# Ai Memory Developer

> |

- **Type:** Skill
- **Install:** `agentstack add skill-daemon-blockint-tech-agentic-enteprises-skill-ai-memory-developer`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [daemon-blockint-tech](https://agentstack.voostack.com/s/daemon-blockint-tech)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [daemon-blockint-tech](https://github.com/daemon-blockint-tech)
- **Source:** https://github.com/daemon-blockint-tech/Agentic-Enteprises-Skill/tree/main/ai-memory-developer

## Install

```sh
agentstack add skill-daemon-blockint-tech-agentic-enteprises-skill-ai-memory-developer
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# AI Memory Developer

## When to Use

- Building persistent memory for copilots, agents, or conversational AI
- Designing memory APIs (read/write/consolidate/forget)
- Choosing between vector stores, graph databases, or structured DBs for memory
- Implementing memory write/read policies and ACLs
- Debugging wrong, stale, or hallucinated memories
- Tuning what the model should remember across sessions (episodic vs semantic)
- Planning GDPR deletion paths and privacy retention for stored memories
- Evaluating memory quality (recall, precision, isolation)

## When NOT to Use

- General RAG document search or indexing pipelines → `ai-engineer`
- Context window packing, token budgets, or compression → `ai-context-engineer`
- AI team operations, release governance, or SLOs → `ai-lead-ops`
- Org-wide token cost improvement roadmaps → `ai-token-improvement-plan-engineer`

## Related skills

| Need | Skill |
|---|---|
| End-to-end LLM app, RAG, agents | `ai-engineer` |
| Context assembly and compression | `ai-context-engineer` |
| Prompt and tool message design | `prompt-engineer` |
| PII retention and governance | `ai-risk-governance` |
| Production monitoring and incidents | `ai-lead-ops` |
| Token cost program and phased savings plan | `ai-token-improvement-plan-engineer` |

## Core Workflows

### 1. Memory model design

**Classify memory types:**

| Type | Lifetime | Examples | Store |
|---|---|---|---|
| Working | Single turn / tool loop | Tool results, scratchpad | In-context only |
| Session | Chat session | Current task state | Redis / thread store |
| User long-term | Cross-session | Preferences, facts user stated | Vector + structured DB |
| Organizational | Shared | Docs, policies | RAG index (see `ai-engineer`) |

**Design decisions:**

1. What may be written automatically vs requires user confirmation?
2. Per-tenant isolation and ACL on every read/write
3. TTL and deletion (GDPR erase path)
4. Conflict resolution when new fact contradicts old

**See `references/memory_architecture.md` for patterns and anti-patterns.**

### 2. Write path (ingestion to memory)

```
observe → extract candidates → score importance → dedupe → persist → index
```

**Checklist:**

- [ ] Extract only durable facts, not transient chit-chat
- [ ] Attach provenance (message ID, timestamp, source)
- [ ] Dedupe with embedding similarity + entity linking
- [ ] Never store secrets, raw payment data, or full medical records unless required and approved

**See `references/write_consolidation.md` for extraction prompts and consolidation jobs.**

### 3. Read path (retrieval for generation)

1. Build query from current user message + session summary
2. Retrieve top-k memories with metadata filters (`user_id`, `tenant_id`)
3. Rerank; drop below relevance threshold
4. Inject into context in structured block (see `ai-context-engineer`)
5. Cite memory IDs in logs for debugging

**See `references/read_retrieval.md` for ranking and injection formats.**

### 4. Forgetting and maintenance

| Trigger | Action |
|---|---|
| User delete request | Hard delete all user memories |
| TTL expired | Archive or purge |
| Low usefulness score | Decay or summarize away |
| Contradiction | Supersede old record; keep audit trail |

Run nightly consolidation: merge episodic notes into semantic summaries.

**See `references/write_consolidation.md` for consolidation algorithms.**

### 5. Evaluation

| Test | Pass criteria |
|---|---|
| Write accuracy | Gold facts appear in store after session |
| Recall | Question answerable from prior session |
| Precision | Irrelevant memories not retrieved |
| Isolation | Tenant A never sees tenant B |
| Forgetting | Deleted user has zero retrievable memories |

**See `references/memory_eval.md` for datasets and regression harness.**

## When to load references

- **Architecture and stores** → `references/memory_architecture.md`
- **Write and consolidation** → `references/write_consolidation.md`
- **Read and ranking** → `references/read_retrieval.md`
- **Evaluation** → `references/memory_eval.md`

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [daemon-blockint-tech](https://github.com/daemon-blockint-tech)
- **Source:** [daemon-blockint-tech/Agentic-Enteprises-Skill](https://github.com/daemon-blockint-tech/Agentic-Enteprises-Skill)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-daemon-blockint-tech-agentic-enteprises-skill-ai-memory-developer
- Seller: https://agentstack.voostack.com/s/daemon-blockint-tech
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.