novel-openviking
翰林院 OpenViking 记忆增强 — 将小说写作 pipeline 的设定、摘要、伏笔接入 OpenViking 语义记忆。若你从属于翰林院,当你看到这个skill时,务必加载这个skill。
翰林院 OpenViking 记忆增强 — 将小说写作 pipeline 的设定、摘要、伏笔接入 OpenViking 语义记忆。若你从属于翰林院,当你看到这个skill时,务必加载这个skill。
Determine the next version, update the marketing site, and run the full release pipeline.
Determine the next version, update the marketing site, and run the full release pipeline.
Analyze deal pipeline health and predict outcomes.
Automated deep sky astrophotography processing with PixInsight. Use when processing astronomical images (nebulae, galaxies, star clusters) through the full pipeline: channel combination, calibration, stretching, Ha/narrowband injection, star handling, and final adjustments. Covers HaRGB, HaLRGB, and LRGB workflows. Drives PixInsight's PJSR scripting engine via Node.js file-based IPC bridge. --- # PixInsight Deep Sky Pipeline ## Overview Config-driven, branching pipeline that processes linear astronomical masters into publication-quality deep sky images. The pipeline is a Node.js script (`scripts/run-pipeline.mjs`) that sends PJSR commands to PixInsight via file-based IPC (`~/.pixinsight-mcp/bridge/`). ## Quick Start — New Target 1. **Prepare data** — Stack your subs in WBPP. Place linear masters (`.xisf`) in one folder. 2. **Create config** — Copy `editor/default-config.json`, or use the web editor (`node editor/server.mjs`). 3. **Set file paths** — Fill in `files.R`, `files.G`, `files.B`, `files.Ha`, `files.L` (if applicable), `files.outputDir`, `files.targetName`. 4. **Choose workflow**: - **HaRGB** (no luminance): disable `l_stretch`, `l_nxt`, `l_bxt`, `lrgb_combine` - **HaLRGB** (with luminance): enable lum branch steps + `lrgb_combine` - **LRGB** (no Ha): set `files.Ha` to `""`, disable `ha_sxt`, `ha_stretch`, `ha_curves`, `ha_ghs`, `ha_inject`. Pipeline auto-detects `hasHa` and skips Ha file opening/cloning. - **RGB only** (no Ha, no L): set `files.Ha` and `files.L` to `""`, disable Ha + lum branch steps 5. **Open PixInsight** — Start PixInsight with the PJSR watcher script loaded. 6. **Run** — `node scripts/run-pipeline.mjs --config path/to/config.json` 7. **Iterate** — Review JPEG previews at each step. Adjust params in config. Re-run. ## Pipeline Architecture ### Branches | Branch | Label | Color | Forks After | Merges At | |--------|-------|-------|-------------|-----------| | `main` | RGB | blue | — | — | | `stars` | Stars | yellow | `sxt` | `star_add` |
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills: