| name | research |
| description | Research any topic — current events, products, people, concepts, comparisons — for evidence gathering and structured multi-source synthesis. |
Deep Research
Operating Principle
Research is breadth-first, then depth-first. Start wide to map the landscape, then dive into the highest-signal sources. Do not jump to a single source type and call it done — each platform reveals a different facet of the topic.
Good research answers not just what happened, but who is saying it, how confident the evidence is, and what the competing narratives are.
Cross-source corroboration: A claim found in 3+ independent sources is stronger than any single source. Multi-platform coverage is the highest-confidence signal.
Internalize the research first: Ground your synthesis in the ACTUAL research content, not your pre-existing knowledge. If sources talk about "ClawdBot" and you assumed "Claude Code", do not conflate them.
Important: What the MCP Handles vs What You Do
This skill uses the web-search MCP server. Search, dedup, clustering, and stats computation, here you do all that synthesis work manually as you read tool results.
The MCP gives you:
- Search and retrieval across 10 tools covering web, social, academic, and developer platforms
- Clean extracted content from URLs
- Rich engagement data (upvotes, comments, views) from community platforms
You are responsible for:
- Running searches sequentially (no engine to fan out in parallel)
- Counting and tracking which claims came from which source
- Spotting patterns and clusters as you read
- Computing stats manually from result sets
- Noticing "X Reply Clusters" in Reddit threads yourself
Cost of comparison mode: Comparing 2 entities means roughly 2x the tool calls (~8-12 per entity). Plan your turn budget accordingly. For 3-way comparisons, consider doing a single focused comparison instead of exhaustive per-entity research.
Tool Reference — 10 Web Search Tools
Tier 1 — Broad Discovery & Reference
| Tool | What It Does | When To Use |
|---|
mcp__plugin_web-search_web-search_search_web | DuckDuckGo or Exa web/news search (via provider param) | First pass: news, background, official sources |
mcp__plugin_web-search_web-search_search_web (domain) | DuckDuckGo (site:) or Exa (include_domains) scoped to a domain | Targeted docs: docs.python.org, react.dev, RFCs |
mcp__plugin_web-search_web-search_fetch_page | Clean HTML-to-markdown extraction from URLs | Read articles, changelogs, specs, papers |
mcp__plugin_web-search_web-search_search_wikipedia | Full article text via MediaWiki API | Factual summaries, background research, citations |
mcp__plugin_web-search_web-search_search_arxiv | Academic paper search w/ Lucene field prefixes | Research papers, literature reviews, citations |
Tier 2 — Community & Social Signal
| Tool | What It Does | When To Use |
|---|
mcp__plugin_web-search_web-search_search_reddit | Reddit via RSS + shreddit enrichment | Real-user discussions, product feedback, niche opinions |
mcp__plugin_web-search_web-search_search_hackernews | HN via Algolia + comment enrichment | Tech debate, architectural analysis, deep critical takes |
mcp__plugin_web-search_web-search_get_github_issue | Full GitHub Issue/PR thread with comments | Complete conversation context sorted by reactions |
mcp__plugin_web-search_web-search_search_x | X/Twitter via Xquik API or Bird CLI | Real-time announcements, expert takes, breaking news |
Source Weighting
| Source | Signal | Best For |
|---|
| Official docs, specs, papers | ★★★★★ | Ground truth, APIs, specifications |
| GitHub (code, issues, releases) | ★★★★☆ | Open-source projects, technical evidence |
| Hacker News comments | ★★★★☆ | Tech consensus, critical analysis |
| Web search (blogs, news) | ★★★☆☆ | Broad coverage, multiple viewpoints |
| Reddit discussions | ★★★☆☆ | Real-user opinions, practical experience |
| X/Twitter | ★★☆☆☆ | Real-time signal, expert takes (high noise) |
Cross-platform corroboration beats any single source type. A claim on Reddit + HN + a blog is stronger than a single whitepaper.
OUTPUT CONTRACT
LAW 1 — Badge on line 1. 🔍 deep-research · {YYYY-MM-DD}. One blank line, then report. No title, no preamble.
LAW 2 — NO em-dashes (—) or en-dashes (–). Use - (single hyphen with spaces). Everywhere. Exception: quoted content.
