no output schema, this is a moderate gap, but the description is adequate for a simple read operation.

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

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

The input schema has zero description coverage, so the description must compensate. It explains the 'id' parameter (by id) and mentions 'ids' for bulk support, but does not explain the 'account' parameter. This partially compensates for the missing schema descriptions but is not comprehensive for all three parameters.

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

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

The description clearly states that the tool details a product by id, which is a specific verb+resource. It also mentions bulk support for multiple ids, adding scope. However, it does not explicitly differentiate from sibling tools like tiny_get_product_stock or tiny_list_products, so it is clear but not fully distinct.

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

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

The description implies usage for retrieving product details, but provides no explicit guidance on when to use this tool versus alternatives. It does not mention when not to use it, nor does it name any alternative tools. The context is implied but lacks exclusions or comparisons.

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 establish that the tool is read-only, idempotent, and non-destructive. The description adds the useful behavioral detail that bulk batches are supported via ids, but it does not disclose account handling, response format, or edge cases such as invalid IDs.

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 short and front-loaded, with the core purpose in the first sentence and batch support in the second. The parenthetical backend filename adds minor noise but does not significantly hurt clarity.

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

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

For a simple read-only stock lookup, the core semantics are present and annotations cover safety. However, the absence of an output schema and the unexplained 'account' parameter make the description not fully self-sufficient for 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?

With 0% schema description coverage, the description must compensate. It adds meaning for 'id' and 'ids', but the 'account' parameter is completely unexplained, so parameter coverage is only partial.

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 returning a product's stock balance by ID, which distinguishes it from siblings like tiny_get_product or tiny_get_order. However, it uses a noun phrase rather than an explicit action verb, and it does not explicitly call out sibling differentiation.

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

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

The description gives a clear context: retrieve stock for a product by id, and it mentions bulk execution via ids. It does not state when not to use this tool or explicitly compare it with sibling tools, so the usage guidance is implied rather than explicit.

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?

As anotações já informam que a operação é somente leitura, idempotente e não destrutiva, e a descrição agrega contexto útil ao revelar o escopo da instalação e o formato do retorno ('id, label'). Não há contradição com as anotações e há transparência suficiente para uma ferramenta simples.

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 descrição é uma frase curta e objetiva, começando pelo verbo de ação e cobrindo o recurso, o escopo e o retorno. Não há ruído, repetição ou informações desnecessárias.

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?

Para uma ferramenta simples e bem anotada, a descrição cobre propósito, escopo e retorno, mas não documenta o parâmetro opcional 'account' nem explica como os IDs retornados devem ser usados nas demais ferramentas tiny_*. Essa é uma lacuna relevante de contexto, embora o uso principal ainda seja compreensível.

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?

O input schema contém apenas 'account' como string opcional, sem descrição, e a cobertura de schema é 0%. A descrição da ferramenta não explica o papel, o formato ou o efeito desse parâmetro, e a menção a CNPJ não é claramente vinculada ao parâmetro. O agente não recebe informação suficiente para decidir como preenchê-lo.

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?

A descrição usa verbo específico ('Lista'), recurso claro ('empresas (CNPJ) Tiny conectadas a este install') e ainda indica o formato do retorno ('id, label'). Distingue-se bem das ferramentas irmãs tiny_list_* pelo recurso e pelo escopo de instalação.

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?

O contexto de uso é claro: listar as empresas já conectadas à instalação corrente. Não há exclusões explícitas nem comparação com alternativas como authenticate/connect ou demais tiny_list_*, mas o escopo apresentado é suficiente para orientar na maioria dos casos.

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, indicating safe read operation. The description adds that it is paginated and that filters accept specific fields (cpf_cnpj, situacao, idVendedor), which is useful context beyond annotations. No contradiction.

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

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

Description is concise (two sentences) and front-loaded with the primary action and pagination info. No waste, but could be more structured with parameter 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 the tool has 4 parameters, 0% schema coverage, no output schema, and no enum hints, the description is reasonably informative but incomplete. It covers key search and filter semantics but omits 'page' and 'account', and no return format is mentioned (though output schema is absent, so the description should at least hint at return behavior). The annotations mitigate some completeness needs.

