awesome-webpage-research
Single-pass mini research for AwesomeWebpageMetaSkill: produce a short cited topic brief from one bounded web-search round. Not a general deep-research replacement.
git clone --depth 1 https://github.com/opensquilla/opensquilla /tmp/awesome-webpage-research && cp -r /tmp/awesome-webpage-research/src/opensquilla/skills/bundled/awesome-webpage-research ~/.claude/skills/awesome-webpage-researchSKILL.md
# Awesome Webpage Research (mini)
Lightweight, single-pass topic research used only by `AwesomeWebpageMetaSkill`.
Produce a concise topic brief with a short citation list so the page planner has
factual anchors. This is **not** a replacement for the bundled `deep-research`
skill; do not invoke it for general literature reviews or multi-round
investigations.
## Inputs
The caller supplies:
- `question`: the topic, audience, language, style, and webpage context to
research.
## Protocol
Single round. Three steps. No iteration, no plan.json, no state file.
1. **Identify 3-5 focused sub-questions** that the page planner needs answered
to ground page sections. Cover what the topic is, why it matters, key facts,
common misconceptions, and at most one stat or date anchor. Do not exceed 5
sub-questions.
2. **Run one bounded web-search round**: at most one search query per
sub-question. Use `web-search` for every language. Prefer recent, reputable
sources. Stop at one usable source per sub-question; do not chase broader
coverage and do not run a second round.
3. **Compile a single brief** (target ~300-500 words) containing:
- one paragraph topic summary
- one paragraph "key facts" with inline `[1]`-style citation tags
- a `Sources` list of 3-5 entries formatted as `[n] Title — URL`
- a final `Page anchors:` line listing 3-5 short phrases that can become
section headings or callouts on the webpage
## Rules
- Do not iterate. One search round, one synthesis pass. Return as soon as the
brief is written.
- Do not fetch full articles. Use search snippets; perform at most one quick
fetch per sub-question if a snippet is unusable.
- Do not invent citations. Every `[n]` must map to a source in the `Sources`
list. If a source cannot be cited, drop the claim instead of fabricating one.
- Do not produce a multi-page literature review. Cap the brief at ~500 words.
- Do not search for images, audio, or video media here; media acquisition is
handled by other meta-skill steps.
- Do not call `deep-research`, `summarize`, or any meta-skill from this step.
- If the search round returns nothing usable, prepend a single line
`RESEARCH_THIN` to the brief and continue with a question-only summary
without inventing citations or sources.
## Output
Return only the brief text. No methodology notes, no per-source commentary,
no JSON wrapper. The caller will truncate this output before feeding it to
the page planner.Submit audio or video for multilingual dubbing, poll status, and download dubbed audio. Use when the user asks for dubbing, 多语言配音, 视频翻译配音, 译制片, or wants a source clip dubbed into another language.
Generate a structured short-video shooting script from a topic. Emits a strict, machine-parseable shot list (3 shots by default) with image prompt + video prompt + voiceover + on-screen text per shot. Trigger when the user asks for a video script, 分镜, 短视频文案, AI视频, 短剧脚本, or wants visual prompts ready for image/video generation.
Use when the user asks to schedule recurring tasks, one-off reminders, timers, or cron-style jobs through the OpenSquilla cron tool.
Multi-round research with explicit methodology, evidence tracking, and citation-tagged synthesis. Trigger on 'deep dive', 'research report', 'literature review', 'investigate X across sources', 'multi-round investigation'. Distinct from the `summarize` skill, which is a single-pass condensation; this skill maintains a state file across iterations, tracks coverage, and produces a long-form report with per-claim citations. Three execution stages: plan (scope into sub-questions), iterate (record evidence per round), compile (synthesize report). The skill itself does not fetch the web — it tells the host agent which fetches to perform via OpenSquilla's existing web tools, and records what comes back.
Read, edit, or create Microsoft Word `.docx` files. Trigger this skill whenever the user mentions a Word document, .docx file, contract, report, brief, memo, or asks to extract text, modify an existing doc, generate one from a brief, or audit tracked changes. Three execution paths: text-and-structure extraction, in-place edit-by-run (preserves styles), and create-from-scratch with python-docx. Falls back to OOXML unzip-and-patch for layout work python-docx cannot reach.
Capture the current git diff (staged, working-tree, or staged file list) as text. Direct shell call for workflows that need repository diffs without an LLM agent loop.
GitHub operations via `gh` CLI: issues, PRs, CI runs, code review, API queries. Use when: (1) checking PR status or CI, (2) creating/commenting on issues, (3) listing/filtering PRs or issues, (4) viewing run logs. NOT for: complex web UI interactions requiring manual browser flows (use browser tooling when available), bulk operations across many repos (script with gh api), or when gh auth is not configured.
Query the per-turn DecisionEntry log for skill co-occurrence patterns, meta-skill usage stats, and the router fixture corpus. Returns a JSON summary suitable for downstream LLM consumption. Used by meta-skill-creator's harvest step but also useful standalone for 'which skills did I use most this week?'