Pimea

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

With no annotations, the description carries the full burden. It discloses the conversational behavior (answer on behalf when possible), the response status handling ('complete' → get_answer), and the authentication fallback mechanism (leave api_key blank unless connector can't send headers). This is rich 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?

The description is front-loaded with the main purpose, followed by targeted usage guidance, a brief auth note, and a clear Args list. No wasted sentences.

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 output schema covers return structure, the description completes the picture with workflow integration (start_session → chat → get_answer), the on-behalf policy, and authentication details. It's fully sufficient for invoking this tool correctly.

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

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

Schema has 0% coverage, but the Args section explains session_id as 'The session UUID from pimea_start_session', message as 'Response to Pimea's question', and api_key as 'Optional fallback only'. This adds essential semantics missing from the schema.

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 'Send a message in an active Pimea session,' a specific verb+resource statement. It further clarifies this is for answering Pimea's clarifying questions, and distinguishes from pimea_get_answer by instructing to call that tool when status is complete.

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?

Explicitly states when to use ('answer Pimea's clarifying questions'), provides a decision rule for answering on behalf of the user vs asking directly, and names the alternative (pimea_get_answer) for retrieving the final deliverable. It also gives authentication usage guidance.

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

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

With no annotations provided, the description carries full burden and does well: it discloses return modes, data_confidence, citation presentation, and auth behavior. It is clear this is a read/retrieval operation, though not explicitly labeled as such.

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 purpose, well-structured with bullets for return modes, and every sentence adds actionable value—from data_confidence to authentication. It is detailed yet concise with no 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?

Given the simplicity (2 params, output schema present) and available context, the description is complete: it explains return modes, confidence metrics, and auth setup, which fully prepares an agent to invoke and interpret the tool correctly.

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

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

The schema has no property descriptions (0% coverage), but the description fully compensates: session_id is defined as the session UUID, and api_key is explained as an optional fallback normally left blank with the connector handling headers.

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?

Purpose is explicitly stated: 'Get the final result from a completed Pimea session.' It uses a specific verb and resource, and distinguishes itself from summarization and sibling tools by declaring the deliverable as the source of truth.

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?

Explicit guidance is given: 'ALWAYS use this to retrieve the grounded deliverable instead of summarizing the chat history yourself.' It also indicates the prerequisite of a completed session and gives authentication fallback instructions, clearly defining when to use this 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?

With no annotations to lean on, the description fully discloses important behaviors: auto-detection of 'recommend' vs 'execute' modes, the return of a session_id and first clarifying question, and the auth mechanism (X-API-Key header with an api_key fallback). It also states that answers are grounded in real campaign data, adding context beyond the bare operation.

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 uses a clear structure: bolded imperative, bulleted mode list, and sectioned args. It is longer than a one-liner but every sentence earns its place—covering triggers, behavior, return value, auth, and parameters—without fluff 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?

Given the tool's role as a session starter, the description covers all essential aspects: what it does, when to call it, what it returns, how auth works, and the next step. The existing output schema handles return details, so the description is complete for selection and invocation.

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 coverage is 0%, but the description adds complete meaning for both parameters. 'message' is explained with an example and instruction to paraphrase the user's need. 'api_key' is clearly marked optional, with precise fallback conditions and when to avoid setting it. This fully compensates for the schema's lack of 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 opening line states a clear verb and resource: 'Start a Pimea marketing intelligence session.' It enumerates specific marketing areas (strategy, channels, campaigns, brand, etc.) and distinguishes the tool from siblings by positioning it as the entry point and directing continuation via 'pimea_chat'.

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?

Explicit when-to-use guidance is given: 'CALL THIS WHENEVER THE USER ASKS ANY MARKETING QUESTION...' and instructs to call it before answering from one's own knowledge. It also clarifies the appropriate follow-up (pimea_chat) and provides authentication handling directives, making alternatives and exclusions clear.

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