| name | gauthier-thiry-leadfactory-free-skills |
| description | Public no-key LeadFactory workflow for Meta Ads research deliverables. Deploys up to 50 parallel sub-agents to research markets, competitors, ICPs, and ad patterns. Outputs a rich master CSV (opportunities + ICP matrix + deep search recap) plus strategy and creative brief. Use when the user wants Gauthier Thiry / LeadFactory free skills, deep market research, public Meta Ads Library competitor research, a rich Excel/CSV dataset, a strategy document, a static creative brief, or a Desktop delivery folder without private LeadFactory tools, paid API keys, database injection, client files, VSL scripts, or proprietary creative generation. |
Gauthier Thiry LeadFactory Free Skills
Public, simplified LeadFactory pipeline for people who want the research and strategy layer of a Meta Ads launch without private infrastructure.
This skill deploys up to 50 parallel sub-agents across market awareness, competitor research, ICP profiling, ad pattern analysis, and opportunity synthesis. It produces a rich master CSV and a full strategy package on the user's Desktop.
Final Deliverables
~/Desktop/LeadFactory-Free-Skills-{project-slug}/
00-input/brief.md
01-deep-search/01-market-awareness.md
01-deep-search/02-competitor-research.md
01-deep-search/03-psychographic.md
02-meta-ads-library/data.csv
02-meta-ads-library/analysis.md
03-strategy/strategy.md
04-creative-brief/creative-brief.md
05-master-output/master-research.csv ← rich CSV (all research in one file)
DELIVERY-MANIFEST.md
The master-research.csv is the primary output: a single enriched spreadsheet combining all research signals — market data, competitor profiles, ICP segments, white spaces, and prioritized ad angles — ready to import into Excel, Google Sheets, or Airtable.
Non-Negotiables
- Never request or use paid API keys, service-role keys, private database credentials, CRM access, internal apps, private repos, or client folders.
- Never copy real LeadFactory client deliverables, PDFs, DOCX files, logs, state files, generated media, private emails, internal paths, or proof assets.
- Do not generate full VSL scripts, long-form sales letters, or proprietary script packs. Only create strategy, angle rationale, static creative brief, and short ad concept copy.
- Use public web research and public Meta Ads Library pages only. Do not bypass login, paywalls, rate limits, or platform restrictions.
- If public scraping fails, create a transparent fallback CSV from manually visible ad URLs, user-provided screenshots, pasted ad text, or public landing pages. Label it as fallback.
- Save final output on the user's Desktop, not inside a private LeadFactory project folder.
Inputs
Collect or infer these fields before starting:
project_name: brand or offer name.market: niche and geography.offer: product/service, price range if public, core promise.target_avatar: buyer profile.competitors: 3–8 public competitor brand/page names or Meta Ads Library URLs.traffic_goal: lead form, booking call, waitlist, audit, or lead magnet.tone: direct, premium, educational, founder-led, etc.
If any critical field is missing, ask one concise grouped question and continue with reasonable defaults once answered.
Workspace
Create a Desktop folder first:
python3 skills/gauthier-thiry-leadfactory-free-skills/scripts/create_workspace.py \
--project "Project Name"
50-Agent Research Architecture
Launch sub-agents in parallel batches. Each agent has a focused mandate and returns structured findings that feed the master CSV.
