Codex Imagem

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

The description discloses important behavioral traits: the permanence of the config-based approach versus the session-only nature of passing a token, and the fact that calling with no args returns a link. This goes beyond the annotations (readOnlyHint=false, idempotentHint=true) by explaining the side effects of each usage mode, though it does not explicitly mention side effects like logging out or token expiration.

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 verbose but well-organized with 'Best:' and 'Or' to separate the two modes. It contains minor redundancy (e.g., 'log in in the browser') but overall conveys essential information without excessive fluff. It could be trimmed slightly but remains clear and readable.

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, the description explains the expected behavior: it returns a link when called with no args, and likely completes authentication when a token is provided. It gives enough context for an agent to understand the tool's functionality and prerequisites, though it doesn't explicitly state the return value for the token-based call.

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 only parameter 'token' is explained in the description: it is used for session-only login when passed. The description clarifies that the token is a JWT and how it differs from the config approach. Although the schema has no description, the tool description fully compensates.

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 explains the tool's purpose: authentication for IDE agents. It details the login flow, token acquisition, and two modes of usage (permanent via config header, session via token). This is distinct from sibling tools like image generation or subscription, leaving no ambiguity.

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 explicitly provides two usage scenarios: 'Best: add it to this server's config...' for permanent connection, and 'Or paste it here...' for session-only login. It also mentions calling with no args to get the login link. This gives clear, actionable guidance on when and how to invoke the tool.

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?

Extends beyond annotations with meaningful details: quota usage, timing, output link, storage in Files tab, and dimension limitation. No contradiction with annotations; annotations are generic while this adds specific behavioral context.

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 concise sentences, front-loaded with the core action resins. Efficiently packs quota, timing, output, and constraint without 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?

No output schema, so description carries burden to explain result: download link also in Files tab. Covers quota, timing, dimension limitation scare. Missing explanation of 'account' parameter, but overall sufficient for a simple generation 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 has 0% description coverage, so description must compensate. It does explain usage of 'prompt' (include framing and aspect ratio) but does not mention 'account' parameter at all. Partial compensation.

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 the verb+resource: generates an image from text. Distinct from sibling 'codex_image_subscription' which handles subscription info. Adds specifics (uses ChatGPT image quota, not API credits) that help differentiate.

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 clear context: consumes image quota, takes ~1 minute, one image per call. Mentions constraints (dimension cannot be fixed, describe framing in prompt). Does not explicitly name alternatives, but the usage scenario 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?

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral context that the tool does not consume quota, which is not captured in annotations and clarifies resource impact. This goes 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?

The description is extremely concise—two short sentences that are front-loaded with the primary action and include a clarifying exclusion. Every word earns its place 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 simple read-only tool with a single optional parameter and no output schema, the description covers the core behavior well. However, the missing explanation of the 'account' parameter means the tool is not fully self-explanatory, and the agent may not know how to populate 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?

Schema description coverage is 0%, so the description must compensate for the undocumented 'account' parameter. It does not mention the parameter at all, leaving its meaning and usage entirely unexplained. This is a significant gap given the low coverage.

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 the connected ChatGPT subscription (email and plan). The explicit mention that it does not generate images distinguishes it from sibling tool codex_image_generate, making its purpose unambiguous.

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 by stating this tool does not generate images or consume quota, implying it should be used for checking subscription info rather than image generation. However, it does not explicitly name alternative tools or provide when-not-to-use conditions beyond the generation exclusion.

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 clear. The description adds valuable behavioral detail by specifying the two possible response shapes depending on connection state, which goes beyond the annotation 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?

The description is two sentences, front-loads the primary purpose ('Returns connection status and URLs'), and immediately follows with concrete conditional behavior. Every sentence adds value with no redundancy or 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 parameterless, read-only status tool with no output schema, the description fully covers the essential behavior: the success case and the credential-missing case. No additional return-type documentation is needed given the tool's simplicity, and the annotations cover safety and idempotency.

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 parameter semantics, but it does add context about what the returned URLs represent (toolkit-level and per-install) that is useful to an agent.

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, with specific conditional outcomes (authenticated:true when connected, connect_url when credentials are missing). This distinguishes it from siblings like authenticate, which performs authentication, and show_version or toolkit_info, which report static metadata.

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 it: to check whether providers are connected and to obtain connection URLs when credentials are missing. It does not explicitly name alternatives or exclusions, but the conditional behavior provides clear usage context and complements authenticate without needing to state 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?

Goes well beyond annotations by disclosing that writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin privileges, that invoke runs a tool without installing it (one-off, without bloating the tool list), and that auth/payment failures return connect/checkout links for the user to complete. This adds critical behavioral context not present in annotations (readOnlyHint=false, openWorldHint=true).

