LaunchFast Full Research Loop
/install launchfast-full-research-loop
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 #1a1a1afor 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
\x3C!DOCTYPE html>
\x3Chtml lang="en">
\x3Chead>
\x3Cmeta charset="UTF-8" />
\x3Cmeta name="viewport" content="width=device-width, initial-scale=1.0" />
\x3Ctitle>LaunchFast Research Report — [Keyword] — [Date]\x3C/title>
\x3Cstyle>
* { 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; }
/* Stats grid */
.stats-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(140px, 1fr)); gap: 16px; margin-bottom: 20px; }
.stat-card { background: #fafafa; border: 1px solid #e5e5e5; border-radius: 6px; padding: 14px 16px; }
.stat-card .label { font-size: 11px; font-weight: 600; color: #999; text-transform: uppercase; letter-spacing: 0.05em; margin-bottom: 6px; }
.stat-card .value { font-size: 20px; font-weight: 700; letter-spacing: -0.02em; }
.stat-card .sub { font-size: 12px; color: #666; margin-top: 2px; }
/* Supplier score bar */
.score-bar { display: flex; align-items: center; gap: 8px; }
.score-bar .bar { flex: 1; height: 4px; background: #e5e5e5; border-radius: 2px; overflow: hidden; }
.score-bar .fill { height: 100%; background: #1a1a1a; border-radius: 2px; }
.score-bar .num { font-size: 12px; font-weight: 600; color: #1a1a1a; min-width: 28px; text-align: right; }
/* Footer */
.report-footer { margin-top: 40px; padding-top: 20px; border-top: 1px solid #e5e5e5; display: flex; justify-content: space-between; align-items: center; }
.report-footer .brand-mark { font-size: 13px; font-weight: 600; color: #1a1a1a; }
.report-footer .generated { font-size: 12px; color: #999; }
\x3C/style>
\x3C/head>
\x3Cbody>
\x3Cdiv class="page">
\x3C!-- HEADER -->
\x3Cdiv class="report-header">
\x3Cdiv class="brand">LaunchFast · FBA Research Report\x3C/div>
\x3Ch1>[Keyword] Opportunity Report\x3C/h1>
\x3Cdiv class="meta">Generated [Full Date] · [N] keywords · [N] products analyzed\x3C/div>
\x3C/div>
\x3C!-- VERDICT BANNER -->
\x3Cdiv class="verdict-banner">
\x3Cdiv class="stat">
\x3Cdiv class="verdict-label">Overall Verdict\x3C/div>
\x3Cdiv class="verdict-value">\x3Cspan class="badge badge-[go/investigate/pass]">[GO / INVESTIGATE / PASS]\x3C/span>\x3C/div>
\x3C/div>
\x3Cdiv class="divider">\x3C/div>
\x3Cdiv class="stat">
\x3Cdiv class="stat-label">Opp Score\x3C/div>
\x3Cdiv class="stat-value">[N]/100\x3C/div>
\x3C/div>
\x3Cdiv class="divider">\x3C/div>
\x3Cdiv class="stat">
\x3Cdiv class="stat-label">IP Risk\x3C/div>
\x3Cdiv class="stat-value">\x3Cspan class="badge badge-[low/medium/high]">[LOW/MEDIUM/HIGH]\x3C/span>\x3C/div>
\x3C/div>
\x3Cdiv class="divider">\x3C/div>
\x3Cdiv class="stat">
\x3Cdiv class="stat-label">Suppliers Found\x3C/div>
\x3Cdiv class="stat-value">[N]\x3C/div>
\x3C/div>
\x3Cdiv class="divider">\x3C/div>
\x3Cdiv class="stat">
\x3Cdiv class="stat-label">PPC Keywords\x3C/div>
\x3Cdiv class="stat-value">[N]\x3C/div>
\x3C/div>
\x3C/div>
\x3C!-- PHASE 1: PRODUCT RESEARCH -->
\x3Cdiv class="section">
\x3Cdiv class="section-header">
\x3Cdiv class="section-title">Product Research\x3C/div>
\x3Cdiv class="phase-label">Phase 1\x3C/div>
\x3C/div>
\x3Cdiv class="stats-grid">
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Products Analyzed\x3C/div>
\x3Cdiv class="value">[N]\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Top Revenue\x3C/div>
