Start async assessment of dialogue/interview transcripts in a session (10 credits). Returns a task_id. Poll with careerproof_task_status(task_id) until status='completed', then fetch results with atlas_get_dialogue_results(session_id). session_id must be from an existing dialogue session.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes | Dialogue session ID from an existing interview/dialogue session |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate mutation (readOnlyHint=false) and non-idempotency (idempotentHint=false). The description adds critical behavioral details: async execution pattern (returns task_id requiring polling), credit consumption (10 credits), and the exact orchestration pattern with other tools. No contradictions with 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?
Four sentences cover: purpose/cost, return value, polling workflow, and input validation. Information is front-loaded with the core action, followed by operational details. No redundant words or tautologies.
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, the description fully compensates by documenting the return value (task_id) and the complete async lifecycle. For an async initiation tool, it provides sufficient context about side effects (credit consumption), return format, and necessary follow-up actions.
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 100% (1 parameter fully documented). The description reinforces the validation constraint ('must be from an existing dialogue session') and contextualizes how the session_id is used in the downstream workflow (with atlas_get_dialogue_results), adding value beyond the schema definition.
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 explicitly states the tool 'Start[s] async assessment of dialogue/interview transcripts in a session' with specific verb (start assessment), resource (dialogue transcripts), and scope (in a session). It clearly distinguishes from sibling analysis tools by emphasizing the async nature and credit cost.
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 multi-step workflow: poll with careerproof_task_status until completed, then fetch results with atlas_get_dialogue_results. Names specific sibling tools for the complete process. Also notes the prerequisite ('session_id must be from an existing dialogue session') and cost constraint (10 credits).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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