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

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

Schema has 0% description coverage, so the description must compensate. It explains 'search' (search by name) and 'filters' (JSON with accepted fields), but 'page' and 'account' are left undocumented. The description adds meaning for two of four parameters, but the other two remain 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 the tool lists contacts with pagination, and the name 'tiny_list_contacts' is specific. It distinguishes from sibling tools like 'tiny_get_contact' by implying a list/search operation, but doesn't explicitly compare to 'tiny_get_contact' or other 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 implies usage for searching contacts by name or filters, but provides no guidance on when to use this tool versus alternatives like 'tiny_get_contact' for single contact retrieval. No explicit when-to-use or when-not-to-use scenarios are given.

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 this as read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds useful behavioral details about pagination and supported filter keys/date format, but does not discuss response behavior, limits, or error cases.

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 compact, front-loaded, and easy to scan. The internal endpoint reference, `notas.fiscais.pesquisa.php`, adds little value and slightly reduces clarity, but the overall structure is efficient.

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

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

For a simple read-only listing tool, the description provides enough to understand the basic use case: search invoices with pagination and filters. However, no output format is described, and effectively 3 of 4 parameters are not documented, leaving meaningful gaps for an agent that needs to construct calls reliably.

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 `filters` parameter well, including JSON keys and the DD/MM/AAAA date format, but leaves `search`, `account`, and even `page` semantics mostly undocumented beyond the implication of pagination.

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

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

The description clearly states that this tool searches invoices (notas fiscais), and mentions pagination and filter options. It is identifiable as a list/search tool, though it does not explicitly differentiate itself from tiny_get_invoice or other listing 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?

It conveys that the tool is used for paginated invoice searching with filters, which gives reasonable usage context. It does not explicitly state when to prefer this tool over tiny_get_invoice or other list/search alternatives.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral context by noting pagination and the JSON filters format, which goes beyond the structured annotations without contradicting them.

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

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

The description is a single front-loaded sentence followed by a compact filter detail. Every phrase adds value—endpoint, pagination, and filter semantics—without redundancy.

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

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

The tool has no output schema, but the description does not mention return shape, default page size, or account requirements. It provides enough for basic invocation but leaves gaps for a complete understanding of the response and optional params.

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

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

Schema description coverage is 0%, and the description compensates only for the 'filters' parameter by listing accepted keys and date format. Params 'page', 'search', and 'account' are left undocumented, so the compensation is 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 uses a specific verb ('Pesquisa') and resource ('pedidos de venda'), immediately identifying it as a sales-order search/list endpoint. The pagination note and filter details distinguish it from sibling tools like tiny_get_order, which retrieves a single order.

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 is given about when to choose this tool over alternatives such as tiny_get_order or tiny_list_invoices. The description implies use for searching paginated order lists but does not state exclusions or alternatives.

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

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

Annotations provide readOnlyHint=true and destructiveHint=false, so the description does not need to restate safety. The description adds that it is paginated and accepts filters with specific date formats and situation values. It does not disclose default page size, response structure, or potential side effects (if any), but given annotations cover the key safety traits, the added behavior is sufficient. No contradiction found.

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

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

The description is concise and front-loaded with the main purpose. It provides the key details in a few lines. The use of parenthetical code reference is a minor extra but doesn't bloat it. Every sentence adds value: purpose, pagination, filter details, and use case.

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 output schema and limited annotations, the description covers the main aspects: what it lists, pagination, and filter semantics. It even provides a use case (reconciliation with Banco MCP). It does not mention response format or default pagination parameters, but for a list tool with read-only permissions, this is adequate. The sibling tools are many but the description sufficiently distinguishes it as a payables list.

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 compensates for the key filter parameter by explaining its JSON structure and accepted values (dataInicial/dataFinal formats, situacao values). It also mentions other filter examples like nomeCliente. However, the other parameters (page, search, account) are not explained beyond their names, which is minimal. Overall, the description adds meaning beyond the schema, especially for the 'filters' 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 states it lists payables ('contas a pagar') and mentions pagination and locality to a PHP script. It clearly distinguishes from sibling tools like tiny_list_receivables and other list tools. However, it uses a specific code reference (contas.pagar.pesquisa.php) which may not be immediately helpful but does not harm clarity.

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

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

The description mentions use in reconciliation with the Banco MCP ('Pareia com o Banco MCP na conciliação'), which gives some context. However, it does not explicitly state when to use this tool over alternatives like tiny_list_invoices or tiny_list_receivables, nor does it provide exclusions or conditions. The guidance is implied but not explicit.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe read operation. The description adds that it is paginated, which is useful context beyond annotations. However, it does not disclose details like default page size, maximum page, or how to handle pagination responses, but moderate given the low complexity.

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 short and to the point, with one sentence covering the purpose and two key parameters. It is front-loaded with the core purpose. The use of backticks around parameter names is helpful. No wasteful language.