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 effectively structured: it starts with the tool's identity and core flow, then covers invoke's key behavior, installation distinction, permission requirements, and ancillary features (prompt library). Each sentence contributes crucial information for a tool with 23 parameters and 14 actions. It could be tightened by removing some redundancy (e.g., repeated mentions of the prompt library), but it is appropriately sized for the complexity and front-loaded with the most important usage 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 highly complex tool with no output schema and 23 parameters, the description is exceptionally complete. It covers the core search-discover-invoke flow, the distinction between one-off invoke and permanent install, auth/payment failure handling, permission requirements (owner/admin for writes), the prompt library functions, and the full list of action enum values. This gives an agent virtually everything it needs to select the correct action and parameters for a given user request.

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 for parameter meaning. It explains the central 'action' parameter and its 14 possible values, and clarifies key parameters like mcp_id, tool_id, arguments, and prompt_* parameters in context. However, several parameters (limit, query, conversation, immediate, tier_slug, etc.) are not individually elaborated, leaving some ambiguity without external knowledge. The description does enough to make most parameters usable given the detailed flow guidance.

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 the official mcp.ai marketplace, explicitly stating it covers capability requests like 'find an MCP that does X'. It distinguishes itself from sibling tools by detailing its core flow (search → describe → invoke) and contrasting invoke vs install, making it unambiguous what this tool does at a high level.

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 guidance: describes the recommended flow (action=search discovers MCPs, describe returns profiles, invoke runs), states when to prefer invoke over install ('prefer invoke for a single/occasional use'), and when install is appropriate (permanent addition to toolkit). It also covers alternative actions like list_tools, subscribe/cancel, and request_mcp, thus giving clear context for when to use this tool vs pursuing other paths.

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 (indicating side effects) and idempotentHint=true (same effect on repeated calls). The description adds a reproduction instruction but does not elaborate on what happens after submission (e.g., whether a confirmation is returned, if data is persisted, or any side effects). With annotations covering the safety profile, the description adds marginal value but not rich behavioral context, so a 3 is appropriate.

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 long and gets straight to the point. The first sentence states the purpose, the second provides a key usage hint. There is zero filler or redundancy, making it highly 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?

For a simple three-parameter tool with no output schema, the description covers the core purpose and one parameter (conversation). However, it omits any explanation of 'message' (the required field) and 'context', and does not clarify the expected format of the conversation string (e.g., JSON array as a string). Given the tool's low complexity and existing annotations, more could be done to fully specify parameter formats, but the essential purpose is clear. A score of 3 reflects this gap.

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 does clarify that 'conversation' is an array of recent messages for reproduction, which adds meaning beyond the raw schema (which defines it as a string defaulting to '[]'). However, it does not explain the 'message' or 'context' parameters, and the word 'array' may conflict with the schema's string type. The description provides some insight but falls short of fully compensating 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's purpose with a specific verb ('Report') and resource ('a bug, missing feature, or send feedback'). It also adds an important detail about including the conversation array for reproduction. This unambiguously distinguishes it from sibling tools like authenticate or show_version, which serve entirely 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?

The description explicitly states when to use this tool (to report bugs, missing features, or give feedback) and even includes a usage hint (include conversation array). While it does not mention when not to use it or name alternatives, the sibling tools are clearly unrelated, so the context is sufficient. It could benefit from a note like 'use for user-facing issues only,' but overall guidance is 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 annotations already declare readOnly and non-destructive behavior, and the description aligns with that ('Show' implies no side effects). No additional behavioral context is provided, but the annotations cover the essential safety profile.

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 sentence with no unnecessary words. It is well-structured and immediately conveys the function.

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, parameterless getter, the description is complete. It specifies exactly what versions are shown (MCP platform and adapter), so the user knows what to expect. No output schema is provided, but the description sufficiently sets expectations.

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 doesn't need to elaborate on parameter semantics, but it also doesn't add any extra context (e.g., optional flags). 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's purpose: showing the current MCP platform and adapter versions. It is specific and distinguishes itself from sibling tools like authenticate or connect by focusing on version information.

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 version information is needed but does not explicitly state when to use it versus alternatives. There are no competing tools for this specific task, but explicit guidance on when to invoke it (e.g., 'when you need to check version compatibility') is missing.

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, idempotentHint, and destructiveHint, covering the safety profile. The description adds valuable context beyond these hints by specifying exactly what state is returned (installed MCPs, statuses, accounts, tool counts), enriching the agent's understanding of the tool's 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 a single, well-structured sentence that front-loads the verb 'Returns' and immediately lists the key content. Every word earns its place with no redundancy or 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?

With no parameters and no output schema, the description carries the full burden of explaining return values. It comprehensively describes what the tool returns (installed MCPs, connection status, accounts, catalog tool counts), making it complete for this simple 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 schema coverage is trivially 100% and there is no parameter information to add. Baseline for 0 params is 4, and the description does not need to explain parameters since none exist.

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 and enumerates specific components (installed MCPs, connection status, connected accounts, catalog tool counts). This is a specific verb+resource and clearly differentiates from sibling tools like connect or authenticate, which are action-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 does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or preferred scenarios. However, its purpose as an informational read-only tool is implicit, so usage is implied but not guided.

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