Prefeitura GO Aparecida de Goiânia: Certidão Negativa de Débitos

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the description adds value by explaining the permanent vs session behaviors and that token is optional. It doesn't disclose exact return formats but covers the main behavioral facets 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?

Three sentences, each carries unique value: context and action, best practice, and alternative usage. No redundancy or fluff, front-loaded with the core 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?

For an authentication tool, it covers both primary flows (permanent and session), explains the token parameter, and lacks only explicit return values which are less critical here. The complexity is adequately addressed.

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 a single string parameter with 0% description coverage. The description fully compensates by explaining the token is a JWT, optional, and how its presence/absence changes behavior (get link vs set session).

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

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

The description clearly states this is an authentication tool for IDE agents, specifying the action (log in, copy access token) and distinguishes from siblings like connect or marketplace by focusing on credential exchange and token management.

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

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

Provides explicit usage context: best practice (permanent config header) and alternative (session-only token), plus guidance on calling with no args to get a login link. Clear recommendations 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 declare readOnlyHint=true and idempotentHint=true, but the description adds valuable specifics: exact return values for two connection states (authenticated:true with empty pending[] vs. connect_url for toolkit and per-install). This goes beyond annotations without contradicting them.

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

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

The description is exactly two sentences, front-loaded with the core function, and adds precise conditional behavior without fluff. 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 no output schema, the description explains return values for the two primary scenarios. It doesn't cover edge cases like partial connections or errors, but for a simple status-check tool with no parameters, it provides sufficient context. A bit more on potential partial states would push it to 5.

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 schema covers everything. The baseline for 0 parameters is 4, and the description does not need to add parameter details. No loss of value here.

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 function: returns connection status and URLs, with specific behavioral details for different states. It distinguishes from siblings like 'authenticate' by focusing on status retrieval rather than initiation.

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 (to check connection status) and what it returns, though it does not explicitly mention alternatives or exclusions. Given the presence of sibling 'authenticate', a direct comparison would strengthen this, but the context is clear enough.

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

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

Adds substantial behavior beyond annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=true). Discloses that invoke runs one-off without installing or bloating the tool list, returns connect/checkout links when auth or payment is missing (with a retry protocol), requires workspace owner/admin for writes, and flags installed_in_toolkit vs installed_in_workspace in search results. No contradiction with annotations; write behavior aligns with readOnlyHint=false.

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

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

The description is a dense single wall of text — likely 400+ words — covering two domains (MCP marketplace and prompt library) with no bullets, headers, or scannable structure. Some length is warranted for a 14-action dispatcher, and it is front-loaded with the primary flow, but the prompt-library tail and billing details run together and would benefit from structural separation.

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 enormous complexity (23 params, 14 actions, no output schema, 0% param coverage), the description carries a heavy burden. It covers the primary consumption path end-to-end (discover → describe → invoke), auth/payment edge cases, installed-status flags, and the install-vs-invoke decision. Secondary flows (subscribe/cancel billing, request_mcp, the prompt-library trio) get only thin treatment — enough for basic use but not complete for a tool this rich.

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 across 23 parameters, the description must compensate, and it does only partially. It maps the core flow params well: action (all 14 values), mcp_id, tool_id, and arguments (via 'pick the right tool_id → invoke RUNS that tool'). However, limit, query, immediate, tier_slug, message, conversation, cancel_reason/comment, report_context, request_*, and the entire prompt_* family receive no semantic explanation — a significant gap for the prompt-library and billing flows.

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 opening sentence is airtight: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It identifies a specific resource (marketplace) with clear verbs (search, describe, invoke, install), covers the capability-request phrasing, and internally differentiates all 14 actions in its 'action' enum. Distinct from siblings like toolkit_info and report_bug.

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 an explicit core flow (search → describe → invoke) and decisive when/when-not guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT in the active toolkit.' Also explains billing actions and the retry-after-connect/checkout-link pattern. It stops short of explicitly naming sibling alternatives to route around, but the internal action-selection tree is thorough.

