Prefeitura SP São Paulo: Dívida Ativa

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

The description adds useful behavioral context beyond the annotations: it explains that calling with no args returns a link, and that pasting a token creates a session-only login. This complements the idempotentHint annotation by implying that multiple calls are safe. It does not discuss side effects or errors, but covers the essential behavior.

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 three sentences long and packs in all necessary details without excessive verbosity. It could be structured with bullet points for readability, but it remains focused and front-loaded with the key action ('log in in the browser'). The redundancy of 'paste it here' and 'after the user pastes' is minor.

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 a single optional parameter and no output schema, the description covers the main usage scenarios (permanent config, session-only, and retrieving the link). It does not describe error handling or return values, but given the simplicity and the presence of sibling tools like 'connect', it is sufficiently complete 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?

With schema coverage at 0%, the description carries the full burden and delivers: it explains the 'token' parameter expects a JWT and describes the no-argument call behavior. This goes well beyond the bare schema, which only lists a string property without context. The semantic value added is high.

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 handles authentication for IDE agents, with a specific verb ('log in') and resource (the MCP server's access token). It explains the primary flow and two modes, but it does not explicitly contrast with the sibling tool 'connect', so it falls short of a 5.

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 each mode: permanent config-based token vs session-only paste, and when to call with no args. However, it does not mention any alternatives or exclusions (e.g., when NOT to use this tool), so it's not a full 5.

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, and the description adds valuable context about the specific response structure—authenticated flag, pending array, and connect URLs—beyond what annotations provide. 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, front-loaded with the main verb and resource, and every clause adds value. No redundancy, ideal length for 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?

The description fully explains all possible outcomes (authenticated true vs. missing credentials) and provides the return fields. Given the absence of an output schema, this is sufficient and complete.

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

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

The tool has zero parameters, so schema coverage is complete. The description adds no parameter details, but none are needed; baseline 4 is appropriate for a no-parameter tool.

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: it returns connection status and URLs. It distinguishes itself from siblings like authenticate or show_version by focusing on connectivity state and provider connection 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?

The description implies usage for checking whether all providers are connected, detailing the two outcomes. It lacks explicit when-not-to-use or mention of alternative tools, but the context is clear enough for a simple status check.

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 the minimal annotations, the description discloses important behaviors: write actions require workspace owner/admin, invoke runs uninstalled MCPs one-off without bloating the toolkit, and invoke returns connect or checkout/top-up links when credentials or payment are needed. It does not contradict the annotations, though it doesn't describe exact side effects for every action like resume.

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 a one-sentence definition and the core flow, and each subsequent sentence adds meaningful guidance about running, installing, permissions, links, and the prompt library. It is dense and somewhat run-on, but no section is 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 complex 14-action, 23-parameter tool with no output schema, the description is unusually thorough: it covers discovery, profiling, one-off execution, permanent install, billing, permissions, and prompt publishing. Minor gaps such as the unexplained resume action and the unclarified immediate/conversation parameters keep it just short of 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?

With 0% schema description coverage, the description carries a lot of the parameter burden and largely succeeds: it explains the central action discriminator and the main parameter families (mcp_id/tool_id/arguments, prompt_* fields, cancel_*/request_* fields). However, several parameters remain unexplained, including immediate, resume, limit, and conversation, leaving gaps across the 23-parameter surface.

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 its role explicitly: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It distinguishes the catalog/execution flow from the prompt-library side and names the action families, making it clear how this broad tool differs from narrower siblings like report_bug and toolkit_info.

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 an explicit core flow: search discovers MCPs, describe returns a profile, and invoke runs the chosen tool. It also states when to prefer invoke over install ('prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT'), when to use request_mcp, and when list_tools is relevant.

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, idempotentHint=true, destructiveHint=false. The description adds genuine value beyond these: the cost model (pay per query with prepaid credit), the auth model (no platform credentials needed), the data classification (same data available to citizens, not confidential), and LGPD compliance responsibilities. This is meaningful operational context annotations cannot express.

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

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

The description is a single paragraph of four sentences that front-loads purpose in the first clause, followed by economic, legal, and compliance context. It's reasonably brief, but it mixes multiple concerns (pricing, authorization, data classification, LGPD compliance) without structure, making it harder to parse than necessary. The LGPD sentence adds legal boilerplate that could be condensed.

