estimate_qa_effort
Estimate QA effort deterministically from project intake fields using PERT, complexity multipliers, team capacity, and confidence scores; returns JSON with validation errors by field.
Instructions
Deterministic QA effort estimate (PERT + complexity multipliers + team capacity + confidence score) — no LLM narrative; write your own from these numbers. Fields mirror the app's project-intake dialogue and are validated with the same rules; a validation failure returns {"error": "validation", "fields": {field: message}}, never a crash; all eleven fields are needed, and a missing or empty one is reported by name in that same shape Success returns the full EstimationData as JSON (baseline, multipliers, pert_activities, capacity, risk_buffer_days, final_effort_min/max, confidence_level/confidence_score, confidence_note, data_quality_score out of data_quality_max=20). Negative team sizes and negative or zero timelines are rejected with a validation error; decimal team sizes ("2.5") are rounded half up to a whole headcount with a warning. capacity_gap = available_person_days - pert_total_expected, so POSITIVE is a surplus and NEGATIVE a deficit; capacity_status ("surplus"/"deficit"/"balanced") and capacity_note state this unambiguously. methodology_note is set only when the methodology does not change the numbers (it is then a label only).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| timeline | No | ||
| tech_stack | No | ||
| known_risks | No | ||
| methodology | No | ||
| project_name | No | ||
| project_type | No | ||
| team_qa_size | No | ||
| team_dev_size | No | ||
| additional_context | No | ||
| existing_automation | No | ||
| project_description | No | ||
| compliance_requirements | No |