Research Skill
Fetch internet content or conduct deep multi-source research.
Routing Table
| Trigger words | Tool | Purpose |
|---|---|---|
| search, find, look up | search.py | Web, docs, news lookup |
| read, fetch, get page | web.py | Extract page text |
| download, extract, subtitles, transcript | youtube.py / yt-dlp | Video subtitles and metadata |
| convert, compress, encode, ffmpeg | ffmpeg.py | Media format conversion |
| research, investigate, analyze, compare | Multi-tool workflow | Deep multi-source research |
When the user intent is ambiguous, ask one clarifying question before proceeding.
Research Depth Levels
Not every request needs a full investigation. Choose the appropriate depth based on complexity, or ask the user if unclear.
"Round" = one cycle of parallel tool calls. A single round can fire 3-5 searches/reads in parallel. Rounds are sequential — each round builds on what you learned in the previous one.
| Level | When to use | Minimum effort |
|---|---|---|
| L1 — Quick lookup | Single fact, definition, simple question | 1 round, 1-2 searches |
| L2 — Focused research | Comparison, how-to, specific topic | 2-3 rounds, 2+ page reads, basic fact-check |
| L3 — Deep investigation | Multi-faceted analysis, market research, technical evaluation | 5+ rounds, 5+ page reads, task list mandatory, full fact-check |
Decision guide:
- If the question can be answered with a single search result → L1
- If it involves comparing options or understanding a topic in depth → L2
- If it requires multiple perspectives, data synthesis, or the user explicitly says "research" / "investigate" / "deep dive" / "深度" → L3
- If you cannot determine the level, ask the user: "This could be a quick lookup or a deeper investigation — how thorough would you like me to be?"
Research Workflow (L2 and L3)
Step 1 — Define Scope
Before searching, clarify:
- What is the core question? What does the user actually need to know?
- What source types are needed — official docs, news, academic papers, user reviews?
- What dimensions matter (price, performance, compatibility, recency...)?
- How confident does the conclusion need to be?
If any of the above is unclear, ask the user before proceeding.
Step 2 — Create Research Plan (L3 mandatory, L2 recommended)
Decompose the task into research dimensions — each dimension is an independent angle of investigation. Use todo, tasks, todowrite, or equivalent tool to create a visible task list.
Example — "深度检索 AI coding 领域的创业公司，区分海内外，并简单判断投资潜力":
[ ] 1. 海外 AI coding 创业公司全景 (who, what, founded when)
[ ] 2. 国内 AI coding 创业公司全景
[ ] 3. 各公司融资情况、投资方、估值
[ ] 4. 产品对比：功能、定价、目标用户
[ ] 5. 市场格局和竞争态势
[ ] 6. 投资潜力评估（团队、技术壁垒、增长、风险）Rules:
- L3 must have at least 3 dimensions, typically 4-6
- Each dimension will get its own dedicated search round(s)
- Do NOT skip this step — a task list forces thoroughness
Step 3 — Execute Per-Dimension (Multi-Round Search)
Execute each dimension as a focused investigation cycle:
For each dimension in the task list:
- Mark in-progress — Before starting a dimension, update its todo status to
in-progress - Search — Fire 1-3 parallel searches targeting this specific dimension
- Read — Open and read the most relevant sources from search results
- Record — Extract key data points and note sources
- Mark complete — Immediately after finishing a dimension, mark it
completedin the todo list - Adapt — If new sub-questions, gaps, or unexpected angles emerge, add new todo items to the list before moving on; do not silently absorb them
Dynamic todo updates are mandatory throughout execution:
- Never batch completions — mark each item done the moment it is finished
- If a dimension turns out to be larger than expected, split it into sub-items
- If a dimension turns out to be irrelevant, mark it
skippedwith a one-line reason - The todo list is a live document — the user should always be able to glance at it and understand what has been done and what remains
Search angle variety within each round:
- Broad terms — Get the landscape, find authoritative sources
- Specific terms — Target precise data (version numbers, prices, specs)
- Contrarian terms — Search for "problems", "downsides", "alternatives", "vs" to find critical perspectives
- Recency terms — Add year or "2025" to filter outdated content
- Multi-language — Search in both English and Chinese when relevant
Parallelism: Within a single round, fire multiple tool calls in parallel (e.g., 3 searches at once, or 2 searches + 1 web read). Each round should maximize parallel execution.
If you have not met these minimums, keep researching. Do NOT shortcut.
Step 4 — Fact-Check
Do not skip this step.
- Cross-verify key data from multiple independent sources (aim for 2-3; more for L3)
- If only a single source exists, explicitly note: "Based on a single source — not independently verified"
- When sources contradict each other:
1. Identify the reason (timing difference? different versions? conflicting interests?) 2. State which source is more credible and why 3. If you cannot resolve the contradiction, present both sides and ask the user how they want to proceed
- Distinguish facts from opinions — opinions may be cited but must not be stated as facts
- Never fabricate or assume unverified data — say "insufficient evidence" instead
Step 5 — Synthesize Output
- Conclusion first — Lead with the most important finding or recommendation, then expand
- Cite every data point with
[1],[2], etc., so the reader can verify - Be honest about uncertainty — If evidence is limited, say so; do not force a conclusion
- End with a full source list
Contradiction and Uncertainty Handling
When you encounter any of the following during research, do not silently resolve it — surface it to the user:
| Situation | Action |
|---|---|
| Sources contradict each other on key data | Present both claims with sources, explain possible reasons, ask user which direction to prioritize |
| A critical piece of information cannot be verified | State what you found and what is missing, ask if the user wants to proceed or dig deeper |
| The scope is ambiguous or too broad | Ask a scoping question before investing effort |
| Research is turning up very little | Report what you found so far, ask if the user can provide additional context or alternative keywords |
| User's assumption appears to be incorrect | Politely flag the discrepancy with evidence, ask for confirmation before proceeding |
Format for follow-up questions:
⚠️ Needs clarification: [concise description of the issue] Options: 1. [Option A] 2. [Option B] Which would you prefer, or would you like me to handle it differently?
