Skill: myvyang/source-research (version 1.0.0)

--- name: source-research description: "Build and maintain a reusable source-research system for discovering source pools, evaluating whether they are worth ongoing investment, defining efficient acquisition/filtering methods, recording rejection decisions, and producing high-quality source lists or notes. Use when the user mentions 信源, 信源池, 高质量信源, 信息源, 来源池, 作者池, account/blog/source curation, or wants a repeatable framework for finding and using high-quality information sources." --- # Source Research Skill Use this skill when the task is about: - discovering or recording new source pools; - deciding whether a pool is worth continued investment; - defining how to acquire information from a pool efficiently; - filtering pools into high-quality sources; - standardizing how source-research artifacts are stored; - leaving reusable artifacts so future agents do not repeat the same analysis. ## Core model Treat source research as: 1. **Three result layers**: source pools / acquisition methods / filtered high-quality sources. 2. **Four execution stages**: record pool / research methods / produce source results / automate monitoring. Important: the four stages are **not a strict sequence**. A pool may stay manual, may have results before methods are documented, or may be recorded now and researched later. ## Default operating rules 1. If you discover a new pool while doing another task, **record it immediately**. 2. If a pool was already evaluated and rejected, **preserve the rejection conclusion** so future agents do not waste time re-evaluating it. 3. If a pool is useful but not automated yet, **manual collection is allowed**; do not block on automation. 4. If a pool repeatedly proves valuable, **raise priority** for methodology, engineering, and automation. 5. Always try to leave at least one reusable artifact: pool update, method doc, result list, rejection note, or engineering design. ## Read these references Read these files before doing non-trivial source-research work: - `references/framework.md` - `references/artifacts.md` - `references/storage.md` - `references/organization.md` ## Storage contract This skill is not only about how to use the framework. It also standardizes how these things should be stored: - source pool information; - acquisition rules or programs; - filtering rules or programs; - high-quality source lists; - high-quality information captured from those sources; - rejection conclusions; - information results and automation assets. Follow the established pattern used by strong skills: keep the **methodology in the skill**, and keep the **workspace data in a dedicated directory**. The canonical dedicated workspace directory for this skill is: - `.source-research/` If it does not exist yet, initialize it with: - `python <skill-dir>/scripts/init_source_research.py [workspace-root]` Canonical categories inside `.source-research/`: - `source-pools/` - `acquisition/` - `filtering/` - `high-quality-sources/` - `high-quality-information/` - `rejections/` - `programs/` Do **not** treat generic docs as the primary storage for these results. Generic docs may hold framework notes, but canonical source-research data should live in `.source-research/`. ## Minimal workflow ### A. New pool discovered - Add or update a pool file under `.source-research/source-pools/`. - Mark a status such as: observed / worth deeper research / has high-quality results / suitable for engineering / not worth investment. ### B. Existing pool revisited - Check existing pool notes and rejection conclusions first. - If it was previously rejected, only reopen when there is genuinely new evidence. ### C. Information needed now - Manual collection is acceptable. - If repeated manual work appears, record that this pool should move toward reusable acquisition/filtering methods. - Store useful captured information under `.source-research/high-quality-information/` when it is worth preserving. ### D. Valuable pool confirmed - Add or update: - acquisition method or program under `.source-research/acquisition/` or `.source-research/programs/`; - filtering method or program under `.source-research/filtering/` or `.source-research/programs/`; - high-quality source results under `.source-research/high-quality-sources/`; - engineering/automation design when justified. ## Storage standard When using this skill, do not leave the outcome only in chat. Normalize storage according to artifact type: - pool metadata and status -> `.source-research/source-pools/`; - acquisition methods/programs -> `.source-research/acquisition/` or `.source-research/programs/`; - filtering methods/programs -> `.source-research/filtering/` or `.source-research/programs/`; - filtered high-quality source results -> `.source-research/high-quality-sources/`; - high-quality information from those sources -> `.source-research/high-quality-information/`; - rejection decisions -> `.source-research/rejections/`; - engineering/automation work -> `.source-research/programs/`. ## Output standard Do not end with only vague suggestions. Leave concrete artifacts in the workspace so another agent can continue from files rather than chat memory.


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