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, no enums, and 0% schema parameter coverage, the description carries the full explanatory burden but leaves major gaps: what the 'sql' parameter accepts, how 'placa' relates to the debt query, what response format to expect, and any rate limits. The compliance, pricing, and data-nature context is genuinely helpful, but the missing parameter and return-value semantics make this tool hazardous to invoke blindly.

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?

Two parameters ('sql' and 'placa') exist with 0% schema description coverage, and the description provides zero parameter information. The ambiguous 'sql' parameter name (suggesting arbitrary query capability) is completely unexplained, and 'placa' only hints at vehicle license plates. With no schema fallback and no description compensation, an agent cannot reliably construct a valid request.

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 verb ('consulta' - query) and resource ('Dívida Ativa da Prefeitura de SP' - SP City Hall Active Debt in an official source). It naturally differentiates from system-level siblings (authenticate, connect, marketplace) by naming the specific government database queried. However, it never explains what a query returns or how the named parameters relate to the stated purpose, keeping it from a 5.

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 useful operational context: no platform credentials needed, pay-per-query with prepaid credit, queries only citizen-available official data (not confidential). This implicitly conveys when to use (to access public Brazilian government data at cost) but provides no explicit when-to-use vs. when-not-to-use instructions or named alternatives. The usage guidance is conveyed implicitly through the cost and data-classification details.

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

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

Annotations already indicate this is a non-read-only, non-destructive, idempotent operation. The description adds some useful behavioral context by saying the conversation array is needed for reproduction, but it does not disclose response behavior, external submission details, or whether duplicate reports are deduplicated. No contradiction with annotations is apparent.

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 sentences. The first sentence captures the purpose, and the second provides the key usage instruction. There is no filler or redundant 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 bug-reporting tool, the description conveys the main purpose and one important parameter behavior, but it omits details about the message/context parameters and expected output or confirmation. It is adequate for basic invocation but not fully self-contained.

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 only clarifies the 'conversation' parameter as an array of recent messages for reproduction, but the schema types it as a string, and it says nothing about 'message' or 'context' semantics. This is insufficient for full parameter understanding.

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 and resource: "Report a bug, missing feature, or send feedback." It clearly states what the tool does and is easily distinguished from the sibling tools, none of which are feedback- or bug-oriented.

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 clear context for when to use the tool: whenever a bug, missing feature, or feedback needs to be submitted. It also provides a concrete instruction to include the conversation array. However, it doesn't explicitly state when not to use it or mention alternatives, though none of the siblings are relevant.

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 minimal extra context (only that it shows versions) and does not contradict annotations. It could mention that it is a quick diagnostic or that it returns version strings, but it adds enough for a simple read-only tool.

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, clear, and front-loaded sentence: 'Show the current MCP platform and adapter versions.' No wasted words, appropriately concise for a simple utility 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 trivial nature (no parameters, no output schema), the description is sufficient. It communicates the exact information returned (platform and adapter versions). A slightly more detailed note about the exact format or fields could bump it to 5, but it is complete enough.

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 zero parameters and 100% schema coverage (vacuously), the description does not need to explain parameters. The baseline for 0 params is 4, and the description adds no param-related details because none exist. It does not introduce confusion.

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: 'Show the current MCP platform and adapter versions.' It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), and it is distinct from sibling tools like authenticate, connect, and report_bug, which serve different functions.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of scenarios where this would be appropriate (e.g., checking version compatibility) or exclusions, which is a gap for a tool that could be confused with toolkit_info if not clarified.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds value by detailing the contents of the returned state (installed MCPs, status, accounts, counts), which is beyond what annotations provide. No contradictions exist.

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, front-loaded sentence with no filler. Every phrase contributes meaning, making it efficient and easy to scan.

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 and a simple state-returning operation, the description fully covers the returned data and confirms it is read-only. It is complete for the tool's simplicity and annotation coverage.

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 is 4. The description does not need to explain any schema details, and it clearly defines the output content without referencing 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 begins with 'Returns the current toolkit state' and enumerates specific components (installed MCPs, connection status, accounts, catalog tool count). This clearly distinguishes it from sibling tools like authenticate or show_version by naming the exact resource and output.

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 no guidance on when to use this tool versus alternatives. It does not state prerequisites, common use cases, or exclusions, leaving the agent to infer usage from the purpose alone.

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