release-sync
Syncs latest release content to NotebookLM and HQ Knowledge Base after version tagging. Reads CHANGELOG, CLAUDE.md, and hook README, updates notebook sources, and ingests release digest. Optionally generates podcast from updated knowledge base. Use after tagging a new version to propagate release knowledge.
What this skill does
# Release Content Sync
Sync the latest OrchestKit release to external knowledge systems.
> **CC ≥ 2.1.118 (M122):** Sync triggers on the new `claude plugin tag` annotated tag (in addition to plain `git tag`). The tag's annotation embeds the plugin manifest version, which release-sync uses as the canonical source-of-truth for the version being synced. See `src/skills/chain-patterns/references/plugin-tag.md`.
## What This Does
1. Reads the latest CHANGELOG entry, CLAUDE.md, and hook README
2. Updates the OrchestKit NotebookLM KB notebook with fresh sources
3. Ingests the release digest into HQ Knowledge Base (if available)
4. Optionally generates a new podcast from the updated notebook
## Prerequisites
- MCP servers: `notebooklm-mcp` and/or `hq-content`
- NotebookLM notebook ID stored in `.claude/release-sync-config.json`
## Step 1: Detect Version and Read Sources
```python
# Read current version from CLAUDE.md
version = Grep(pattern="Current.*\\d+\\.\\d+\\.\\d+", path="CLAUDE.md")
# Read CHANGELOG — extract latest release section
changelog = Read("CHANGELOG.md", limit=80)
# Read hook architecture summary
hook_readme = Read("src/hooks/README.md", limit=100)
# Read CLAUDE.md for project overview
claude_md = Read("CLAUDE.md")
```
## Step 2: Load Config
```python
config = Read(".claude/release-sync-config.json")
# Expected format:
# {
# "notebooklm_notebook_id": "0a05e680-e33b-4d8c-94b2-5df26a1af329",
# "hq_kb_project": "orchestkit"
# }
```
If config doesn't exist, prompt user:
```python
AskUserQuestion(questions=[{
"question": "NotebookLM notebook ID for OrchestKit KB?",
"header": "Configuration",
"options": [
{"label": "Use default", "description": "OrchestKit v7 — Complete KB (0a05e680...)"},
{"label": "I'll provide", "description": "Enter a custom notebook ID"}
]
}])
```
## Step 2b: Choose Sync Targets via ork-elicit (M118 #1468)
Replace the historical 3-question sequential ask with one form using the `release-sync-targets` ork-elicit preset (registered in `src/mcp-server/src/presets/release-sync-targets.ts`). Form fields: `notebooklm`, `hq_kb`, `slack`, `notes`.
```python
# Skip the form when targets are explicit:
# /ork:release-sync --targets=notebooklm,slack → skip, use those
#
# Otherwise, prefer ork-elicit; fall back to AskUserQuestion if MCP unavailable:
elicit_available = ToolSearch(query="select:mcp__ork-elicit__ork_elicit").found
if elicit_available:
raw = mcp__ork-elicit__ork_elicit(preset="release-sync-targets")
parsed = json.loads(raw)
# parsed = {
# "action": "accept" | "decline" | "cancel",
# "values": {"notebooklm": bool, "hq_kb": bool, "slack": bool, "notes": str}
# }
if parsed["action"] != "accept":
return # user cancelled
targets = parsed["values"]
else:
# Fallback: 3 sequential AskUserQuestion calls (one per boolean target).
# ALL targets default to False — OrchestKit is open-source and these
# targets (notebook IDs, HQ KB, Slack) are user-private infrastructure
# that the plugin cannot assume is configured. User explicitly opts in.
targets = {
"notebooklm": ask_yn("Push to NotebookLM?", default=False),
"hq_kb": ask_yn("Push to HQ KB?", default=False),
"slack": ask_yn("Announce in Slack?", default=False),
"notes": ""
}
```
The form path is ~1 round-trip; the AskUserQuestion fallback is 3. Behavior at the dispatch layer is identical — the rest of this skill reads `targets["notebooklm"]`, `targets["hq_kb"]`, `targets["slack"]`, `targets["notes"]` regardless of source.
**Privacy note:** all targets are opt-in (default false). NotebookLM notebook IDs and HQ knowledge bases are user-private — the open-source plugin must not assume they exist or push to them implicitly.
## Step 3: Update NotebookLM Sources
```python
# Probe MCP availability
ToolSearch(query="select:mcp__notebooklm-mcp__source_add")
# Add release digest as new source
mcp__notebooklm-mcp__source_add(
notebook_id=config.notebooklm_notebook_id,
source_type="text",
title=f"Release {version} — {date}",
text=release_digest,
wait=True
)
```
## Step 4: Ingest to HQ Knowledge Base (Optional)
```python
# Probe HQ content MCP
ToolSearch(query="select:mcp__hq-content__knowledge_ingest")
# If available, ingest
mcp__hq-content__knowledge_ingest(
title=f"OrchestKit {version} Release Notes",
content=release_digest,
project="orchestkit",
content_type="release-notes"
)
```
## Step 5: Generate Podcast (Optional)
```python
AskUserQuestion(questions=[{
"question": "Generate a podcast from the updated notebook?",
"header": "Podcast",
"options": [
{"label": "Yes — deep dive", "description": "~10 min podcast covering all changes"},
{"label": "Yes — brief", "description": "~3 min summary"},
{"label": "No", "description": "Skip podcast generation"}
]
}])
if podcast_requested:
mcp__notebooklm-mcp__studio_create(
notebook_id=config.notebooklm_notebook_id,
artifact_type="audio",
audio_format=selected_format,
confirm=True
)
```
## Output
Report what was synced:
```
Release Sync Complete — v{version}
NotebookLM: source added to {notebook_title}
HQ KB: ingested as release-notes/{version}
Podcast: generating (poll with studio_status)
```
Related in Writing & Docs
jax-development
IncludedUse this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.
nature-article-writer
IncludedDrafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.
deckrd
IncludedDocument-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.
clinical-decision-support
IncludedGenerate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
handling-sf-data
IncludedSalesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).
accelint-ac-to-playwright
IncludedConvert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.