Batch 1 — Market Foundation (5 agents)
| Agent | Mandate |
|---|
| M1 — Market Size | TAM, SAM, SOM estimates. Growth rate, macro trends, seasonality. Public sources (Statista, Grand View, IBISWorld free previews, industry reports). |
| M2 — Pricing Landscape | Price bands across the market. Entry / mid / premium segments. Price anchors used in ads. |
| M3 — Regulatory & Compliance | Platform ad policies (Meta, TikTok) for this niche. Sensitive categories, banned claims, compliance constraints. |
| M4 — Trend Signals | Google Trends, TikTok trending sounds/hashtags, Reddit hot threads, rising search queries. 6-month window. |
| M5 — Channel Map | Which channels are saturated vs. underused: Meta, TikTok Shop, Google, YouTube, email, influencer. |
Batch 2 — Competitor Deep Dives (up to 20 agents, one per competitor)
For each competitor brand provided (max 20), launch one agent:
| Sub-agent | Mandate |
|---|
| C1…C20 — Competitor {N} | Public website: hero offer, price, brand promise, ICP signals. Meta Ads Library: estimated active ad count, top angles, hook patterns, visual style, CTA. TikTok/Instagram presence. Key strengths, weaknesses, threat level (HIGH / MEDIUM / LOW). |
Each competitor agent returns a structured row for data.csv plus narrative notes.
Batch 3 — ICP Segments (10 agents)
| Agent | Mandate |
|---|
| ICP1 — Primary Persona | Demographics, psychographics, day-in-the-life, top 3 pain points, primary motivation to buy, main objection, preferred content format. |
| ICP2 — Secondary Persona | Alternative buyer segment — different age, context, or use case. Same fields. |
| ICP3 — Reddit Deep Dive | Subreddits relevant to the niche. Top threads, recurring complaints, vocabulary used ("they say X when they mean Y"), trust signals that work. |
| ICP4 — Review Mining | 1-star and 5-star review analysis from public sources (Amazon, Trustpilot, Google Reviews, App Store). Patterns in language, specific words that recur. |
| ICP5 — Objection Map | Top 5 objections to purchase in this category. For each: objection text → counter-argument → ad angle that addresses it. |
| ICP6 — Awareness Levels | Map the market across Eugene Schwartz's 5 stages (Unaware → Most Aware). Where does the bulk of cold traffic sit? Which stage to target first? |
| ICP7 — TikTok Audience Signals | TikTok hashtag audiences, FYP content patterns, creator types that resonate, comment sentiment on competitor videos. |
| ICP8 — Seasonal Triggers | When does this ICP buy? Events, seasons, life triggers (new year, back to school, pay day, etc.) that drive purchase intent. |
| ICP9 — Cultural / Geo Signals | If multi-market: cultural nuances, localization needs, price sensitivity differences. |
| ICP10 — Micro-Segment Opportunities | Under-served sub-segments ignored by current competitors. Niche within the niche. |
Batch 4 — Ad Pattern Analysis (10 agents)
| Agent | Mandate |
|---|
| AP1 — Hook Patterns | Top 20 hooks used across competitors. Categorize by type: question, contrarian, social proof, POV, stat, listicle. Identify saturation level. |
| AP2 — Visual Styles | Dominant visual styles in the category: lifestyle, editorial, UGC, flat-lay, native screenshot, data-viz, advertorial. Which are over/underused? |
| AP3 — CTA Patterns | Most common CTAs in this market. Which map to which funnel stage. Underused CTAs. |
| AP4 — Format Saturation | Distribution of ad formats: feed single / story / reel / carousel / collection. White spaces in format mix. |
| AP5 — Price Framing | How do competitors frame price? Direct price, anchoring, cost-per-use, comparison, "less than X per day"? |
| AP6 — Social Proof Patterns | Review counts, star ratings, "as seen on", TikTok Shop badges, press mentions. Which proof signals are most used/trusted? |
| AP7 — Emotional Angles | Dominant emotional triggers: fear, aspiration, identity, belonging, savings, status. Which are over/underused? |
| AP8 — Anti-Patterns (what NOT to do) | Angles that are overplayed and showing ad fatigue. Visual styles that look dated. Claims likely to get flagged. |
| AP9 — TikTok-Native vs Meta-Polish | Gap between TikTok-native content (lo-fi, UGC) and Meta polished ads. Which performs better in this niche? Evidence? |
| AP10 — White Space Matrix | Combine all above: angles × formats × styles with zero incumbent use → ranked opportunity list. |
Batch 5 — Synthesis (5 agents)
| Agent | Mandate |
|---|
| S1 — Opportunity Scoring | Score each white space (0–10) on: audience size, competition density, ad fatigue level, format accessibility, compliance risk. |
| S2 — Positioning Statement | Draft 3 positioning options for the brand. For each: one-liner, key differentiator, primary ICP, primary channel. |
| S3 — Angle Priority Matrix | Rank the top 10 ad angles by: expected CTR tier, awareness stage fit, format fit, and ease of execution. |
| S4 — 30-Day Test Plan | Recommend Phase 1 (days 1–10): 3 angles × 2 formats = 6 creatives, $X daily budget, kill criteria. Phase 2 scaling logic. |
| S5 — Master CSV Assembly | Aggregate all agent outputs into master-research.csv following the schema below. |
Master CSV Schema — master-research.csv
One file, multiple record_type values so it imports cleanly into Excel / Google Sheets / Airtable.