LAW 3 — NO ## section headers in body. No ## Key Findings, no ## Analysis. Narrative uses bold-lead-in paragraphs. Exceptions: comparison mode (see below).
LAW 4 — Bold-lead-in paragraphs. Every narrative paragraph begins with **Headline** - .
LAW 5 — Inline markdown links. [name](url) for every citation. Raw URLs never shown. Priority:
[@handle](https://x.com/handle) > [r/sub](https://reddit.com/r/sub) > [channel](url) > [HN](url) > [publication](url)- Never emit broken
[name]().
LAW 6 — NO trailing Sources block. The Sources consulted: list is INSIDE the report. Nothing after the invitation.
Pre-Flight: Keyword Trap Detection
Before any searches, check for these failure classes:
Class 1 — Demographic shopping: gift for 42 year old man → ask about hobbies/relationship/budget, or reframe to gifts for men in their 40s + scope to gift subreddits.
Class 2 — Numeric keyword trap: 42 collides with unrelated content (Jackie Robinson, Hitchhiker's). Strip numbers from queries unless load-bearing ("GPT-4" is fine).
Class 3 — Overly-literal phrasing: how to use Docker → social posts use "my Docker setup", "Docker Compose tip", not tutorial phrasing. Reframe to discussion keywords.
Class 4 — Generic single noun: sneakers, coffee, bread → no anchor, pure noise. Ask for specificity.
Resolution Phase
Before community searches, resolve platform-scoped targeting. This is where you do manual lookups that drastically improve signal quality.
Subreddits: Run search_web "{topic} subreddit" to find 3-5 relevant subreddits. For product/tool topics, also add 2-3 category-peer subs from the table below (where cross-product discussion actually happens):
| Category | Peer Subs |
|---|
| AI image gen | StableDiffusion, midjourney, dalle2, aiArt |
| AI video gen | aivideo, StableDiffusion, runwayml, singularity |
| AI music gen | SunoAI, udiomusic, aimusic |
| AI coding | ChatGPTCoding, LocalLLaMA, singularity |
| AI chat models | LocalLLaMA, ChatGPT, ClaudeAI, singularity |
| SaaS/productivity | SaaS, productivity, Entrepreneur |
X handles: For person/product topics, run search_web "{topic} X handle" for the primary handle and 1-2 commentators.
GitHub: For developer topics, resolve github.com/{handle}. For projects, resolve owner/repo.
Use these resolved values when calling community search tools (e.g., search_reddit with the subreddits parameter). Scoped searches produce dramatically better signal than keyword-only searches.
Research Workflow
Phase 1 — Broad Discovery (Tier 1)
Run 2-3 searches to map the landscape. Vary the angle:
search_web "{topic} 2026"
search_web "{topic}" (news mode)
search_web "{topic}" domain="docs.python.org"
From results, pick 1-2 long-form sources to deep-read later.
Phase 2 — Community Mining (Tier 2)
Mine 3-4 platforms. Use resolved handles/subreddits/repos to scope. The tool results come with engagement data — use it:
| Platform | How | Look For |
|---|
search_reddit | Topic + subreddits parameter | Real experiences, complaints, workarounds. Top comments are highest-signal. |
search_hackernews | Topic + keywords | The why behind the news. Comments from domain experts. |
search_github | Topic as issue/PR keyword | Roadmap signals, breaking changes, community wishlists. |
search_x | Topic + resolved handles | Real-time reactions, expert threads, announcements. |
Per-platform notes (read before searching):
- Reddit: When you see a thread where someone asked for recommendations and multiple independent replies converged on the same answer, note it — this "Reply Cluster" pattern is the strongest form of community endorsement. The
search_reddit tool returns top comments with scores; read them.
- HN: The
search_hackernews result includes top_comments and comment_insights fields — these are pre-extracted for you. Use them.
- GitHub:
search_github returns state (open/closed), labels, engagement.reactions, and top_comments. Look for closed PRs to see how something was fixed.
- X: No engagement enrichment in the current response. Treat X as real-time signal; cross-reference against other sources.
