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davidslavich

GTM Account Research

by davidslavich · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
175
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0
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1
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1
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Install in OpenClaw
/install gtm-account-research
Description
Deep-dive a target company and produce a structured account intelligence brief covering tech stack, buying signals, key personas, and a recommended engagemen...
README (SKILL.md)

GTM Account Research

Produce an Account Intelligence Brief for a named company. Ground every signal in a specific, traceable source.

Steps

  1. Snapshot — company name, HQ, size, business model, recent news (last 90 days)
  2. Tech stack — identify tools in the categories most relevant to your product (e.g. data warehouse, CRM, marketing automation, paid channels). Use BuiltWith, job postings, and engineering blogs as sources.
  3. Buying signals — job postings, conference attendance, funding events, published strategy content. Date every signal.
  4. Displacement triggers — are they actively migrating off a competitor? Hiring for a role that signals a gap you fill? Flag ⚡ if a strong trigger is present.
  5. Personas — identify Economic Buyer (budget authority), Technical Champion (evaluates), and End User (daily use). Name + LinkedIn URL when findable.
  6. Engagement angle — one specific recommendation: what pain, which product, what channel, who reaches out first, and the opening hook.

Output

# Account Brief: [Company] | [Date]

Snapshot: [3 sentences — what they do, size, recent context]
ICP Segment: [your segment label]
Stack: [Category: tool — or "Unknown" for each category]
Signals: [Bulleted — signal + source + date]
Displacement: [⚡ Yes — detail / None detected]
Personas: [Name · Title · LinkedIn · Pain point — one row per person]
Gaps: [What's missing that would sharpen the approach]

Engagement Angle:
[Specific: pain → product → channel → who reaches out → opening hook]

Keep the brief scannable. Flag any detail as [Unverified] if not directly observed.

Usage Guidance
This skill is coherent and instruction-only: it will perform live web research and produce briefs citing sources. Before installing, confirm the agent platform grants safe, rate-limited web search access and that you accept the agent collecting public personal data (names + LinkedIn URLs). Be aware of site terms-of-service (LinkedIn, job boards) and privacy/regulatory requirements (GDPR, CCPA) when storing or using identified personas. If you want to limit risk, keep autonomous invocation off or require human review, and add guardrails to avoid scraping behind logins or bulk-harvesting personal data. If you expect proprietary signals that require authenticated APIs, provide credentials explicitly and only if you trust the skill — currently it requests none.
Capability Analysis
Type: OpenClaw Skill Name: gtm-account-research Version: 1.0.0 The skill bundle consists of metadata and markdown instructions (SKILL.md) for an AI agent to perform standard Go-To-Market (GTM) account research. It contains no executable code, suspicious dependencies, or instructions to exfiltrate sensitive local data; it simply directs the agent to use web search to gather publicly available business information and format it into a report.
Capability Assessment
Purpose & Capability
Name and description match the SKILL.md steps: live web research (BuiltWith, job postings, blogs), identifying personas and signals, and producing a structured brief. The skill does not request unrelated binaries, credentials, or config paths — there is no disproportionate access requested for the stated task.
Instruction Scope
Instructions are scoped to public web research and grounding every signal in a traceable source. They instruct the agent to find people and LinkedIn URLs, date signals, and flag unverified items. This is in-scope but raises operational/privacy considerations: scraping or bulk collection of LinkedIn or other sites may run into terms-of-service, rate-limiting, or require authentication; outputs will include personal data (names + LinkedIn) which may have compliance implications.
Install Mechanism
No install spec and no code files — instruction-only. This is the lowest-risk install mechanism and matches the skill's purpose.
Credentials
The skill requests no environment variables, credentials, or config paths. That is proportionate: public web signals typically do not require secrets. Note: some desired signals (e.g., private job posting details or LinkedIn 'view' content) might be inaccessible without authenticated access, but the skill does not request those credentials.
Persistence & Privilege
always:false and default autonomous invocation are set. The skill does not request permanent presence or change other skills' configs. Autonomous invocation is normal; consider governance if you do not want the agent to autonomously perform live web lookups that may collect PII.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install gtm-account-research
  3. After installation, invoke the skill by name or use /gtm-account-research
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release
Metadata
Slug gtm-account-research
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is GTM Account Research?

Deep-dive a target company and produce a structured account intelligence brief covering tech stack, buying signals, key personas, and a recommended engagemen... It is an AI Agent Skill for Claude Code / OpenClaw, with 175 downloads so far.

How do I install GTM Account Research?

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

Is GTM Account Research free?

Yes, GTM Account Research is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does GTM Account Research support?

GTM Account Research is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created GTM Account Research?

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

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