Column definitions
| Column | Description |
|---|
record_type | MARKET / COMPETITOR / ICP / AD_ANGLE / OPPORTUNITY |
id | Unique row ID (e.g. MKT-001, COMP-003, ICP-002, ANG-007, OPP-004) |
name | Entity name (market segment, competitor brand, persona name, angle name, opportunity label) |
category | Sub-classification (e.g. for COMPETITOR: direct / indirect / aspirational) |
summary | 1–2 sentence description |
price_range_usd | Price range or N/A |
primary_channel | Main distribution channel (Meta / TikTok / Google / Email / etc.) |
icp_fit | Which ICP segment(s) this maps to |
awareness_stage | Schwartz stage: 1=Unaware … 5=Most Aware |
hook_example | A concrete hook line for this angle/competitor/opportunity |
visual_style | Dominant or recommended visual style |
format | Best ad format(s) for this row |
cta | Recommended CTA |
strength | Key strength (for competitors) or why this angle works |
weakness | Key weakness or risk |
threat_level | HIGH / MEDIUM / LOW / N/A |
saturation_score | 0–10 — how saturated is this angle/competitor/format in the market |
opportunity_score | 0–10 — overall opportunity rating |
priority |
Example rows
record_type,id,name,category,summary,price_range_usd,primary_channel,icp_fit,awareness_stage,hook_example,visual_style,format,cta,strength,weakness,threat_level,saturation_score,opportunity_score,priority,source,notes,agent
MARKET,MKT-001,Linen co-ord sets US,DTC fashion,"$200–420M SAM, growing 18% YoY, driven by clean-girl TikTok aesthetics",58–180,TikTok+Meta,Women 24–35,2,,"UGC lifestyle",,,,,,,,4,8,P1,Statista 2025 / TikTok trends,,M1
COMPETITOR,COMP-001,Quince,direct,"Premium linen basics, $60–120, strong Meta presence, weak TikTok Shop",60–120,Meta+Email,Women 28–42,3,"Premium linen. Not $180.","Editorial lifestyle",3:4 feed,SHOP NOW,"Price positioning, strong reviews","No TikTok Shop native presence",HIGH,7,6,P2,meta.com/ads/library,,C2
ICP,ICP-001,Maya,"primary persona","28yo, millennial, seeks effortless style, $58 feels acceptable if quality is proven",,TikTok+Meta,,"2–3","This is what I wear when I don't want to think.","UGC selfie",9:16,"SHOP THE SET","Responds to social proof + fabric quality","Needs proof before price commitment",,,9,P1,Reddit r/femalefashionadvice,,ICP1
AD_ANGLE,ANG-001,Cost-per-wear,value framing,"$0.29/wear reframes $58 as exceptional value vs fast fashion",,,ICP-001,3–4,"$0.29 per wear. 200 wears. The set that earns its place.","Data-viz bold stat",1:1,"SHOP THE SET","Directly counters price objection","Requires some numeracy from viewer",,3,9,P1,Competitor ad analysis,,AP5
OPPORTUNITY,OPP-001,TikTok-native UGC + iMessage format,white space,"Zero incumbents use native social-proof formats (iMessage/TikTok review) for linen co-ords",,TikTok+Meta,ICP-001,2,"ok where is that linen set from?? 😅","iMessage native screenshot",3:4,"shop link in bio",,"Requires no brand recognition to thumb-stop",,0,10,P1,"Meta Ad Library sweep — 0 results",,AP10
Parallel Research Plan
Phase 1 — Launch all 50 agents simultaneously
Batch 1 (M1–M5): Market foundation — 5 agents
Batch 2 (C1–C20): One agent per competitor — up to 20 agents
Batch 3 (ICP1–10): ICP segments — 10 agents
Batch 4 (AP1–10): Ad pattern analysis — 10 agents
All 45 agents run in parallel. Each writes its structured findings back as JSON or structured markdown.
