gtm-reverse-engineer
ASecurityReverse-engineer any company's public go-to-market into an evidence-graded, multi-file playbook (copy / adapt / skip). Use whenever the user wants competitor GTM teardown, growth forensics, channel analysis (Instagram, X/Twitter, LinkedIn, ads, Reddit/community, SEO, jobs, pricing), "how did X grow", unicorn/breakout GTM playbook, modular GTM research, or to install a 90-day motion plan from public signals. Trigger even if they say "spy on their GTM", "tear down their acquisition", or name a ...
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[](https://www.skillsdirectory.com/skills/ndpvt-web-gtm-reverse-engineer)---
name: gtm-reverse-engineer
description: |
Reverse-engineer any company's public go-to-market into an evidence-graded, multi-file playbook (copy / adapt / skip). Use whenever the user wants competitor GTM teardown, growth forensics, channel analysis (Instagram, X/Twitter, LinkedIn, ads, Reddit/community, SEO, jobs, pricing), "how did X grow", unicorn/breakout GTM playbook, modular GTM research, or to install a 90-day motion plan from public signals. Trigger even if they say "spy on their GTM", "tear down their acquisition", or name a single channel (ads only, X only, community only). Prefer this skill over ad-hoc web search when a structured pack or playbook is desired.
argument-hint: <company URL or name> [modules=full|quick|standard|ads,social_x|...] [depth=quick|standard|max]
version: 1.0.0
---
# GTM Reverse Engineer
General, **company-agnostic** skill. Nothing about a specific brand is hardcoded in runtime logic. The target company is always supplied by the user (or clarified before run).
## Defaults (override if user already chose otherwise)
| Setting | Default |
|---------|---------|
| Skill id | `gtm-reverse-engineer` |
| Output root | `./outputs/gtm-playbook-<slug>/` under current workspace |
| Depth | `standard` unless user says quick/max/full |
| Modules | user-selected; if user says "full" / "in-depth" / "everything" → all modules |
| Collectors | auto-detect (see below); never require Kimi or any browser bridge |
| Extra vs base research | **Channel Completeness Contracts** on every gather + scorecard |
If product choices are still ambiguous after reading the user message, ask before spending a large run. Do not invent the target company.
## When this skill triggers
- Competitor / company GTM, growth, acquisition, positioning teardown
- Single-channel asks: "only Instagram", "only X", "only ads", "only community"
- Full playbook / 90-day copy plan / what not to copy
- Modular or full-depth GTM research workflows
## Non-goals / honesty fence
- Not insider or "stolen secrets." Public and user-session-visible signals only.
- Not audited financials. Company-claimed ARR/users/valuation stay labeled.
- Not equal depth for every company. Thin public exhaust → thin pack + explicit coverage.
- Do not hardcode example companies as the run target. Examples in docs are illustrations only.
## Required inputs
1. **Target** (required): company name and/or website URL.
2. **Modules** (required unless full): list or preset (`full`, `quick`, or explicit module ids).
3. **Optional:** geo focus, B2B vs B2C emphasis, output directory, depth (`quick` | `standard` | `max`).
If target is missing or ambiguous (multiple entities share the name), **stop and disambiguate** (entity lock) before gather.
## Module catalog (v1)
Compose any subset. `full` enables all gather modules + analyze bundle + verify + playbook.