Error Handling
When a tool fails, follow this protocol — never silently fail or fabricate content:
| Error | Action |
|---|---|
search.py returns empty results | Retry with rephrased keywords or different language, up to 3 attempts. If still empty, inform user and suggest alternative search terms. |
web.py extraction fails (anti-bot, paywall, timeout) | Inform user the page is inaccessible. Try searching for a cached or alternative version. |
youtube.py / yt-dlp fails | Check URL format. If "Sign in to confirm you're not a bot" or timeout: suggest enabling TUN mode proxy, or trying --cookies-from-browser chrome, or using a Bilibili alternative. Report the specific error to user. |
ffmpeg.py fails | Report the error message. Check input format compatibility. Suggest alternative format if applicable. |
| Any unknown error | Run doctor to diagnose, report findings to user, do not guess. |
Core principle: If a tool fails and you cannot recover, tell the user what happened, what you tried, and suggest next steps. Never pretend it succeeded.
Output Format
Strict portable Markdown only. The output must render correctly in any Markdown editor (GitHub, Obsidian, Typora, VS Code, etc.).
Rules
- No HTML tags — no
<br>,<div>,<table>,<sub>,<sup>, or any HTML whatsoever - Table cells must be single-line plain text — no line breaks, no nested lists, no multi-line content inside a cell
- If content does not fit single-line table cells, use a list instead of a table
- Use blank lines before and after headings, tables, code blocks, and block quotes to ensure correct parsing
- Do not use indented code blocks — always use fenced code blocks with triple backticks
Formatting Toolkit
| Element | Usage |
|---|---|
| Bold | Key conclusions, important numbers |
Lists (- or 1.) | Pros/cons, steps, explanations |
✅ ❌ ⚠️ | Supported / not supported / caution |
> quote block | Direct quotes from sources |
` inline code ` | Tool names, commands, technical terms |
Table Example (Use Only When Appropriate)
Tables are for comparing multiple items with short single-line values:
| Product | Price | Offline | Rating |
| ------- | ----- | ------- | ------ |
| A | $99 | ✅ | 4.5/5 |
| B | $199 | ❌ | 4.0/5 |
| C | Free | ✅ | 3.5/5 |Do not use tables when: content is single-column, cells need multi-line text, or structure requires nesting.
Source Citations
Inline: [1], [2], etc.
At the end:
## Sources
[1] [Title](URL) — Key data description
[2] [Title](URL)Context Management
- Long content (>2000 words): Summarize key information after extraction; do not paste raw content into the response
- Subtitles: Download to disk by default — only load into context when the user explicitly asks for content analysis (e.g. "summarize this video", "extract info about X")
- Multiple pages: Synthesize and integrate findings; do not stack raw page dumps
CLI Tools Reference
📁 Working directory: All commands run from~/.agents/skills/skilless/. Thecd ~/.agents/skills/skilless/ &&prefix is shown in full for each command to ensure correct execution.
Search (Exa AI)
cd ~/.agents/skills/skilless/ && uv run scripts/search.py "your query"
cd ~/.agents/skills/skilless/ && uv run scripts/search.py "your query" 10Web Reader (Jina Reader)
cd ~/.agents/skills/skilless/ && uv run scripts/web.py <url>Video / Transcript Extractor
youtube.py — One-step subtitle + metadata extraction (recommended for most cases):
cd ~/.agents/skills/skilless/ && uv run scripts/youtube.py "<url>"yt-dlp direct — Advanced usage (custom formats, audio-only, subtitle listing):
cd ~/.agents/skills/skilless/ && uv run yt-dlp "URL"
cd ~/.agents/skills/skilless/ && uv run yt-dlp --list-subs "URL"
cd ~/.agents/skills/skilless/ && uv run yt-dlp --write-subs --write-auto-subs "URL"
cd ~/.agents/skills/skilless/ && uv run yt-dlp -x --audio-format mp3 "URL"Supported platforms (1700+ via yt-dlp): YouTube, Bilibili, TikTok, Twitter/X, Twitch, Vimeo, Dailymotion, Niconico, Rumble, Odysee, SoundCloud, Reddit, Instagram, Facebook, and many more.
Download path rules:
- Specific project directory (e.g.
~/codes/my-project/) → download to current working directory - Home directory (
~) or empty path → download to~/Downloads/ - Never download to
/tmp— requires special permissions, files may auto-delete
YouTube troubleshooting:
- "Sign in to confirm you're not a bot" or timeout → enable TUN mode proxy, or try
--cookies-from-browser chrome, or use Bilibili as alternative
FFmpeg (Media Converter)
cd ~/.agents/skills/skilless/ && uv run scripts/ffmpeg.py <input> <output>
cd ~/.agents/skills/skilless/ && uv run scripts/ffmpeg.py video.mkv output.mp4
cd ~/.agents/skills/skilless/ && uv run scripts/ffmpeg.py audio.wav output.mp3
cd ~/.agents/skills/skilless/ && uv run scripts/ffmpeg.py input.mp4 output.mp4 -crf 28Supports all common media formats (mp4, mkv, mp3, wav, flac, webm, avi, mov, etc.)
Cross-References
- Need a detailed report? → After completing research, invoke
skilless.ai-writingto produce professional reports, articles, documentation, or any structured written content from your findings - Research goal unclear? → Invoke
skilless.ai-brainstormingto define scope, clarify questions, and explore approaches before starting a deep investigation