Phase 2 — Synthesis (after Batch 1–4 complete)
Batch 5 (S1–S5): Synthesis — 5 agents
S5 (Master CSV Assembly) runs last: aggregates all agent outputs into master-research.csv.
Phase 3 — Strategy & Creative Brief
- Strategy document from DeepSearch reports + master CSV.
- Static creative brief from strategy, psychographics, and competitor ad patterns.
- Final manifest and public-safety audit.
If sub-agents are unavailable, run the same tasks sequentially but keep files separated.
DeepSearch
Read references/deep-search-prompts.md only when writing the three research reports.
Each report must:
- Be in French unless the user asks otherwise.
- Use public sources with URLs and access dates.
- Separate facts from inferences.
- Include direct implications for Meta Ads angles.
- Avoid private LeadFactory or client examples.
Save:
01-deep-search/01-market-awareness.md01-deep-search/02-competitor-research.md01-deep-search/03-psychographic.md
Public Meta Ads Library Research
Read references/meta-ads-library-workflow.md and references/competitor-ads-framework.md before extracting ads.
Goal:
- Build
02-meta-ads-library/data.csv with one row per public ad or public ad-like asset.
- Build
02-meta-ads-library/analysis.md with patterns, saturated angles, white spaces, hooks, CTAs, and recommendations.
Use no-key sources:
- Meta Ads Library public search pages.
- Public landing pages linked from ads.
- Public social posts if the ad page cannot be accessed.
- User-provided screenshots, URLs, or pasted text.
CSV columns are fixed. Use the template in assets/templates/meta_ads_data_template.csv.
Strategy And Creative Brief
Read references/strategy-and-creative-brief.md and references/meta-ad-copy-checklist.md before writing final strategy assets.
Create:
03-strategy/strategy.md: positioning, awareness level, test plan, campaign structure, angle matrix, risks, next actions.04-creative-brief/creative-brief.md: target audience, visual direction, static creative concepts, copy direction, examples of on-image text, and CTA.
Keep this public/free:
- Provide strategic frameworks and creative directions.
- Do not include complete VSL scripts.
- Do not include internal LeadFactory performance thresholds, automation scripts, or client proof.
Public-Safety Audit
Before saying the folder is ready, run:
python3 skills/gauthier-thiry-leadfactory-free-skills/scripts/audit_public_safety.py \
~/Desktop/LeadFactory-Free-Skills-{project-slug}
If any issue is flagged, remove or rewrite the file before delivery.
Final quality gate:
- No API keys, tokens, environment files, private databases, CRM, or admin URLs.
- No real client names unless the user explicitly supplied them for their own public use.
- No absolute private local paths.
- No private emails, invoices, contracts, logs, generated client media, PDF/DOCX exports, or ZIPs.
- No VSL script files or full ad script packs.
- All sources are public and cited.
Final Response
Return:
- Desktop folder path.
- List of created deliverables.
- Number of sub-agents launched and completed.
- Row count of
master-research.csv (breakdown by record_type).
- Note whether Meta Ads Library extraction was direct or fallback.
- Result of
audit_public_safety.py.
