Conselho Regional de Farmácia SP: Cadastro

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

Annotations already cover idempotency and non-destructiveness, but the description adds valuable behavioral context: the session-only vs permanent auth distinction and how the token flow works. It does not contradict annotations, though it omits details about error responses or expired tokens.

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

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

The description is front-loaded with the core purpose and then explains the two call modes in a compact paragraph. It could be slightly cleaner (minor duplicated 'in in'), but every sentence contributes useful information.

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

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

For a simple one-parameter authentication tool with no output schema, the description is complete: it covers both invocation modes, the permanence tradeoff, and the config-header alternative. An agent would know exactly how to initiate and complete authentication.

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

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

With 0% schema coverage, the description fully compensates by explaining that the optional 'token' is a JWT pasted by the user, that passing it creates a session-only login, and that omitting it returns the auth link. This is precise parameter semantics beyond the bare string type.

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 authenticates to MCP.AI for IDE agents, specifying both the browser-login flow and token handoff. It goes beyond a simple verb by explaining the two call modes, making the purpose unambiguous even among siblings like '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?

It gives explicit, actionable guidance: call with no args to get a login link, or call with a token after the user pastes it. It also recommends the permanent config-header alternative, making the when and how very clear.

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

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

The description goes beyond the annotations by detailing the conditional behavior (authenticated with empty pending vs. missing credentials with connect_url), giving a clear picture of what the tool does.

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 (three sentences) and straightforward, with no unnecessary details or 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?

Without an output schema, the description fully explains the return value in different scenarios, covering both possible outcomes and the relevant URLs, making it complete for a status-check 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?

There are no parameters, so the schema is fully covered. The description adds no parameter-specific information, which is acceptable given the empty parameter list; baseline score of 3 is appropriate.

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

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

The description clearly states the tool returns connection status and URLs, and distinguishes it from sibling tools like authenticate by focusing on status checking.

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 explains the different output states (authenticated vs. missing credentials) which provides context for when to use it, but does not explicitly contrast with alternative tools like authenticate.

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 annotations (readOnly, idempotent, non-destructive), the description adds meaningful behavioral details: it's a paid service with credit-based billing, no credentials needed, and it queries non-confidential official data with LGPD compliance responsibilities placed on the client. This enhances 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 somewhat run-on and mixes multiple aspects (hosting, billing, data source, legal responsibility) in a single block. It is not overly long but could be better structured for clarity. It avoids redundancy but lacks clear logical 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?

The description omits essential details such as what the output looks like, the exact meaning of the input parameter, and any expected response format. Given the tool's simplicity, this lack of completeness could hinder correct usage, especially for a paid service.

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 one required parameter 'inscricao' but the description does not explain what this value represents or how it should be formatted. With 0% schema description coverage and no explanation in the description, the parameter semantics are essentially undefined.

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 indicates this is a query tool for official pharmacy registry data ('consulta em fonte oficial'). It distinguishes itself from siblings like authentication or marketplace tools by specifying its function as a data consultation service.

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 usage context: it's hosted on the platform, requires no platform credentials, and is pay-per-query with prepaid credits. However, it does not explicitly explain when to choose this over other query tools or contrast with alternatives, so guidance is partial.

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 are minimal (readOnlyHint false, openWorldHint true, etc.), so the description carries the burden. It discloses that writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also explains that invoke runs a tool without installing it, and that it may return connect or checkout links. It describes the prompt library's behavior. This adds context beyond annotations and does not contradict them, though it could be even more specific about side effects of uninstall/cancel.

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 large paragraph that packs a lot of information. It front-loads the main purpose but then covers core flow, invoke specifics, install usage, permissions, and the prompt library all in one block. It is logically ordered but not broken into sections, making it dense and harder to scan. Some redundancy exists (e.g., repeated emphasis on 'one-off') but it's not overly verbose given the complexity. It is acceptable but not optimally structured.

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

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

Given the tool's complexity (14 distinct actions, 23 params, no output schema), the description is remarkably complete. It explains the primary workflows (search → describe → invoke), the distinction between permanent and one-off usage, permission requirements, error recovery (connect/checkout links), and the separate prompt library system. However, it omits details on some actions like 'resume' and doesn't describe return formats for most actions, though it does mention a few. Overall, it provides a strong contextual framework but has minor coverage 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?

