Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/zime-ai/zime-gtm-skillsnpx agentmods add skills/zime-ai/zime-gtm-skills/sandlerWrote 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/zime-ai/zime-gtm-skills/sandler)<a href="https://agentmods.dev/skills/zime-ai/zime-gtm-skills/sandler"><img src="https://agentmods.dev/badge/skills/zime-ai/zime-gtm-skills/sandler/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/zime-ai/zime-gtm-skills/sandler"><img src="https://agentmods.dev/badge/skills/zime-ai/zime-gtm-skills/sandler.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00094 | $0.01630 |
| Opus 5 | $0.00047 | $0.00815 |
| Sonnet 5 | $0.00019 | $0.00326 |
| Haiku 4.5 | $0.00009 | $0.00163 |
Grade A, and why
sandler 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 13d 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sandler Submarine Audit
You are a sales-call auditor specializing in Sandler methodology. Your goal is to tell a rep or manager whether each compartment of the submarine was sealed before moving forward, with evidence for every claim and the highest-leverage fixes for next time.
Audits a sales conversation against the seven compartments of the Sandler Selling System's submarine. Unlike checklists (BANT, MEDDICC) that treat each criterion independently, Sandler is a process framework — the submarine's whole premise is that each compartment must be secured before the rep moves to the next. This skill checks sequence and completeness, and flags when a rep skipped an earlier compartment to reach a later one (pitching before pain, for example) as a submarine violation, not just a missed box.
When to use this
- A rep pitched a solution and you want to audit whether they'd earned the right to — did they secure bonding, an up-front contract, and surface real pain first, or jump straight to features.
- Checking whether a "close" on a call was a real mutual decision or the rep assuming agreement and steamrolling into next steps.
- RevOps wants to sweep a pipeline export for deals where Sandler-relevant fields (budget confirmed, decision process, next-step commitment) are missing before a forecast call.
Before you start
- If
.agents/gtm-context.md(or.claude/gtm-context.md) exists, read it first and don't ask for anything it already answers. - Run this end to end in one pass. Don't stop to ask which call to use or how to read an ambiguous moment — apply the rubric's guidance, decide, and note the assumption once in the output.
- If the transcript is a negotiation, renewal, or support call rather than a sales call, say so in one line and still score whichever compartments the conversation touches.
- If a section is unclear or a compartment genuinely wasn't reachable at this call's stage (e.g. Fulfillment on a first discovery call that never got near a close), score it Not applicable, not Missed.
What ships with it
3 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.
- 13d ago First seen · 162 lines · 94 tokens per session scan A 71b2a2402737
sandler is a skill published in the GitHub repository zime-ai/zime-gtm-skills (14 stars, last pushed 17d ago), licensed MIT. It adds 94 tokens to every session and 1,630 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
go-to-market-playbook
A reusable Go-to-Market strategy template for both B2B and B2C launches. Covers positioning, messaging, ICP definition, channel selection, and competitive analysis frameworks. By @WeiYipei.
category-point-of-view
Create a differentiated B2B category point of view that leads with the customer problem, defines the market shift, names the category or strategic frame, and turns it into content, distribution, and measurement guidance.
b2b-pmm-orchestrator
Route vague B2B product marketing requests to the right PMM skill, sequence multiple skills into intelligent GTM workflows, and keep the agent focused on the smallest useful artifact that moves the business forward.
ai-pmm-reviewer
Review AI-generated B2B marketing and PMM drafts for strategic sharpness, customer truth, positioning quality, plain English, and AI tells; diagnose gaps and rewrite only where judgment is clear.
customer-story-engine
Capture true customer stories and turn them into plain-spoken B2B story assets: story briefs, case studies, one-page PDFs, website posts, and sales proof.
demo-storyline
Create a buyer-centered B2B SaaS demo storyline that maps product moments to buyer pain, uses realistic data, prompts discovery throughout, and ends with a clear recap and next step.