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?

This is a paginated list tool with no output schema, so the description needs to explain pagination behavior and return format. It mentions pagination but provides no details on how to request a page or what the response looks like. It also lacks information on optional parameters like 'account', which could be critical for multi-account setups. The description is incomplete for a tool with zero schema coverage and 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?

Schema description coverage is 0%, meaning the description must explain parameters. It mentions 'search' for name/code and 'filters' (JSON) for status/category, but does not explain 'page' or 'account' parameters. The description adds some semantic value to search and filters but omits half of the parameters, so it does not fully compensate for the 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?

The description clearly states the tool lists products via a specific PHP endpoint, emphasizes pagination, and hints at search/filter capabilities, which distinguishes it from sibling list tools (e.g., tiny_list_orders for orders). It doesn't explicitly mention 'products' as the resource in a structured way, but the context is 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?

The description implies usage for searching products by name/code and filtering by status/category, which provides context for when to use this tool. However, it lacks explicit 'when not to use' guidance or alternatives, such as when to use tiny_get_product for a single product or tiny_list_orders for orders.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context about pagination and filter capabilities, but does not disclose response format, default page size, or auth requirements. 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 concise and front-loads the core action ('Lista contas a receber'), followed by pagination and filter details. The reference to the internal PHP filename adds minor noise but does not seriously hurt readability, and there is no wasted content overall.

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 four optional parameters and no output schema, the description should clarify more of the parameter semantics and pagination behavior. It does mention pagination and the most important filter keys, but lacks details about `page`, `search`, `account`, and the returned data shape. Adequate for a basic list tool but with clear 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 input schema has 0% description coverage, so the description is the only place parameter meaning is explained. It provides partial semantics for the `filters` parameter (dataInicial/dataFinal, situacao, nomeCliente) but leaves `page`, `search`, and `account` completely unexplained, and the filter list is incomplete ('etc.'). This only partially compensates for the lack of schema descriptions.

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

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

The description clearly states the tool lists accounts receivable (contas a receber), identifies the underlying endpoint, and notes pagination support. It does not explicitly differentiate itself from sibling tools like tiny_list_payables or tiny_list_invoices, but the resource name is specific enough to convey purpose.

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

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

The description implies when to use the tool by mentioning it lists receivables with optional filters such as date range, status, and client name, but it provides no explicit guidance on when to prefer this over sibling list tools or when not to use it. Usage context is present but not directive.

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 behavior details beyond the annotations: pagination and that the 'search' parameter filters by name. This complements the readOnly/idempotent annotations well, though it does not describe output format or other potential side effects.

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, using only two short sentences. It avoids redundancy and clearly conveys the core purpose without unnecessary words.

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

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

Given the tool's simplicity as a list operation, the description is incomplete. It omits details about pagination behavior, the meaning of 'account' and 'filters', and the expected response structure. The minimal info provided is not enough for a user to fully understand how to use the tool effectively.

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 of four parameters ('search') is explained (searches by name). The parameters 'page', 'account', and 'filters' have no description in the schema or the description. With 0% schema coverage, 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 that the tool searches sellers ('Pesquisa vendedores') and provides the underlying function name. This is specific and distinct from sibling list tools for other resources (e.g., accounts, contacts).

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 given on when to use this tool versus alternatives. It does not mention criteria like 'use for seller searches' or distinguish it from other list tools beyond the resource name. For a tool with many siblings, this is insufficient.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds value by specifying what information is returned (installed MCPs, statuses, accounts, catalog counts), giving more behavioral detail beyond the annotations. 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, well-structured sentence that immediately states the tool's purpose and enumerates the returned data. No extraneous words, front-loaded with the core action, and easy to parse.

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 covers the necessary context by listing the types of information returned. It adequately informs the agent of what to expect, though it does not specify the exact format or structure of the response. Still, it is sufficient for a simple read-only state inspection.

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

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

The tool has zero parameters, so the baseline score is 4. The description does not need to elaborate on parameters, and the purpose is self-contained. It effectively communicates what the tool returns without any parameter explanations.

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

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

The description clearly states the tool returns the current toolkit state, listing specific components (installed MCPs, connection status, accounts, catalog tool counts). It distinguishes itself from sibling tools like show_version or connect by focusing on overall state rather than version or actions.

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 contrast with alternatives or state when not to use it. However, the context is evident from the tool's purpose and the sibling list, so it provides clear context without explicit exclusions.

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