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atlas_start_report

Start async generation of a research report (15 credits). IMPORTANT: Call atlas_list_report_types first to get valid report_type values and required inputs. Returns report_id and task_id. Poll with careerproof_task_status(task_id) or atlas_get_report(report_id) until status='completed', then download PDF with atlas_download_report(report_id).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsYesReport-specific inputs — use atlas_list_report_types to see required/optional fields for each type
report_typeYesReport type from atlas_list_report_types (e.g. 'candidate_evaluation', 'compensation_benchmark', 'skills_gap_analysis')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Adds significant operational context beyond annotations: discloses 15 credit cost, explains async pattern (returns IDs requiring polling), specifies PDF output format, and describes completion criteria (status='completed'). Annotations already cover safety profile (non-destructive write), so description adds workflow and cost transparency.

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

Conciseness5/5

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

Single compound sentence efficiently packs cost, prerequisites, return values, polling mechanics, and download instructions. Front-loaded with core action 'Start async generation'. Every clause is essential for correct API usage; zero wasted words despite high information density.

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

Completeness5/5

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

Excellent coverage for an async mutation tool with no output schema. Compensates for missing output_schema by documenting return values (report_id, task_id), polling behavior, and final download format. Credit cost disclosure is critical for user decision-making.

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

Parameters3/5

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

With 100% schema description coverage, the schema already documents parameters thoroughly (including examples like 'candidate_evaluation'). Description reinforces the dependency on atlas_list_report_types but adds no new parameter semantics beyond what's in the schema descriptions.

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

Purpose5/5

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

Description clearly states 'Start async generation of a research report' with specific verb (Start/async generation) and resource (research report). The async workflow and PDF output distinguish it from synchronous sibling tools like atlas_chat or atlas_get_report.

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

Usage Guidelines5/5

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

Provides explicit prerequisite: 'Call atlas_list_report_types first'. Details complete polling workflow using careerproof_task_status or atlas_get_report, and specifies atlas_download_report for final retrieval. Explicitly names alternative tools for each lifecycle phase.

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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