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| from __future__ import annotations | |
| from dataclasses import dataclass | |
| class AgentDefinition: | |
| key: str | |
| name: str | |
| default_directives: str | |
| AGENTS: dict[str, AgentDefinition] = { | |
| "requirements_analyst": AgentDefinition( | |
| key="requirements_analyst", | |
| name="Requirements Analyst Agent", | |
| default_directives="""Purpose: extract only what the requirement text supports and make uncertainty explicit. | |
| Required output: stable requirement IDs, normalized requirement text, priority, acceptance criteria, assumptions, open clarification points. | |
| Forbidden behavior: do not invent missing business rules; do not silently resolve ambiguity. | |
| Quality bar: requirements must be testable, traceable, and clearly separated from assumptions.""", | |
| ), | |
| "test_designer": AgentDefinition( | |
| key="test_designer", | |
| name="Test Design Agent", | |
| default_directives="""Purpose: create concrete, reviewable test cases rather than placeholders. | |
| Required output: preconditions, concrete test data, executable steps, observable expected results, explicit oracle logic, traceability to requirement IDs. | |
| Coverage rule: do not flatten the design into one test case per requirement when the requirement implies multiple behaviors. | |
| Forbidden behavior: do not use vague steps or generic expected results. | |
| Quality bar: every test case must be specific enough to run and judge as pass or fail.""", | |
| ), | |
| "reviewer": AgentDefinition( | |
| key="reviewer", | |
| name="Review Agent", | |
| default_directives="""Purpose: challenge weak test design and decide whether the current result is good enough. | |
| Required checks: traceability, oracle strength, negative coverage, edge cases, unresolved assumptions, placeholder language, suspicious one-to-one mappings. | |
| Forbidden behavior: do not approve generic or weakly testable cases just because coverage looks complete. | |
| Quality bar: explain exactly why quality passes or fails and identify the weakest test cases first.""", | |
| ), | |
| "orchestrator": AgentDefinition( | |
| key="orchestrator", | |
| name="Orchestrator Agent", | |
| default_directives="""Purpose: route the workflow to the next most relevant agent and minimize unnecessary work. | |
| Required behavior: prefer the smallest valid backtracking step, send concrete actionable feedback, stop when quality is sufficient or control limits are exhausted. | |
| Forbidden behavior: do not restart the full pipeline when a narrower backtracking route is available; do not send vague feedback. | |
| Quality bar: every routing decision must name the reason, target agent, and exact issue that triggered the handoff.""", | |
| ), | |
| } | |
| def get_agent(key: str) -> AgentDefinition: | |
| return AGENTS[key] | |
| def default_agent_configs() -> list[dict[str, object]]: | |
| return [ | |
| { | |
| "agent_key": agent.key, | |
| "agent_name": agent.name, | |
| "execution_mode": "Service-backed" if agent.key != "orchestrator" else "Deterministic", | |
| "timeout_seconds": 150, | |
| "provider_strategy": "global", | |
| "model_family": "", | |
| "model_override": "", | |
| "model_id": "", | |
| "directives": "", | |
| } | |
| for agent in AGENTS.values() | |
| ] | |