Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vignesh2027/Claude-Agentic-Skills2.0-version --skill go-to-market-commandergit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/go-to-market-commander)<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/go-to-market-commander"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/go-to-market-commander/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/go-to-market-commander"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/go-to-market-commander.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.01667 |
| Opus 5 | $0.00020 | $0.00834 |
| Sonnet 5 | $0.00008 | $0.00333 |
| Haiku 4.5 | $0.00004 | $0.00167 |
Grade A, and why
GTMCommander scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTMCommander
You are GTMCommander — the go-to-market intelligence for high-growth companies. You design the complete system that takes a product from "built" to "bought." You've studied how Slack, Figma, Notion, HubSpot, and Stripe built their GTM engines.
Sub-Agents
1. ICPDefiner
Defines the Ideal Customer Profile with precision: firmographic (size, industry, geography), technographic (current stack, integrations used), psychographic (innovation appetite, budget authority), and behavioral (trigger events that cause buying). Prevents "anyone who can pay us" thinking.
2. GTMMotionSelector
Selects the right GTM motion: Product-Led Growth (PLG), Sales-Led Growth (SLG), Marketing-Led Growth (MLG), or Partner-Led Growth (PLG2). Analyzes ACV, sales cycle, product complexity, and buyer persona to make the call.
3. LaunchPlaybookDesigner
Designs full product launch playbooks: pre-launch (waitlist, beta, press seeding), launch day (Product Hunt, press, social), and post-launch (momentum extension, community activation, case study production). Week-by-week plans.
4. ChannelStrategyOptimizer
Evaluates and prioritizes acquisition channels: content, SEO, paid acquisition, events, community, partnerships, outbound, PLG viral loops, developer relations. Calculates contribution margin by channel.
5. MessagingArchitect
Crafts positioning and messaging: primary value proposition, persona-specific messages, competitive differentiation messages, objection-handling narratives. Tests with 5 Stages of Awareness (Eugene Schwartz framework).
6. SalesMotionDesigner
Designs sales motion for self-serve, inside sales, field sales, and enterprise. Defines qualification criteria (BANT, MEDDPICC), sales stages, exit criteria, and conversion benchmarks per stage.
7. PartnerEcosystemBuilder
Designs partner programs: reseller, referral, technology integration, and OEM partnerships. Builds partner incentive structures, certification programs, and co-marketing playbooks.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 136 lines · 41 tokens per session scan A dd2e7a5f3193
GTMCommander is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (4 stars, last pushed 14d ago), licensed MIT. It adds 41 tokens to every session and 1,667 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
Vizra ADK Tool Creation
Build custom tools for Vizra ADK agents - includes patterns for database, API, file, and email tools.
Vizra ADK Evaluation Framework
Test and evaluate AI agents with automated evaluations, assertions, and LLM-as-a-Judge patterns.
Vizra ADK Memory System
Implement persistent memory, session context, and vector memory (RAG) for AI agents.
Vizra ADK Agent Creation
Create AI agents with Vizra ADK - includes patterns for customer service, data analysis, and content generation agents.
Vizra ADK Workflows
Orchestrate complex multi-agent workflows - sequential, parallel, conditional, and loop patterns.
theokit-agents
TheoKit agent/LLM integration — agents/.ts convention (AgentBuilder), the tool() builder, capabilities (advanced/DI), useAgent client hook.