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LaunchFast Full Research Loop

by BlockchainHB · GitHub ↗ · v1.0.0
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/install launchfast-full-research-loop
Description
Complete Amazon FBA product research pipeline using the LaunchFast MCP. Runs product research, IP checks, supplier sourcing, and PPC keyword research in sequ...
README (SKILL.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

\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]
Usage Guidance
This skill appears coherent and low-risk: it simply orchestrates four LaunchFast MCP tools and writes a standalone HTML report. Before installing or running it: (1) ensure you have access to the named LaunchFast MCP tools (the skill lists them as prerequisites); (2) confirm the report save path (default is ~/Downloads) so you know where files will be written; (3) be aware the report will reproduce LaunchFast's visual design and brand elements — ensure you have rights/permission if that's a concern; (4) understand that any data the MCP tools access is governed by your platform's MCP integrations (the skill itself asks for no secrets); and (5) if you want stricter controls, review platform logs for the invoked MCP calls or run the skill on a test account first.
Capability Analysis
Type: OpenClaw Skill Name: launchfast-full-research-loop Version: 1.0.0 The skill instructs the agent to save a generated HTML report to a user-specified path (SKILL.md, STEP 1, PHASE 5). This creates a potential arbitrary file write vulnerability if the agent's underlying file system operations do not sanitize the provided path. Additionally, the skill instructs the agent to populate an HTML template with data from external MCP calls (SKILL.md, PHASE 5). Without explicit sanitization of this data before insertion into the HTML, there is a risk of stored Cross-Site Scripting (XSS) if the external data contains malicious HTML/JavaScript. While these are significant vulnerabilities, the skill itself does not contain explicit instructions for malicious actions like data exfiltration or remote code execution, classifying it as suspicious rather than malicious.
Capability Assessment
✓ Purpose & Capability
Name/description match the runtime instructions: it sequences LaunchFast MCP calls for product research, IP checks, supplier sourcing, and PPC keyword research and then produces an HTML report. It does not request unrelated binaries, environment variables, or file-system locations beyond a user-specified report path.
✓ Instruction Scope
SKILL.md confines operations to invoking the four named mcp__launchfast__* tools, extracting results, and writing a standalone HTML report to a user-specified path. It does not instruct reading unrelated system files, environment variables, or sending data to third-party endpoints beyond those MCP calls. Note: it will write a file to the user's file system (default ~/Downloads) — the user should confirm the save path.
✓ Install Mechanism
No install spec and no code files — lowest-risk form (instruction-only). Nothing will be downloaded or written by the skill itself beyond the report file the agent is instructed to create.
✓ Credentials
The skill declares no required environment variables or credentials. The only dependencies are the four LaunchFast MCP tools named in the README, which is appropriate for the described functionality. (Platform-level MCP tool credentials or access controls are external to this skill.)
✓ Persistence & Privilege
always is false and the skill does not request persistent system changes or modify other skills' configs. Autonomous invocation is allowed by default but is not combined with elevated privileges or broad credential access.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install launchfast-full-research-loop
  3. After installation, invoke the skill by name or use /launchfast-full-research-loop
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Complete Amazon FBA research loop with one command. - Runs sequential product research, IP check, supplier sourcing, and PPC keyword research for any product keyword. - Compiles all results into a professionally formatted downloadable HTML report using LaunchFast design guidelines. - Requires all four core LaunchFast MCP skills to operate. - Guides the user through required inputs and reports progress at each phase. - Supports output customization, including report save location and PPC competitor ASINs.
Metadata
Slug launchfast-full-research-loop
Version 1.0.0
License —
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is LaunchFast Full Research Loop?

Complete Amazon FBA product research pipeline using the LaunchFast MCP. Runs product research, IP checks, supplier sourcing, and PPC keyword research in sequ... It is an AI Agent Skill for Claude Code / OpenClaw, with 598 downloads so far.

How do I install LaunchFast Full Research Loop?

Run "/install launchfast-full-research-loop" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is LaunchFast Full Research Loop free?

Yes, LaunchFast Full Research Loop is completely free (open-source). You can download, install and use it at no cost.

Which platforms does LaunchFast Full Research Loop support?

LaunchFast Full Research Loop is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created LaunchFast Full Research Loop?

It is built and maintained by BlockchainHB (@blockchainhb); the current version is v1.0.0.

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