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 Growth-Today/claude-skills --skill gt-gtm-strategy-advisorgit clone --depth 1 https://github.com/Growth-Today/claude-skillsWrote 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/growth-today/claude-skills/gt-gtm-strategy-advisor)<a href="https://agentmods.dev/skills/growth-today/claude-skills/gt-gtm-strategy-advisor"><img src="https://agentmods.dev/badge/skills/growth-today/claude-skills/gt-gtm-strategy-advisor/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/growth-today/claude-skills/gt-gtm-strategy-advisor"><img src="https://agentmods.dev/badge/skills/growth-today/claude-skills/gt-gtm-strategy-advisor.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 | $0.00242 | $0.01457 |
| Opus 5.5 | $0.00097 | $0.00583 |
| Sonnet 5.5 | $0.00048 | $0.00291 |
| Haiku 4.5 | $0.00024 | $0.00146 |
Grade A, and why
gt-gtm-strategy-advisor 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 1mo 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Strategy Advisor
Turn what you already know about your business — your CRM history, your sales deck, your website, your call recordings — into a sharp, signal-based GTM playbook you can act on.
Who this is for: VP of Sales, Head of Growth, RevOps leads, and founder-led sales teams who want a data-backed GTM motion, not a generic template. You run this on your own company and your own prospects.
What you get: a complete Excel workbook — Company + Market, ICP, Buyer Journey, Pain per Persona, Signal Library, Signal Combo Plays, Messaging Matrix, Battlecard, and a STRATEGY summary — built from your real data, not guesses.
The core idea
The quality of your playbook depends on the quality of what you feed it. Your own materials give a hypothesis; your CRM data gives real patterns. Together they produce a high-confidence playbook.
BRONZE Your materials only (deck, website, positioning doc).
A solid starting hypothesis — good before you have data pulled.
GOLD Your materials + real CRM data (closed-won / closed-lost patterns).
The standard working version — grounded in who actually buys.
GOLD + VALIDATED The above + call recordings / transcripts.
Your real sales conversations confirm or correct the hypothesis.
Step 0 — Feed it your data
Give the advisor as much real input as you can. Three ways, best combined:
- Connect your CRM. If you have a HubSpot or Salesforce connector enabled, the advisor reads your real closed-won and closed-lost patterns, contact and account fields, and deal history — this is what turns a guessed ICP into a data-backed one. (Related GT skills for pulling and cleaning this data:
gt-hubspot-admin,gt-salesforce-admin,gt-clay-builder.) - Upload your materials. Sales deck, website copy, positioning doc, a CRM export (CSV), and any competitor notes. The more concrete, the sharper the output.
- Add call recordings. One or two recent sales-call transcripts are the single highest-leverage input — they reveal the real objections, triggers, and champion that your deck usually gets wrong.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed · +2 tokens per session 035a1d545e1b
- 2mo ago First seen · 92 lines · 240 tokens per session scan A c5acde0a65aa
gt-gtm-strategy-advisor is a skill published in the GitHub repository Growth-Today/claude-skills (6 stars, last pushed yesterday), licensed MIT. It adds 242 tokens to every session and 1,457 once invoked, about $0.0010 per session on Opus 5.5. 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.
gt-gtm-strategy-advisor compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gt-gtm-strategy-advisorGrowth-Today/claude-skills | Skill | 6 | yesterday | MIT | A | 242 | Claude Code, Codex |
| crm-customer-managementzavora-ai/skill-crm-customer-management | Skill | 2 | 5mo ago | none | A | 0 | Claude Code |
| gooseworksgooseworks-ai/goose-skills | Skill | 1.3k | today | MIT | A | 70 | Claude Code |
| gingiris-go-globalGingiris-1031/gingiris-skills | Skill | 89 | 3d ago | MIT | A | 534 | Claude Code |
| deepline-ads-audiencesgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 133 | Claude Code, Codex |
| deepline-analyticsgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 115 | Claude Code |
| deepline-enginegetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 43 | Claude Code, Codex |