Syncs knowledge to the agentic-harness knowledge base and AGENTS.md learned facts.
Scanned 9/2/2026
Install to Claude Code
npx -y skills add ulises-jeremias/agent-toolkit --skill workspace-knowledge-sync --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: workspace-knowledge-sync
description: Syncs knowledge to the agentic-harness knowledge base and AGENTS.md learned facts.
Use when the assistant discovers new patterns, learns user preferences, workspace facts,
or identifies information worth preserving for future sessions. Integrates with platform-engineer
(formerly tech-assistant) for automatic trigger points.
origin:
type: first-party
metadata:
inspired_by:
- repository: cursor/plugins
path: continual-learning/skills/continual-learning
ref: 60c641e4fad674784b30abcf9f8915dea39df38d
note: Durable learned facts (user preferences / workspace facts), plain-bullet AGENTS.md
sections, deduplication and 12-bullet cap; adapted without hooks/transcript mining to explicit sync
---
# Workspace Knowledge Sync
Automatically syncs valuable discoveries, patterns, and decisions to the agentic-harness knowledge base and durable `AGENTS.md` learned facts.
---
## Purpose
The orchestrator session accumulates knowledge through work. This skill ensures that valuable discoveries don't get lost and are available for future sessions — both in the workspace knowledge base (`knowledge/`) and as durable learned facts in `AGENTS.md`.
Inspired by `cursor/plugins` `continual-learning` (without hooks — no transcript mining or `stop` hook).
---
## Trigger Points (Automatic)
The platform-engineer (archived `tech-assistant` — now inline `references/WORKSTATION_OPS.md`) will invoke this skill automatically when:
| Situation | What to Sync | Target |
|-----------|--------------|--------|
| Discovery of new skill/tool | Skill name, purpose, usage pattern | `knowledge/skills/discovered.md` |
| New process pattern | Process steps, roles, tools | `knowledge/processes/general.md` |
| Key decision made | Decision, rationale, outcome | `knowledge/learnings/general.md` |
| Pending follow-up | Task description, context | `knowledge/todos/pending.md` |
| User teaches something | Information, preference | Relevant knowledge file |
| Recurring user preference / correction | Plain bullet, durable preference | `AGENTS.md` → `## Learned User Preferences` |
| Stable workspace fact | Plain bullet, durable fact | `AGENTS.md` → `## Learned Workspace Facts` |
---
## How It Works
### Knowledge base (`agent-toolkit memory`)
The skill uses the stable `agent-toolkit memory` API with `--from-skill` for origin tracking (harness alias: `assistant-memory` / `bin/assistant-memory`):
```bash
# Search before adding
agent-toolkit memory search "<query>"
# Add a learning (with origin tracking)
agent-toolkit memory add --type learning --from-skill knowledge-sync "Pattern: <description>"
# Add a skill (with tags)
agent-toolkit memory add --type skill --from-skill knowledge-sync --tags jira,workflow "New skill: <name>"
# Add a pending todo
agent-toolkit memory add --type todo --from-skill knowledge-sync "<description>"
```
### Learned facts (AGENTS.md)
For durable, reusable facts that should survive across sessions, update `AGENTS.md` directly:
1. Read existing `AGENTS.md` first. If it does not exist, create it with only:
- `## Learned User Preferences`
- `## Learned Workspace Facts`
2. Pull out only durable, reusable items:
- recurring user preferences or corrections
- stable workspace facts
3. Update `AGENTS.md` carefully:
- update matching bullets in place
- add only net-new bullets
- deduplicate semantically similar bullets
- keep each learned section to at most 12 bullets
4. If the merge produces no `AGENTS.md` changes, leave `AGENTS.md` unchanged.
No hooks, no transcript index, no `followup_message` — the sync is explicit (manual or via platform-engineer trigger), not hook-driven.
---
## Knowledge Structure
```
knowledge/
├── skills/
│ └── discovered.md # New skills found during work
├── processes/
│ ├── jira.md
│ ├── confluence.md
│ └── general.md # Generic process patterns
├── learnings/
│ └── general.md # Key decisions and insights
└── todos/
└── pending.md # Follow-up items
AGENTS.md (workspace root)
├── ## Learned User Preferences # max 12 plain bullets
└── ## Learned Workspace Facts # max 12 plain bullets
```
---
## Learned Facts — Criteria and Guardrails
Inspired by `continual-learning` `agents-memory-updater` (adapted without transcript mining):
**Include only:**
- Recurring user preferences or corrections (e.g., "Always use feature branches", "Prefer pnpm over npm")
- Stable workspace facts (e.g., "Primary DB is Postgres 16 on host X", "Deploy via Vercel")
**Exclude:**
- Secrets, private data, tokens, credentials
- One-off instructions or transient details
- Evidence/confidence tags, process instructions, rationale blocks, or metadata
**Format:**
- Plain bullet points only (`- ...`)
- Keep only these sections: `## Learned User Preferences`, `## Learned Workspace Facts`
- No tables, no tags, no frontmatter in these sections
**Limits:**
- At most 12 bullets per section; deduplicate semantically similar bullets
- Update in place when a bullet already exists with similar meaning
---
## Manual Usage
You can also trigger this skill manually:
```
User: "Save that pattern for later"
Assistant: → Use knowledge-sync to preserve the pattern
User: "Remember I prefer pnpm and conventional commits"
Assistant: → Append to knowledge/learnings/general.md and AGENTS.md ## Learned User Preferences
```
---
## Integration with platform-engineer (formerly tech-assistant)
The platform-engineer (archived `tech-assistant` → `references/WORKSTATION_OPS.md`) checks for these automatic sync opportunities:
1. **After task creation/update** → Sync initiative info
2. **After discovering space/list IDs** → Sync to knowledge base (per `knowledge-sync`).
3. **After learning user preferences** → Sync to learnings + `AGENTS.md` learned facts (if durable)
4. **When user mentions follow-up** → Add to pending
5. **After stable workspace facts emerge** → Sync to `AGENTS.md` `## Learned Workspace Facts`
---
## Best Practices
1. **Be selective** - Only sync valuable, reusable information
2. **Be specific** - Include context and usage examples
3. **Be concise** - One idea per entry, link to details
4. **Be current** - Update outdated information when found
5. **Be durable** - AGENTS.md facts must be reusable across sessions, not transient
---
## Examples
### Auto-sync discovery
```
Assistant discovers Initiative list IDs for all Technology spaces
→ Syncs to knowledge/processes/clickup/spaces/
```
### Auto-sync key decision
```
Assistant and user decide on naming convention
→ Syncs to knowledge/learnings/general.md
```
### Learned fact — user preference
```
User repeatedly corrects: "use pnpm, not npm"
→ Assistant adds to AGENTS.md:
## Learned User Preferences
- Use pnpm for JS package management
```
### Learned fact — workspace fact
```
Workspace uses Postgres 16 with vector extension on host db.internal
→ Assistant adds to AGENTS.md:
## Learned Workspace Facts
- Postgres 16 with pgvector on db.internal
```
### Manual sync request
```
User: "Remember that we always use feature branches"
→ Assistant syncs to knowledge/processes/general.md and AGENTS.md ## Learned User Preferences
```
---
## Configuration
The skill uses these environment variables:
| Variable | Default | Purpose |
|----------|---------|---------|
| `KNOWLEDGE_BASE_PATH` | `~/.ai-workspace/knowledge` | Knowledge base root |
---
Base directory: `~/.local/share/knowledge-sync` (installer path; `~/.local/share/agent-toolkit/` when using toolkit install)
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