Phase 3 — Synthesis (You Do This Manually)
After reading all results, answer these questions:
- Corroborated? — same claim in 3+ independent sources → high confidence
- Contradicted? — sources disagree → note each camp
- Single-sourced? — interesting but lower confidence → flag it
- Missing? — questions the evidence doesn't answer
Output Format
General / News
🔍 deep-research · 2026-06-10
**{Headline}** - {1-2 sentences}, per [@handle](url)
**{Headline}** - {1-2 sentences}, per [r/sub](url)
**{Headline}** - {1-2 sentences}, per [publication](url)
Patterns from the research:
1. {Pattern} — per [source](url)
2. {Pattern} — per [source](url)
3. {Pattern} — per [source](url)
Gaps & uncertainty:
- {What isn't known or weakly supported}
Sources consulted:
- [name](url)
- [name](url)
---
Some things you could ask next:
- {Specific follow-up based on the most discussed finding}
- {Deeper dive into a contested angle}
Recommendations
Rank by signal quality, not mention count. This is the most common failure mode in recommendation research — leading with "Python has 15 mentions" when the actual story is a domain expert switching to Go.
| Signal | Weight | Example |
|---|
| Practitioner testimony with specifics | Highest | "I use X for Y and here's why" |
| Expert defection | High | Domain insider publicly switching |
| Measurable benchmark | High | "43.7% latency win" |
| Reasoned comparison | Medium | Side-by-side with tradeoffs |
| Multiple unaffiliated voices concur | Medium | Various people saying the same thing |
| Descriptive mention (exists) | Low | "X is a Python framework" |
| Promotional / bootcamp | Skip | "Comment CODE for my course" |
Lead with the 30-day delta, not the status-quo baseline. A status-quo leader with no new movement is a footer item.
Output:
🔍 deep-research · 2026-06-10
Recommended (ranked by signal quality):
**[Pick 1]** - why it's the top recommendation
- Evidence: {specific quote, benchmark, or defection}
- Best for: {use case}
- Voices: {@handles, r/subs}
**[Pick 2]** - ...
**[Pick 3]** - ...
Also mentioned (exists, not specifically recommended): {name} ({why it's a mention, not a pick})
Gaps & uncertainty:
- ...
Sources consulted:
- [name](url)
Comparison (X vs Y)
Cost warning: Each entity requires its own Phase 1-2 search cycle. For 2 entities expect ~10-14 tool calls total. Use the subreddits parameter and resolved handles to scope early and avoid wasted searches.
🔍 deep-research · 2026-06-10
# {A} vs {B}: What the Research Says
## Quick Verdict
{Thesis sentence. Comparable metrics. Community framing quote.}
## {Entity 1}
Strengths:
- {per [source](url)}
- ...
Weaknesses:
- {per [source](url)}
## {Entity 2}
{Same structure}
## Head-to-Head
| Dimension | {A} | {B} |
| ---------- | --- | --- |
| What it is | ... | ... |
| Key signal | ... | ... |
| Best for | ... | ... |
## The Bottom Line
{A} if {use case}. {B} if {use case}.
Sources consulted:
- [name](url)
The ## Quick Verdict, ## {Entity}, ## Head-to-Head, ## The Bottom Line headers are exceptions to LAW 3 — allowed only in comparison mode.
Pre-Presentation Self-Check
- Badge on line 1. Nothing above it.
- Bold headlines on every narrative paragraph.
- No em-dashes — all replaced with
-.
- No
## headers in body (comparison mode exempted for the 4 allowed headers).
- Inline markdown links — every name/handle is
[text](url). No raw URLs, no [name]().
- No trailing Sources block —
Sources consulted: is inside the report. Nothing after invitation.
- Research grounded in actual sources — not what you already knew.
Max ONE regeneration. If still broken, emit the best version and note the gap.
Post-Research Mode
After delivering the report, treat yourself as an expert for the rest of the conversation. Do NOT run new searches on the same topic — answer from what you gathered. Only research again if the user asks about a different topic.
Edge Cases
- Too broad: Narrow with one clarifying question, or auto-scope to the most common interpretation. Mention the choice.
- Zero results: Widen the query. Check for typos. If still empty: "no significant discussion found."
- Conflicting evidence: Present both sides with source authority notes. Don't cherry-pick.
- Breaking news: Use
search_web (news mode) + search_x. Timestamp everything. Flag volatility.
- SEO pollution: Add
-site:spam-site.com exclusions. Prefer search_web with domain="..." on known-good domains. Community platforms (Reddit, HN) resist SEO gaming.