| Module id | Purpose |
|-----------|---------|
| `entity` | Company lock, founders/team surface, timeline anchors |
| `press_funding` | Press, launches, funding claims (graded) |
| `product_pricing` | Site, pricing, packaging, enterprise/affiliates pages |
| `jobs` | Careers/jobs as GTM org proxy |
| `social_x` | X/Twitter official + founders (archives/web first) |
| `social_linkedin` | LinkedIn company (+ founders if reachable) |
| `social_instagram` | Instagram official |
| `ads` | Meta/Google ad library and paid creative angles |
| `community` | Reddit/community sentiment and objections |
| `seo_distribution` | SEO content, PH, affiliates, distribution surfaces |
| `youtube_interviews` | Talks/interviews index + transcripts when available |
| `analyze` | Analysis suite (scoped to enabled evidence) |
| `verify` | Adversarial review + claim audit + confidence/gaps |
| `playbook` | Copyable playbook chapters (scoped) |
Presets (resolved by `scripts/init_run.py` into concrete module ids):
- `quick` → `entity`, `product_pricing`, `press_funding`, `analyze`, `verify`
- `standard` → all gather modules + `analyze`, `verify`, `playbook`
- `full` / `max` → same module set as standard; **depth** controls effort/browser willingness, not a different module list
**Scorecard is not a module.** After any gather, always run completeness rollup (phase), then optional analyze slices.
**Depth vs modules:** modules = what runs; depth = how hard (query volume, browser enrich only if confirmed).
Read `references/modules.md` for per-module outputs, done-when, and analyze scope.
## Pipeline (always) — load order
```
0. Parse args → resolve modules (init_run.py) → output paths
1. Detect collectors (detect_collectors.py) — browser_enrich_possible defaults false
2. Entity lock (serial; stop if ambiguous)
3. Gather enabled modules in parallel (each returns completeness_contract)
4. Orchestrator rollup COMPLETENESS-SCORECARD + RUN-CONFIG contracts
5. validate_run.py --phase post_gather (block on FAIL)
6. Analyze (only dimensions supported by evidence)
7. Verify if enabled (claim audit + adversarial)
8. Playbook if enabled (only if module enabled)
9. validate_run.py --phase final; index + confidence map + gaps
```
For large multi-module runs, prefer Claude Code **Workflow** orchestration (`dynamic-workflow` patterns): `phase`, `parallel`, `pipeline`, structured `agent` returns. Pass **modules_resolved**, not preset strings. For single-module asks, inline agents are enough — Completeness Contracts remain mandatory.
## Collector auto-detect (never hardcode Kimi)
Run `scripts/detect_collectors.py` (or follow `references/collector-matrix.md`) at start of every run.
**Priority order for raw collection:**
1. **Always:** web search skill (if present), `curl`/HTTP fetch, public APIs/archives
2. **If present:** YouTube transcript scripts/skills
3. **If browser bridge available** (chrome-session-bridge / Capy browser bridge online): optional logged-in enrich for login-walled surfaces
4. **If Kimi webbridge skill + daemon/extension available:** optional; **one session per agent**, max 2 tabs; never default bulk
5. **If nothing beyond web:** proceed web-only; document limits in completeness contracts
**Rules:**
- Detection must be runtime, not baked into module lists as "requires Kimi."
- If user is not logged in and wall blocks, set contract `blockers` to include `login_wall` and list `login_required_surfaces` — do not invent engagement.
- Never open mass tabs. Prefer one tab reused per browser agent.
- Omit browser tools from prompts when `browser_enrich_possible` is false.
## Channel Completeness Contracts (mandatory)
Every gather agent (including `entity` and single-module/inline runs) MUST emit a full canonical contract. Schema + enums: `references/completeness-contracts.md`.
All required keys: `module`, `channel`, `method` (`web`|`archive`|`browser`|`mixed`), `claimed_complete` (default **false**), `items_captured`, `date_span`, `sample_note`, `what_was_not_covered`, `grade_of_collection`, `login_required_surfaces`, `blockers`.
**Rollup:** orchestrator writes `00-meta/COMPLETENESS-SCORECARD.md` and `RUN-CONFIG.completeness_contracts` after gather. Missing contract for an enabled gather module = QA fail (`scripts/validate_run.py`).
Analyze/playbook must not imply full channel history/census when `claimed_complete` is false.
## Evidence grades
- **A** primary (official site/app, official social, filings, careers, primary founder post/transcript)
- **B** strong secondary with attribution
- **C** pattern from multiple weaker signals (list them)
- **D** single weak source — never playbook foundation
- **UNKNOWN** missing — do not invent
Company-claimed metrics: always label. See `references/evidence-grades.md`.