With 23 parameters and 0% schema description coverage, the description must compensate. It does explain core parameters like action, mcp_id, tool_id, arguments, and mentions prompt-related fields (prompt_slug, prompt_vars) in passing, but many parameters (limit, conversation, immediate, tier_slug, cancel_reason, prompt_targets, etc.) are not described. The description provides a high-level flow but falls short of covering all parameter semantics, especially for the many action-specific fields.

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 is the official mcp.ai marketplace catalog and the way to run MCPs. It specifies the resource (marketplace) and the main actions (search, describe, invoke), and it implicitly distinguishes from sibling tools like crf_sp_cadastro_consultar by defining its role as the universal catalog and execution layer. The purpose is explicit and not tautological.

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 explicit guidance on when to use invoke vs install ('prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT'), when to use search/describe, and how to handle error cases like missing credentials ('invoke returns a connect link') or empty wallet ('invoke returns a checkout/top-up link, then you retry'). It also clarifies the role of search_prompts, get_prompt, publish_prompt, and billing actions. This is a textbook example of when-to-use vs 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=false, idempotentHint=true, and destructiveHint=false. The description adds some behavioral context by mentioning the conversation array for reproduction, implying data is sent, but doesn't elaborate on side effects or response behavior. This adds modest value beyond annotations.

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

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

Two sentences, front-loaded with purpose, no filler. Every word earns its place.

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

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

The tool is simple with 3 parameters and no output schema. The description covers the core usage but leaves ambiguity around 'context' and 'message' semantics, and doesn't mention what happens after reporting (e.g., response or acknowledgment). Adequate 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?

Schema description coverage is 0% – property descriptions are absent. The description only hints at 'conversation array' but does not explain the 'message' (required) or 'context' parameters. It fails to compensate for the lack of schema-level documentation.

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

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

The description clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This is a specific verb-resource combination that distinguishes it from unrelated siblings like authenticate, marketplace, or show_version.

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 context on when to use it (for bugs, features, feedback) and instructs to include the conversation array for reproduction. While it doesn't explicitly mention alternatives or when not to use, none are needed given the distinct sibling 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, covering the safety profile. The description adds the meaningful detail of WHAT versions are reported ('MCP platform and adapter versions'), which goes beyond a generic 'get version' by scoping the output domain. For such a trivial read-only tool, there is little else to disclose, so this is appropriately transparent.

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?

Nine words, one sentence, front-loaded with the action verb 'Show.' Every word earns its place, and there is zero fluff or redundancy. This is a model of how a trivial tool should be described.

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 the tool's scope given its trivial nature with no parameters and clear annotations. The only minor gap is the absence of any mention of the return format, which would matter since no output schema exists to infer from. Still, for a version-inspection tool, this is more than 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?

With zero parameters, the baseline is 4, and there is nothing for the description to document. The description focuses correctly on the output domain rather than inputs. The schema coverage is effectively 100% (vacuously), so no parameter documentation gap exists.

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' with a clear resource: 'the current MCP platform and adapter versions.' This precisely differentiates the tool from siblings like authenticate, connect, and toolkit_info by specifying exactly which versions are reported. The intent is unambiguous even to an agent unfamiliar with the codebase.

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 is implied from the description rather than explicitly stated; there's no explicit 'when to use' or mention of alternatives. However, for a zero-parameter version-inspection tool, the use case is self-evident from the verb 'Show' and the specific resource described, bringing it to the 'implied usage' tier.

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, openWorldHint=false, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds content specifics (what state includes) but does not disclose any additional behavioral traits such as potential latency, caching, or error conditions. With annotations covering the basics, the description provides moderate added value.

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

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

A single concise sentence that immediately states the purpose and lists the key return contents. Zero fluff, fully front-loaded.

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

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

For a zero-parameter read-only info tool with robust annotations (readOnly, idempotent, non-destructive), the description fully covers what the tool does and what information it provides. No missing details; complete for its purpose.

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)Skip the schema baseline for 0 params is 4. The description correctly implies no inputs are needed. No additional parameter explanation required.

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

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

The description uses a specific verb ('Returns') and identifies the resource ('current toolkit state') with detailed enumeration of what is returned (installed MCPs, connection status, accounts, catalog tools). It clearly distinguishes from siblings like connect or authenticate, which focus on actions, not state inspection.

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 makes clear this is an introspection tool for checking toolkit state, which is distinct from the action-oriented siblings. It does not explicitly state when not to use it or name alternatives, but the purpose is self-evident enough for an agent to infer appropriate usage.

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