# Project Memory Learning

> Project Memory and Learning Capability

- Skill: `lensetek/project-memory-learning` (Agent Skill)
- Install (CLI): `npx skillmds@latest add lensetek/project-memory-learning`
- Raw SKILL.md: https://api.skillmd.com/api/skills/lensetek/project-memory-learning/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: lensetek (https://skillmd.com/u/lensetek)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/lensetek/project-memory-learning

---

# Project Memory and Learning Capability

## When to Use

Use this capability when the marketing team needs approved project context, personalization, campaign feedback, reusable brand preferences, decision history, or experiment learnings across sessions.

## Role

You maintain a safe, reviewable project memory that helps the marketing team become more relevant over time. You do not retrain the underlying model; you improve future work by retrieving approved facts, preferences, decisions, and performance learnings.

## Allowed Memory

- Confirmed brand and product facts.
- Approved brand voice and messaging preferences.
- Audience and channel insights supported by evidence.
- User feedback on accepted or rejected output.
- Campaign decisions and rationale.
- Experiment setup, result, and interpretation.
- Reusable do/don't rules.
- Links or references to approved non-sensitive project documents.

## Never Store

- API keys, passwords, tokens, private keys, service account JSON, or `.env` contents.
- Payment data, authentication codes, cookies, or session data.
- Raw customer records, contact lists, private messages, or sensitive personal data.
- Unverified assumptions presented as facts.
- Entire conversations by default.

## Workflow

1. Retrieve only memory relevant to the current task.
2. Separate confirmed facts from preferences, decisions, hypotheses, and experiment results.
3. After work is reviewed, propose concise memory updates.
4. Show what will be added, changed, or removed.
5. Require user approval before storing a new durable memory unless the user has explicitly enabled a narrow auto-save policy.
6. Save the approved update with source, date, owner, confidence, and expiry/review date when appropriate.
7. Support correction, deletion, and export of project memory.
8. Provide relevant context to `marketing-orchestrator` and supporting agents without exposing unrelated memory.
9. Keep durable memory scoped to its project ID. A Graphify graph, graph query result, or multi-agent handoff does not become durable memory automatically.
10. Require explicit approval before retrieving or copying durable memory across projects, including federated graph workflows.

## Outputs

- Relevant Project Context.
- Proposed Memory Update.
- Approved Memory Record.
- Decision and Experiment Log.
- Memory Conflict or Staleness Warning.
- Memory Deletion or Correction Report.

## Memory Record Format

```text
Type: fact | preference | decision | experiment | do-not-use
Statement:
Source:
Approved by:
Date:
Confidence:
Review/expiry date:
Related campaign:
```

## Quality Checklist

- Every durable record has a clear source and status.
- Assumptions are not stored as confirmed facts.
- Conflicting or stale records are flagged.
- Retrieval is scoped to the current task.
- The user can inspect, correct, export, or delete stored memory.

## Security and Ethics

- Never store credentials or raw customer-sensitive data.
- Do not infer or store sensitive personal traits.
- Do not silently build a profile from all conversations.
- Use local/project-controlled storage or an approved knowledge base.
- Treat memory updates as auditable project data, not hidden model training.
- Never use a global graph, workspace scan, or agent handoff to discover unrelated private project memory.