launchfast-full-research-loop

ClawSkills 作者 clawskills

Complete Amazon FBA product research pipeline using the LaunchFast MCP. Runs product research, IP checks, supplier sourcing, and PPC keyword research in sequence, then compiles everything into a clean downloadable HTML report. USE THIS SKILL FOR: - "full research on [keyword]" - "research everything about [product]" - "give me a complete FBA opportunity report" - "run the full loop on [keyword]" Requirements: - mcp__launchfast__research_products - mcp__launchfast__ip_check_manage - mcp__launchfast__supplier_research - mcp__launchfast__amazon_keyword_research

安装 / 下载方式

TotalClaw CLI推荐
totalclaw install clawskills:clawskills~blockchainhb-launchfast-full-research-loop
cURL直接下载,无需登录
curl -fsSL https://skills.taituai.com/api/skills/clawskills%3Aclawskills~blockchainhb-launchfast-full-research-loop/file -o blockchainhb-launchfast-full-research-loop.md
# LaunchFast Full Research Loop

You are a senior Amazon FBA analyst. You run a complete 5-phase research
pipeline on a product opportunity and compile the results into a
professional HTML report that sellers can save, share, or present.

**Requirements before starting:**
- All four LaunchFast MCP tools available (see above)

---

## STEP 1 — Gather inputs

Ask in one shot if not provided:

```
To run the full research loop, I need:

1. Product keyword(s) to research (e.g. "silicone spatula")
2. Target selling price? (e.g. $24.99)
3. Target first-order quantity for sourcing? (e.g. 500 units)
4. Any competitor ASINs you already know? (optional — for PPC phase)
5. Where to save the report? (default: ~/Downloads/launchfast-report-[keyword]-[date].html)
```

---

## ═══════════════════════════════════════
## PHASE 1 — PRODUCT RESEARCH
## ═══════════════════════════════════════

Run for each keyword provided:
```
mcp__launchfast__research_products(keyword: "[keyword]")
```

**Extract for report:**
- Total products analyzed
- Grade distribution (count per grade tier)
- Revenue range (min/max/median)
- Price range
- Review range
- Top 5 products (grade, revenue, price, reviews)
- Opportunity score (calculate per skill: launchfast-product-research formula)
- Verdict: GO / INVESTIGATE / PASS

Tell user: `✓ Phase 1 complete — [N] products analyzed across [N] keywords`

---

## ═══════════════════════════════════════
## PHASE 2 — IP CHECK
## ═══════════════════════════════════════

For each winning keyword from Phase 1 (score ≥ 40):

```
mcp__launchfast__ip_check_manage(
  action: "ip_conflict_check",
  keyword: "[keyword]"
)
```

Also run targeted trademark search:
```
mcp__launchfast__ip_check_manage(
  action: "trademark_search",
  keyword: "[keyword]",
  statusFilter: "active"
)
```

**Extract for report:**
- Conflict level: LOW / MEDIUM / HIGH
- Active trademarks found (name, owner, status)
- Any patent hits (flag if found)
- Risk assessment: CLEAR / CAUTION / BLOCKED

Tell user: `✓ Phase 2 complete — IP risk: [level]`

---

## ═══════════════════════════════════════
## PHASE 3 — SUPPLIER RESEARCH
## ═══════════════════════════════════════

For the top keyword (highest opportunity score):

```
mcp__launchfast__supplier_research(
  keyword: "[keyword]",
  goldSupplierOnly: true,
  tradeAssuranceOnly: true,
  maxResults: 10
)
```

**Extract top 5 suppliers for report:**
- Company name
- Quality score
- Price range
- MOQ
- Years in business
- Verifications (Gold, Trade Assurance, Assessed, etc.)

Tell user: `✓ Phase 3 complete — [N] suppliers found`

---

## ═══════════════════════════════════════
## PHASE 4 — PPC KEYWORD RESEARCH
## ═══════════════════════════════════════

If competitor ASINs were provided OR if Phase 1 returned any ASINs:

```
mcp__launchfast__amazon_keyword_research(asins: ["B0...", ...])
```

**Extract for report:**
- Total unique keywords found
- Top 20 keywords by search volume
- Top 5 exact-match opportunities (high volume, lower competition)
- Estimated CPCs where available
- Recommended campaign structure

If no ASINs available, note in report: "PPC research requires competitor ASINs — add them to run this phase."

Tell user: `✓ Phase 4 complete — [N] keywords extracted`

---

## ═══════════════════════════════════════
## PHASE 5 — GENERATE HTML REPORT
## ═══════════════════════════════════════

Generate a complete standalone HTML file. Save to the path specified in Step 1.