## Output tree (generic)
```
outputs/gtm-playbook-<slug>/
00-meta/ README, SOURCE-INDEX, CONFIDENCE-MAP, GAPS, COMPLETENESS-SCORECARD, RUN-CONFIG
01-entity/ COMPANY-LOCK, ...
02-raw-evidence/<module>/...
03-analysis/...
04-playbook/... (if enabled)
05-verification/... (if enabled)
```
`<slug>` from target domain or normalized company name. Init via `scripts/init_run.py` when available.
Templates: `references/output-tree.md`.
## RUN-CONFIG.json
Written by `init_run.py` at start (update at end). Important fields:
```json
{
"target_input": "<user string>",
"entity_locked": null,
"slug": null,
"modules_preset": "standard",
"modules_resolved": ["entity", "…"],
"gather_modules": ["entity", "…"],
"synthesis_modules": ["analyze", "verify", "playbook"],
"depth": "standard",
"collectors_detected": {},
"output_dir": "",
"started_at": "",
"completed_at": null,
"completeness_contracts": []
}
```
No default target company field. Never set target to an example output path.
## Modular execution examples
User: "only X GTM for https://example.com"
→ modules: `entity`, `social_x`; completeness rollup phase; light `analyze` slice (social scorecard only); skip full playbook unless asked.
User: "Instagram ads only"
→ modules: `entity`, `social_instagram`, `ads` (IG-relevant), completeness contracts, ads/social scorecards.
User: "full in-depth GTM playbook for Acme"
→ all modules; Workflow recommended; verify + full playbook.
## Workflow templates
- `workflows/README.md` — how to compose
- `workflows/modular-gather.md` — gather agent prompt patterns (parameterized)
- `workflows/full-run.md` — full depth phase map
- Do not ship company-specific JS. Any Workflow script must take `args`: `{ target, modules, outputDir, depth, collectors }`.
## QA expectations while using this skill
Before final handoff:
1. Entity lock file exists and matches user target
2. Every enabled gather module has a completeness contract
3. No invented metrics
4. SOURCE-INDEX lists sources
5. GAPS-AND-UNKNOWNS honest
6. If playbook enabled: recommendations cite grades
## References to load as needed
| File | When |
|------|------|
| `references/modules.md` | Module plan / dependencies |
| `references/completeness-contracts.md` | Every gather |
| `references/collector-matrix.md` | Start of run |
| `references/output-tree.md` | Init outputs |
| `references/evidence-grades.md` | Analysis / verify / playbook |
| `references/playbook-chapters.md` | Playbook module |
| `references/agent-prompt-templates.md` | Spawning subagents |
| `references/guardrails.md` | Browser/safety |
## Scripts
| Script | Purpose |
|--------|---------|
| `scripts/detect_collectors.py` | Print JSON of available collectors |
| `scripts/init_run.py` | Expand presets, create tree + RUN-CONFIG |
| `scripts/validate_run.py` | Fail-closed QA (`--phase post_gather|final`) |
## Anti-patterns
- Hardcoding a demo company’s handles as defaults
- Requiring Kimi/browser to run at all
- One tab per post / mass navigation
- Claiming complete social history without contract proof
- Turning company-claimed ARR into playbook foundation
Files in this skill
- SKILL.md
- assets/EXAMPLE-OUTPUT-POINTER.md
- references/agent-prompt-templates.md
- references/aristotelian-run-brief.md
- references/collector-matrix.md
- references/completeness-contracts.md
- references/evidence-grades.md
- references/guardrails.md
- references/modules.md
- references/output-tree.md
- references/playbook-chapters.md
- scripts/detect_collectors.py
- scripts/init_run.py
- scripts/validate_run.py
- workflows/README.md
- workflows/full-run.md
- workflows/modular-gather.md
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