\x3Cdiv class="value">$[X]k\x3Cspan style="font-size:14px;font-weight:500">/mo\x3C/span>\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Price Range\x3C/div>
\x3Cdiv class="value">$[X]–$[X]\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Avg Reviews\x3C/div>
\x3Cdiv class="value">[N]\x3C/div>
\x3C/div>
\x3C/div>
\x3Ctable>
\x3Cthead>
\x3Ctr>
\x3Cth>#\x3C/th>
\x3Cth>Product\x3C/th>
\x3Cth>Grade\x3C/th>
\x3Cth>Revenue/mo\x3C/th>
\x3Cth>Price\x3C/th>
\x3Cth>Reviews\x3C/th>
\x3Cth>BSR\x3C/th>
\x3C/tr>
\x3C/thead>
\x3Ctbody>
\x3C!-- Repeat for top 5–10 products -->
\x3Ctr>
\x3Ctd style="color:#999">1\x3C/td>
\x3Ctd>[Product title truncated to 60 chars]\x3C/td>
\x3Ctd>\x3Cspan class="grade grade-[a/b/c]">[Grade]\x3C/span>\x3C/td>
\x3Ctd>$[X,XXX]\x3C/td>
\x3Ctd>$[XX.XX]\x3C/td>
\x3Ctd>[X,XXX]\x3C/td>
\x3Ctd>#[X,XXX]\x3C/td>
\x3C/tr>
\x3C/tbody>
\x3C/table>
\x3Cdiv class="callout" style="margin-top:20px">
\x3Cstrong>Key finding:\x3C/strong> [1-2 sentence insight about the market — grade distribution, revenue consistency, competitive dynamics]
\x3C/div>
\x3C/div>
\x3C!-- PHASE 2: IP CHECK -->
\x3Cdiv class="section">
\x3Cdiv class="section-header">
\x3Cdiv class="section-title">IP & Trademark Check\x3C/div>
\x3Cdiv class="phase-label">Phase 2\x3C/div>
\x3C/div>
\x3Cdiv class="stats-grid">
\x3Cdiv class="stat-card">
\x3Cdiv class="label">IP Risk Level\x3C/div>
\x3Cdiv class="value">\x3Cspan class="badge badge-[low/medium/high]">[LOW/MEDIUM/HIGH]\x3C/span>\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Active Trademarks\x3C/div>
\x3Cdiv class="value">[N]\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Patent Hits\x3C/div>
\x3Cdiv class="value">[N]\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Assessment\x3C/div>
\x3Cdiv class="value">\x3Cspan class="badge badge-[clear/caution/blocked]">[CLEAR/CAUTION/BLOCKED]\x3C/span>\x3C/div>
\x3C/div>
\x3C/div>
\x3C!-- If trademarks found, show table -->
\x3Ctable>
\x3Cthead>
\x3Ctr>\x3Cth>Trademark\x3C/th>\x3Cth>Owner\x3C/th>\x3Cth>Status\x3C/th>\x3Cth>Class\x3C/th>\x3C/tr>
\x3C/thead>
\x3Ctbody>
\x3Ctr>
\x3Ctd>[Trademark name]\x3C/td>
\x3Ctd>[Owner]\x3C/td>
\x3Ctd>[Live/Dead]\x3C/td>
\x3Ctd>[Class number]\x3C/td>
\x3C/tr>
\x3C/tbody>
\x3C/table>
\x3Cdiv class="callout" style="margin-top:20px">
\x3Cstrong>Recommendation:\x3C/strong> [Clear action — e.g. "No direct conflicts found. Avoid branding your product as [word] to stay safe." or "HIGH risk — consult an IP attorney before proceeding."]
\x3C/div>
\x3C/div>
\x3C!-- PHASE 3: SUPPLIER RESEARCH -->
\x3Cdiv class="section">
\x3Cdiv class="section-header">
\x3Cdiv class="section-title">Alibaba Supplier Research\x3C/div>
\x3Cdiv class="phase-label">Phase 3\x3C/div>
\x3C/div>
\x3Ctable>
\x3Cthead>
\x3Ctr>
\x3Cth>#\x3C/th>
\x3Cth>Supplier\x3C/th>
\x3Cth>Score\x3C/th>
\x3Cth>Price Range\x3C/th>
\x3Cth>MOQ\x3C/th>
\x3Cth>Years\x3C/th>
\x3Cth>Verified\x3C/th>
\x3C/tr>
\x3C/thead>
\x3Ctbody>
\x3C!-- Repeat for top 5 suppliers -->
\x3Ctr>
\x3Ctd style="color:#999">1\x3C/td>
\x3Ctd>[Company Name]\x3C/td>
\x3Ctd>
\x3Cdiv class="score-bar">
\x3Cdiv class="bar">\x3Cdiv class="fill" style="width:[score]%">\x3C/div>\x3C/div>
\x3Cdiv class="num">[score]\x3C/div>
\x3C/div>
\x3C/td>
\x3Ctd>$[X.XX]–$[X.XX]\x3C/td>
\x3Ctd>[N] units\x3C/td>
\x3Ctd>[N] yrs\x3C/td>
\x3Ctd>[Gold · TA · Assessed]\x3C/td>
\x3C/tr>
\x3C/tbody>
\x3C/table>
\x3Cdiv class="callout" style="margin-top:20px">
