# Feature Requirements Quality Checklist: Deep Research Agent

**Purpose**: Validate completeness, clarity, and consistency of deep-research-agent requirements before implementation
**Created**: 2026-03-30
**Feature**: [spec.md](../spec.md)
**Depth**: Standard | **Audience**: Reviewer (PR)

## Requirement Completeness

- [ ] CHK001 Are all 11 deliverable files explicitly listed with their expected content? [Completeness, Spec §FR-001 through §FR-017]
- [ ] CHK002 Are the 7 CompositeBackend route paths and their corresponding S3 prefix suffixes fully enumerated? [Completeness, Spec §FR-003]
- [ ] CHK003 Are requirements for all 3 seed files specified with both local source paths and S3 destination paths? [Completeness, Spec §FR-013]
- [ ] CHK004 Are all required environment variables documented with required/optional status? [Completeness, Spec §Assumptions + Plan §data-model]
- [ ] CHK005 Are requirements for both run modes (CLI and LangGraph Studio) specified? [Completeness, Spec §US-1, §SC-007]

## Requirement Clarity

- [ ] CHK006 Is the longest-prefix matching behavior for `/memories/semantic/` vs `/memories/` explicitly defined with expected routing outcome? [Clarity, Spec §FR-004]
- [ ] CHK007 Are the research subagent's "hard limits" quantified — is "2-3 simple" vs "up to 5 complex" sufficiently specific for implementation? [Clarity, Spec §FR-006]
- [ ] CHK008 Is "idempotent" behavior for setup_backend.py defined with the specific mechanism (check existence before upload)? [Clarity, Spec §FR-013]
- [ ] CHK009 Is the structured memory categorization guidance (how to classify fact vs experience vs rule) defined in both SYSTEM_PROMPT and AGENTS.md requirements? [Clarity, Spec §FR-009, §FR-010]
- [ ] CHK010 Are the HITL interrupt behavior differences between CLI mode and LangGraph Studio mode specified? [Clarity, Spec §US-5, Gap — research.md §R5 addresses this but spec does not]

## Requirement Consistency

- [ ] CHK011 Are memory path references consistent between SYSTEM_PROMPT requirements (FR-009), AGENTS.md requirements (FR-010), and acceptance scenarios (US-3)? [Consistency]
- [ ] CHK012 Does the skills loading mechanism (FR-016: `skills=["/skills/"]`) align with the setup_backend.py upload paths (FR-013: `/skills/linkedin-post/SKILL.md`)? [Consistency]
- [ ] CHK013 Are the `_build_backend()` / `_s3()` pattern requirements (FR-015) consistent with how the 7 routes are specified in FR-003? [Consistency]
- [ ] CHK014 Is the model specification (FR-008: `claude-sonnet-4-20250514`) consistent with the `langchain-anthropic` dependency (FR-001 pyproject.toml)? [Consistency]

## Acceptance Criteria Quality

- [ ] CHK015 Are all 8 success criteria (SC-001 through SC-008) measurable without subjective interpretation? [Measurability]
- [ ] CHK016 Is SC-001 ("under 10 minutes") a reasonable and testable metric for developer setup? [Measurability, Spec §SC-001]
- [ ] CHK017 Is SC-002 ("at least 3 inline citations") a verifiable minimum for report quality? [Measurability, Spec §SC-002]
- [ ] CHK018 Is SC-008 ("files written to each path land in the expected S3 prefix") testable without implementation-specific knowledge? [Measurability, Spec §SC-008]

## Scenario Coverage

- [ ] CHK019 Are requirements defined for what happens when the agent auto-categorizes a memory the user intended for a different type? [Coverage, Gap — US-3 only covers explicit saves]
- [ ] CHK020 Are requirements defined for multi-turn research conversations where the agent should recall prior turns' context? [Coverage, Gap]
- [ ] CHK021 Are requirements specified for the content and format of episodic memory session logs (what exactly gets saved)? [Coverage, Spec §FR-010 mentions guidelines but not exact format]
- [ ] CHK022 Are requirements defined for skill loading failure (what if SKILL.md is missing or malformed on S3)? [Coverage, Gap]

## Edge Case Coverage

- [ ] CHK023 Is the behavior specified when `S3_BACKEND_PREFIX` is empty vs has a trailing slash vs has no trailing slash? [Edge Case, Spec §Assumptions]
- [ ] CHK024 Are requirements defined for what happens when the Tavily API returns zero results for a search query? [Edge Case, Gap — only invalid key is covered]
- [ ] CHK025 Is the behavior specified when memories conflict (e.g., user preference saved to semantic memory contradicts a procedural rule)? [Edge Case, Gap]
- [ ] CHK026 Are requirements defined for setup_backend.py behavior when S3 bucket doesn't exist or is inaccessible? [Edge Case, partial — only "invalid credentials" covered]

## Dependencies & Assumptions

- [ ] CHK027 Is the assumption that `deepagents>=0.4.0` provides `create_deep_agent`, `CompositeBackend`, and all referenced middleware validated against the actual deepagents API? [Assumption]
- [ ] CHK028 Is the assumption that `deepagents-contrib-aws>=0.2.0` provides both `S3Backend` and `AgentCoreCodeInterpreterSandbox` validated? [Assumption]
- [ ] CHK029 Are the required IAM permissions for S3 and Bedrock AgentCore documented in requirements? [Dependency, Gap — README §FR-017 doesn't list this explicitly]
- [ ] CHK030 Is the dependency on langgraph-101 reference files (skills, AGENTS.md) documented as a build-time requirement only (not runtime)? [Dependency]

## Notes

- CHK010 flags a gap: the spec defines HITL for both write_file and edit_file but doesn't clarify that CLI mode (main.py) doesn't surface interrupts. The research.md (R5) addresses this but the spec itself does not.
- CHK019/CHK020 identify scenario gaps where the agent's autonomous memory categorization and multi-turn context aren't fully specified — these may be acceptable given this is an example project.
- CHK029 identifies that IAM permissions (s3:PutObject, s3:GetObject, bedrock:InvokeModel, etc.) are not listed in the spec or README requirements.