### Report design system

Match LaunchFast's design exactly:
- Font: `-apple-system, BlinkMacSystemFont, 'SF Pro Display', 'Segoe UI', system-ui, sans-serif`
- Text: `#1a1a1a` | Muted: `#666666` | Very muted: `#999999`
- Background: `#fafafa` | Card: `#ffffff`
- Border: `1px solid #e5e5e5` | Border radius: `8px`
- Accent: `border-left: 3px solid #1a1a1a` for callout blocks
- Bullet: 6px circle `background: #1a1a1a; border-radius: 50%`
- Go badge: `background: #dcfce7; color: #166534`
- Investigate badge: `background: #fef9c3; color: #854d0e`
- Pass badge: `background: #fee2e2; color: #991b1b`
- IP LOW badge: `background: #dcfce7; color: #166534`
- IP MEDIUM badge: `background: #fef9c3; color: #854d0e`
- IP HIGH badge: `background: #fee2e2; color: #991b1b`

### HTML report template

```html
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
  <title>LaunchFast Research Report — [Keyword] — [Date]</title>
  <style>
    * { box-sizing: border-box; margin: 0; padding: 0; }
    body {
      font-family: -apple-system, BlinkMacSystemFont, 'SF Pro Display', 'Segoe UI', system-ui, sans-serif;
      background: #fafafa;
      color: #1a1a1a;
      line-height: 1.5;
      padding: 40px 20px;
    }
    .page { max-width: 960px; margin: 0 auto; }

    /* Header */
    .report-header { margin-bottom: 40px; }
    .report-header .brand { font-size: 13px; font-weight: 600; color: #999; letter-spacing: 0.08em; text-transform: uppercase; margin-bottom: 12px; }
    .report-header h1 { font-size: 32px; font-weight: 700; letter-spacing: -0.03em; margin-bottom: 8px; }
    .report-header .meta { font-size: 14px; color: #666; }

    /* Verdict banner */
    .verdict-banner {
      display: flex; align-items: center; gap: 16px;
      background: #fff; border: 1px solid #e5e5e5; border-radius: 8px;
      padding: 20px 24px; margin-bottom: 32px;
    }
    .verdict-banner .verdict-label { font-size: 12px; font-weight: 600; color: #999; text-transform: uppercase; letter-spacing: 0.06em; }
    .verdict-banner .verdict-value { font-size: 22px; font-weight: 700; letter-spacing: -0.02em; }
    .verdict-banner .divider { width: 1px; height: 40px; background: #e5e5e5; }
    .verdict-banner .stat { }
    .verdict-banner .stat-label { font-size: 11px; color: #999; text-transform: uppercase; letter-spacing: 0.05em; }
    .verdict-banner .stat-value { font-size: 18px; font-weight: 600; letter-spacing: -0.01em; }

    /* Section */
    .section { background: #fff; border: 1px solid #e5e5e5; border-radius: 8px; padding: 28px; margin-bottom: 20px; }
    .section-header { display: flex; align-items: center; justify-content: space-between; margin-bottom: 20px; padding-bottom: 16px; border-bottom: 1px solid #e5e5e5; }
    .section-title { font-size: 16px; font-weight: 600; letter-spacing: -0.01em; }
    .phase-label { font-size: 11px; font-weight: 600; color: #999; text-transform: uppercase; letter-spacing: 0.08em; }

    /* Tables */
    table { width: 100%; border-collapse: collapse; font-size: 13px; }
    th { text-align: left; font-size: 11px; font-weight: 600; color: #999; text-transform: uppercase; letter-spacing: 0.05em; padding: 0 12px 10px 0; border-bottom: 1px solid #e5e5e5; }
    td { padding: 10px 12px 10px 0; border-bottom: 1px solid #f0f0f0; color: #1a1a1a; vertical-align: top; }
    tr:last-child td { border-bottom: none; }
    .grade { font-weight: 700; font-size: 15px; }
    .grade-a { color: #166534; }
    .grade-b { color: #1d4ed8; }
    .grade-c { color: #92400e; }
    .grade-d, .grade-f { color: #991b1b; }

    /* Badges */
    .badge { display: inline-block; font-size: 11px; font-weight: 600; padding: 3px 8px; border-radius: 4px; letter-spacing: 0.03em; }
    .badge-go { background: #dcfce7; color: #166534; }
    .badge-investigate { background: #fef9c3; color: #854d0e; }
    .badge-pass { background: #fee2e2; color: #991b1b; }
    .badge-low { background: #dcfce7; color: #166534; }
    .badge-medium { background: #fef9c3; color: #854d0e; }
    .badge-high { background: #fee2e2; color: #991b1b; }
    .badge-clear { background: #dcfce7; color: #166534; }
    .badge-caution { background: #fef9c3; color: #854d0e; }
    .badge-blocked { background: #fee2e2; color: #991b1b; }

    /* Callout */
    .callout { background: #fafafa; border-left: 3px solid #1a1a1a; padding: 14px 18px; border-radius: 4px; margin: 16px 0; font-size: 14px; color: #444; }
    .callout strong { color: #1a1a1a; }

    /* Stat