Enel RJ: Download

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

It discloses the key behavioral aspects: the tool can return a login link, accept a pasted JWT, and that session-only login expires. Annotations already indicate idempotent and non-read-only, so the description adds value by explaining the session vs. permanent header distinction. It doesn't cover failure modes or token validity, but the primary side effects are 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?

The description is clear but somewhat meandering, combining a product intro ('MCP.AI for IDE agents'), instructions for the user, and commands for the agent in a single block. It's under 80 words and mostly front-loaded, but it could be better organized into a short 'how to use' list. Overall, adequate but not as crisp as it could be.

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 two input modes, no output schema, and auth implications, the description covers both invocation patterns (no-arg and token), the meaning of the return (link vs. success), and the distinction from persistent configuration. It omits details like response format or expiration, but these are less fundamental for an agent to invoke the tool correctly. The guidance is sufficiently 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 input schema has one optional token parameter with no description (0% schema coverage). The description explicitly defines its meaning: pass {"token": "<jwt>"} after the user pastes it, or omit the argument to receive the login link. This fully compensates for the bare schema, giving the agent exact usage instructions for both modes.

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 an MCP.AI server in IDE agents, explaining the login flow (browser, token paste, session). It distinguishes itself from siblings through its action-focused phrasing ('log in', 'access token'), though it doesn't explicitly name a sibling alternative. The resource is specific: the MCP.AI server connection.

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-call guidance: with no args to get the login link and with a token to complete authentication. It also contrasts with a configuration-based approach for permanent access, which helps the agent choose between a one-time session and a persistent setup. It doesn't mention sibling tools but effectively clarifies when to use this tool vs. a configuration change.

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 meaningfully extends the readOnlyHint=true and idempotentHint=true annotations by revealing a state-dependent contract: 'authenticated:true' with empty 'pending[]' when all providers connected, vs. per-install URLs when credentials are missing. This documents return-shape variance beyond what annotations convey.

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 crisp, well-constructed sentences. Pasted together: one defines what's returned, the second explains the state-conditional branch ('When all providers are connected... When credentials are missing...'). The description front-loads the core purpose and conveys a conditional contract with zero fluff.

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

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

For a parameterless read-only status/health-check tool, this fully captures the contract: the two possible states, the exact field names the agent can expect, and the ordering of fields ('connect_url' for the toolkit and per-install URLs). Clearly addresses operational context.

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 schema coverage is trivially 100% (empty properties). With no parameters to document, the description isn't burdened with explaining inputs. The baseline 4 applies here since there's truly nothing to compensate for.

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

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

Description uses a specific verb+resource ('Returns connection status and URLs') and clearly explains the tool's scope. It could earn a 5 with explicit sibling differentiation (e.g., vs. 'toolkit_info' or 'authenticate'), but the behavior is clearly defined.

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?

Reading between the lines, an agent would know to call this when checking connection state, but there's no explicit 'when to use vs. alternatives' guidance. The sibling tools (authenticate, toolkit_info, show_version) suggest related but distinct purposes, and the description doesn't clarify when to pick 'connect' over '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 declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, destructiveHint=false. The description adds context about data privacy (LGPD), client responsibility, and that data is public/non-confidential, which is complementary. It does not contradict annotations. However, it doesn't specify rate limits or what 'download' precisely returns.

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

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

The description is a single, dense paragraph that efficiently packs in purpose, business model, legal/ethical context, and data source. It could be more scannable with bullets, but it remains concise for the amount of context conveyed.

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 read-only, idempotent query tool with annotations, the description covers legal (LGPD), commercial (prepaid), and operational (platform-hosted) context. However, it's unclear whether 'Download' means it downloads a file or returns data; this ambiguity, combined with zero parameter semantics, leaves some 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% — the description does not explain any of the 4 parameters (empresa, instalacao, login_email, login_senha). While the login credentials are somewhat self-evident, 'empresa' and 'instalacao' are domain-specific and unexplained. The description adds no parameter-level semantics.

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 performs a download/consultation ('Download, consulta em fonte oficial') for Enel RJ (energy utility in Rio de Janeiro). It explains it's a paid, prepaid-credit query from official Brazilian sources. However, the name is in Portuguese and somewhat cryptic, and the description could more explicitly distinguish it from sibling tools, though it implies a clear 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 provides context on when to use (for querying official Brazilian sources, not confidential data) and constraints (prepaid credits, no credentials). However, it does not explicitly contrast with sibling tools like 'authenticate' or 'connect', so the usage guidelines are 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?

Surfaces critical runtime behaviors beyond annotations: invoke works even if the MCP is not installed, returns a connect link when credentials are needed, and returns a checkout/top-up link when the wallet is empty. It also discloses that writes (install/uninstall/subscribe/cancel and one-off install behind invoke) require workspace owner/admin. These details go well beyond the mere readOnlyHint/openWorldHint/destructiveHint flags, enabling the agent to anticipate side effects and auth failures.

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 the tool has 14 actions and significant auth/edge-case semantics, so the length is mostly earned. It is front-loaded with the core identity, then flows into action logic and prompt library. A more structured bulleted format would improve scannability, but the density is justified and there is 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?

