
Learn
Run a six-phase research workflow that turns unfamiliar topics or messy source bundles into a coherent mental model and publish-ready article or reference.
Install
npx skills add https://github.com/tw93/waza --skill learnWhat is this skill?
- Six-phase workflow from raw materials to published output
- Explicit outcome contract: sources, contradiction handling, and teachable final structure
- Supports 学习一下 / deep dive / compile sources intents with boundary vs quick /read
- Preserves user thinking; organizes and explains without replacing judgment
- Delivers notes, outline, draft, or canonical reference per chosen mode
Adoption & trust: 5.9k installs on skills.sh; 5.6k GitHub stars; 2/3 security scanners passed (skills.sh audits).
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Journey fit
Primary fit
Deep dives and compiling unfamiliar domains start in Idea research before validation or content growth decisions. The skill collects, digests, and structures primary material—the core research subphase—not single-shot lookups.
Common Questions / FAQ
Is Learn safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.
SKILL.md
READMESKILL.md - Learn
# Learn: From Raw Materials to Published Output Prefix your first line with 🥷 inline, not as its own paragraph. Collect, organize, translate, explain, structure. Support the user's thinking; do not replace it. ## Outcome Contract - Outcome: unfamiliar material becomes a reliable mental model, reference, article, or notes set the user can use. - Done when: primary sources are collected or supplied, contradictions are handled explicitly, and the final structure teaches the topic without hiding uncertainty. - Evidence: source URLs or files, fetched content, notes from digestion, outline decisions, and self-review against the requested output. - Output: research notes, outline, publish-ready draft, or canonical reference, matching the chosen mode. **Boundary**: single URL that only needs fetching belongs in `/read`. A single URL that needs summary or analysis can use `/read` as the fetch step, but the final answer should satisfy the user's requested summary or analysis. `/learn` is for multi-source research that produces a new structured output. ## Pre-check Check whether `/read` and `/write` skills are installed (look for their SKILL.md in the skills directories). Warn if missing, do not block: - `/read` missing -- Phase 1 fetch falls back to native `WebFetch` / `curl`; coverage on paywalled, JS-heavy, and Chinese-platform pages degrades. - `/write` missing -- Phase 5 AI-pattern stripping falls back to manual scan. Phases 1-4 are unaffected. ## Choose Mode Ask the user to confirm the mode, using the environment's native question or approval mechanism if it has one: | Mode | Goal | Entry | Exit | |------|------|-------|------| | **Deep Research** | Understand a domain well enough to write about it | Phase 1 | Phase 6: publish-ready draft | | **Quick Reference** | Build a working mental model fast, no article planned | Phase 2 | Phase 2: notes only | | **Write to Learn** | Already have materials, force understanding through writing | Phase 3 | Phase 6: publish-ready draft | | **Canonical Article** | One article that covers a topic so thoroughly readers need nothing else | Phase 1 | Phase 6: single authoritative reference | If unsure, suggest Quick Reference. ## Canonical Article Mode Activate when: "一篇就够", "一站式参考", "整理成长文", "目的是大家只需要看这篇就好了", or the user wants a single authoritative reference on a topic. Goal: after reading the article, no one should need to search for anything else on this topic. Additional requirements on top of standard Deep Research: - Every major sub-topic must have its own section; nothing left as a footnote - Include worked examples, not just principles - Cover common mistakes and how to avoid them - Add a "Further Reading" section with the 3-5 sources that go deepest; flag which ones are the best starting points - Phase 6 self-review must confirm: "Could a reader implement/understand this from this article alone?" ## Phase 1: Collect Gather primary sources only: papers that introduced key ideas, official lab/product blogs, posts from builders, canonical "build it from scratch" repositories. Not summaries. Not explainers. Three ordered steps per source -- no shortcuts, no merging: 1. **Discover** -- use an installed search plugin (e.g., PipeLLM) to map the landscape, then deep-search the 2-3 most promising sub-topics. No plugin: use the environment's native web search. Output is a URL list; do not fetch content here. 2. **Fetch** -- every URL goes