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 already indicating read-only/idempotent, description adds that it is hosted by the platform, requires prepaid credit, and involves non-confidential data under LGPD. 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?

Four sentences, front-loaded with purpose, then operational and legal context. Somewhat verbose but each sentence adds relevant information; could be streamlined but is acceptable.

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 and description does not explain return values. Parameter semantics are underdeveloped, and it does not clarify whether CPF, CNPJ, or either is needed. Covers cost/legal aspects but misses functional details.

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 2 parameters (cpf, cnpj) with no descriptions and 0% coverage. The description does not explain their format, purpose, or required combination, so it fails to compensate 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?

Clearly states it queries a Certidão Negativa de Débitos from Prefeitura de Aparecida de Goiânia from official sources. The verb 'consultar' and specific resource distinguish it from unrelated sibling tools.

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

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

Provides practical context: no platform credentials needed, pay-per-query with prepaid credit, and data is non-confidential. Does not explicitly mention exclusions, but siblings are unrelated so no confusion.

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 readOnlyHint=false, destructiveHint=false, so the action is clearly a non-read, non-destructive operation. The description adds the behavioral context of including the conversation for reproduction, which is useful but does not explain side effects or response behavior. No contradiction is present.

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 sentence with no filler. It front-loads the purpose and gives the key usage tip in one concise line.

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 no output schema, the description covers the essential purpose and the noteworthy conversation hint, but lacks explicit parameter explanations and any indication of the workflow or result. It is sufficient for basic use but leaves gaps for full usability.

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 only explains the 'conversation' parameter ('recent messages for reproduction'), while 'message' and 'context' are left undefined. Users cannot infer what 'context' is or how the 'message' content should be structured, leaving ambiguity.

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

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

The description clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('Report') and resource ('bug, missing feature, or feedback'), which distinguishes it well from the unrelated sibling tools (e.g., authenticate, connect).

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

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

The description implies usage when reporting an issue but provides no explicit guidance on when to prefer this tool over alternatives or when not to use it. It gives a small hint ('Include the conversation array...') but lacks any exclusion or context comparing to other tools.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool's safety profile is covered. The description adds that it shows versions but doesn't detail return format or side effects, which is fine given 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?

A single, succinct sentence that fully conveys the purpose without any fluff. It is appropriately front-loaded and every word contributes to meaning.

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 adequately covers the purpose for a simple read-only tool with annotations indicating safety and idempotency. It does not detail return format, but that is likely obvious from the tool name and low complexity.

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

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

There are no parameters (schema coverage 100% with zero parameters). The description adds no parameter information needed beyond the schema, which is complete. Baseline for zero params is 4.

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

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

The description clearly states the tool shows current MCP platform and adapter versions, specifying the verb and resource. It distinguishes from siblings like authenticate, connect, and toolkit_info, 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 implies when to use the tool—to check version information—but does not explicitly discuss alternatives or exclusions. Since no sibling covers version info, the context is clear enough, though not exhaustive.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safe read-only nature is covered. The description adds useful detail about what state is returned but no additional behavioral caveats such as freshness, error cases, or prerequisites. 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 a single, front-loaded sentence with no filler. Every component—installed MCPs, connection status, accounts, catalog tool counts—earns its place and directly supports agent decision-making.

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

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

For a zero-parameter, read-only, idempotent introspection tool, the description is fully adequate. It names the key output categories, and the annotations cover safety and side-effect behavior, so the agent has enough context to select and invoke the tool correctly.

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

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

The tool has zero parameters and an empty input schema, so the baseline of 4 applies. The description correctly focuses on return content rather than parameter syntax, which is unnecessary here.

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

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

The description uses a specific verb ('Returns') and precisely identifies the resource ('current toolkit state'), enumerating the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like show_version or connect.

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

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

The description clearly establishes that this tool is for inspecting overall toolkit state, but it does not explicitly state when not to use it or name alternatives such as show_version for version-only information. Context is clear, yet exclusions are absent.

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