Despite no output schema and thin annotations, the description covers all major workflows: discovering MCPs, running one-off invokes, handling credential/payment interruptions, permanent installation, workspace auth requirements, prompt library usage, and the fallback request_mcp path. It tells the agent exactly what to expect and how to retry, making the tool self-contained for the common cases.

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 carries the full burden and does so well by explaining the action enum values (search/describe/invoke/list_tools/request_mcp/prompt actions) and interpreting key params like tool_id ('you pick the right tool_id'), arguments (passed to invoke), and prompt_vars (filled in get_prompt). It does not explicitly describe every optional parameter (limit, immediate, tier_slug, cancel_reason, etc.), but the workflow narratives make the main parameter relationships clear.

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

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

The description opens with 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', immediately stating the tool's central purpose. It clearly differentiates marketplace from siblings by enumerating its unique capabilities (search/describe/invoke/install/prompt library) and positions it as the hub for discovering and executing MCPs, rather than a single-purpose tool.

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

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

Provides explicit selection guidance: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', and 'request_mcp asks us to build a NEW MCP when nothing fits'. It also explains the core flow (search→describe→invoke) and when to use list_tools, giving the agent clear decision rules for when to choose this tool and which action within it.

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 the behavioral detail that conversation messages should be included for reproduction, which helps the agent understand expected input. Annotations already provided readOnlyHint=false and destructiveHint=false, so the description does not need to restate those. No contradiction; it is additive, though it stops short of describing side effects like sending a report to maintainers.

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

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

The description is concise, front-loaded with the tool's purpose and follows with a short reproduction instruction. Both sentences create value, and there is no repetition of parameter/schema 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 simplicity of the tool and annotations, this is a minimum viable description: it communicates the basic action and one key input instruction. However, it does not mention what the tool returns, how to format 'context' or 'conversation', or whether any confirmation of the report will be given, which leave understandable gaps without an 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?

The schema has 0% description coverage, so the description must compensate, but it only explains the 'conversation' parameter ('include the conversation array'). The required 'message' parameter and the optional 'context' parameter are not explicitly defined. The phrase 'conversation array' also conflicts slightly with the schema's type (string), suggesting a JSON string serialization that is not stated.

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 has a clear, specific verb ('Report') and object ('a bug, missing feature, or send feedback'), making the tool's purpose immediately obvious. It also inherently distinguishes itself from siblings like 'connect' or 'show_version' by naming its unique reporting/feedback function.

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: for reporting bugs, missing features, or feedback. It also gives a reproduction guidance ('include the conversation array with recent messages'), which is useful for the AI to invoke it correctly. It does not explicitly state when not to use it or name alternatives, but no sibling overlaps with this functionality.

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, idempotentHint=true, destructiveHint=false, which already declare the safety profile. The description adds that it provides version information, which is consistent with annotations. It doesn't add much behavioral detail beyond the annotations, but given annotations cover safety, the description is adequate. No contradiction; it reinforces the read-only nature.

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, concise sentence that perfectly captures the tool's purpose without any fluff. It is front-loaded and 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?

Given the simplicity (0 parameters, no output schema), the description is complete. It clearly states what it does, and with annotations covering safety and idempotency, the description is sufficient for an agent to know when to use it.

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 baseline is 4. The description appropriately mentions that it shows versions, which is sufficient for a parameterless tool. No additional parameter information is needed.

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

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

The description clearly states the tool's function: showing the current MCP platform and adapter versions. It uses a specific verb ('Show') and identifies the resource (platform and adapter versions), distinguishing it from sibling tools like 'marketplace' or 'toolkit_info'. However, it could be more explicit about the distinction from 'toolkit_info' which might also display version-like information, but the description is clear enough for a version-specific query.

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 this tool (when you need to check the current versions of the platform and adapters). It doesn't explicitly mention alternatives or when not to use it, but given the sibling tools, it's distinct enough. No explicit guidance on context is provided, leaving the agent to infer from the purpose.

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 well covered. The description adds value by specifying exactly what the state contains and signals that the result is a live/current snapshot, which is useful behavioral context beyond the annotations.

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

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

Single, tightly worded sentence that front-loads the action and then lists the key data elements without redundancy. Every clause earns its place and the structure makes the tool's purpose immediately scannable.

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 no output schema, the description supplies sufficient selection and invocation context. It names all major data categories returned and, combined with the annotations, fully characterizes the tool's behavior.

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, so there are no parameter semantics to clarify. Per the baseline for parameter-less tools, the description does not need to compensate for schema gaps and includes all relevant information.

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

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

Description uses a specific verb ('Returns') with an explicit object ('current toolkit state') and enumerates the state components: installed MCPs, connection status, accounts, and catalog-tool counts. This clearly distinguishes it from siblings like connect, authenticate, and 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?

The description clearly establishes the tool's context: use it when you need an overview of toolkit state, installed MCPs, connection statuses, or connected accounts. It does not explicitly mention alternatives, but for a read-only informational tool this is a clear context with no exclusions needed.

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