aws-samples / aws-samples/sample-autonomous-cloud-coding-agents
feat(memory): structured knowledge graph (tier 4, optional)
- Dominant language
- TypeScript
- Stars
- 143
- Forks
- 46
- Avg merge
- 3d 9h
- Merged PRs (30d)
- 20
Description
**Context:** ROADMAP.md → Memory security → Structured knowledge graph (tier 4)
---
## Component
Agent (Python runtime)
## Describe the feature
Optional **long-term** direction: structured knowledge graph if semantic + episodic AgentCore Memory proves insufficient for repo-specific query patterns (e.g. cross-file API dependency queries).
## Use case
Some repos need relationship-aware retrieval ("what calls this endpoint?") beyond vector similarity. Defer until semantic/episodic limits are measured in production.
## Proposed solution
1. RFC spike: graph schema, query API, sync from codebase indexing.
2. Integration point with hydration budget.
3. Explicitly **optional**—ship only if evaluation pipeline shows retrieval gaps.
4. May leverage external store (Neptune, or embedded graph) — TBD in RFC.
## Other information
- Lowest priority in memory epic; do not block other memory security work.
- Design context: `docs/design/MEMORY.md`.
- [ ] This might be a breaking change
Contributor guide
Research direction
Read ROADMAP.md and docs/design/MEMORY.md to understand the memory-security context and existing semantic and episodic limits. Begin with the proposed RFC spike, documenting the graph schema, query API, codebase-index synchronization, and hydration-budget integration. Done means the evaluation pipeline justifies the optional feature and the RFC resolves the external-store choice.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, python
- Domain
- ai, databases
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100