\x3Cstrong>Top pick:\x3C/strong> [Company Name] — [reason: highest score, most verifications, best price range for target margin]
\x3C/div>
\x3C/div>
\x3C!-- PHASE 4: PPC KEYWORDS -->
\x3Cdiv class="section">
\x3Cdiv class="section-header">
\x3Cdiv class="section-title">PPC Keyword Intelligence\x3C/div>
\x3Cdiv class="phase-label">Phase 4\x3C/div>
\x3C/div>
\x3Cdiv class="stats-grid">
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Total Keywords\x3C/div>
\x3Cdiv class="value">[N]\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Tier 1 (Priority)\x3C/div>
\x3Cdiv class="value">[N]\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Tier 2 (Growth)\x3C/div>
\x3Cdiv class="value">[N]\x3C/div>
\x3C/div>
\x3Cdiv class="stat-card">
\x3Cdiv class="label">Tier 3 (Discovery)\x3C/div>
\x3Cdiv class="value">[N]\x3C/div>
\x3C/div>
\x3C/div>
\x3Ctable>
\x3Cthead>
\x3Ctr>\x3Cth>#\x3C/th>\x3Cth>Keyword\x3C/th>\x3Cth>Search Vol\x3C/th>\x3Cth>Tier\x3C/th>\x3Cth>Match Types\x3C/th>\x3Cth>Est. CPC\x3C/th>\x3C/tr>
\x3C/thead>
\x3Ctbody>
\x3C!-- Top 20 keywords -->
\x3Ctr>
\x3Ctd style="color:#999">1\x3C/td>
\x3Ctd>[keyword]\x3C/td>
\x3Ctd>[X,XXX]\x3C/td>
\x3Ctd>Tier 1\x3C/td>
\x3Ctd>Exact · Phrase\x3C/td>
\x3Ctd>$[X.XX]\x3C/td>
\x3C/tr>
\x3C/tbody>
\x3C/table>
\x3Cdiv class="callout" style="margin-top:20px">
\x3Cstrong>Campaign strategy:\x3C/strong> [Brief recommendation — e.g. "Start with the 12 Tier 1 exact-match keywords at $0.90 bid. Run broad on Tier 3 for discovery data. Revisit in 2 weeks."]
\x3C/div>
\x3C/div>
\x3C!-- FOOTER -->
\x3Cdiv class="report-footer">
\x3Cdiv class="brand-mark">LaunchFast\x3C/div>
\x3Cdiv class="generated">Generated [Date] · Data via LaunchFast MCP\x3C/div>
\x3C/div>
\x3C/div>
\x3C/body>
\x3C/html>
Fill ALL placeholder values ([...]) with real data from the research phases.
Save the complete file to the path from Step 1.
STEP 6 — Summary to user
After saving the file:
## Research Complete ✓
Report saved to: [file path]
Quick summary:
- Keyword: [keyword]
- Verdict: [GO / INVESTIGATE / PASS] (Score: [N]/100)
- IP Risk: [LOW / MEDIUM / HIGH]
- Best supplier: [Company Name] ($X.XX–$X.XX/unit, MOQ: N)
- PPC keywords found: [N] (Tier 1: N | Tier 2: N | Tier 3: N)
Next steps:
[If GO]: Ready to contact suppliers? Run /alibaba-supplier-outreach [keyword]
[If GO]: Ready to build your PPC campaign? Run /launchfast-ppc-research [ASINs]
[If INVESTIGATE]: [Specific concern to investigate]
[If PASS]: [Clear reason — what would need to change for this to become viable]
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install launchfast-full-research-loop - 安装完成后,直接呼叫该 Skill 的名称或使用
/launchfast-full-research-loop触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
LaunchFast Full Research Loop 是什么?
Complete Amazon FBA product research pipeline using the LaunchFast MCP. Runs product research, IP checks, supplier sourcing, and PPC keyword research in sequ... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 598 次。
如何安装 LaunchFast Full Research Loop?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install launchfast-full-research-loop」即可一键安装,无需额外配置。
LaunchFast Full Research Loop 是免费的吗?
是的,LaunchFast Full Research Loop 完全免费(开源免费),可自由下载、安装和使用。
LaunchFast Full Research Loop 支持哪些平台?
LaunchFast Full Research Loop 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 LaunchFast Full Research Loop?
由 BlockchainHB(@blockchainhb)开发并维护,当前版本 v1.0.0。