| name | research |
| description | Research any topic — current events, products, people, concepts, comparisons — using Web Search MCP 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 8 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 — 7 Web Search Tools
Tier 1 — Broad Discovery
| Tool | What It Does | When To Use |
|---|
search_web | DuckDuckGo web/news search | First pass: news, background, official sources |
search_web (domain) | DuckDuckGo scoped to a domain | Targeted docs: docs.python.org, react.dev, RFCs |
search_exa | Exa AI semantic search | Deep topic research, filtered by category/domains |
fetch_web_page | Clean HTML-to-markdown from a URL (Exa fallback for JS-heavy pages) | Read articles, changelogs, specs, papers |
Tier 2 — Community & Social Signal
| Tool | What It Does | When To Use |
|---|
search_reddit | Reddit via RSS + shreddit enrichment | Real-user discussions, product feedback, niche opinions |
search_hackernews | HN via Algolia + comment enrichment | Tech debate, architectural analysis, deep critical takes |
search_github | GitHub Issues/PR search | Upstream discussions, feature requests, deprecation notices |
search_x | X/Twitter via 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.
