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 matteotitta/genesys-skills --skill sales-enablement-indexgit clone --depth 1 https://github.com/matteotitta/genesys-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/matteotitta/genesys-skills/sales-enablement-index)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/sales-enablement-index"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/sales-enablement-index/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/matteotitta/genesys-skills/sales-enablement-index"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/sales-enablement-index.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 | $0.00123 | $0.01765 |
| Opus 5 | $0.00062 | $0.00882 |
| Sonnet 5 | $0.00025 | $0.00353 |
| Haiku 4.5 | $0.00012 | $0.00177 |
Grade A, and why
sales-enablement 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sales enablement
Orchestrator for sales enablement assets. Routes to dedicated sub-skills for decks, battlecards, demo scripts, and CX/chatbot demos. Handles ROI calculators, objection handlers, discovery guides, competitive one-pagers, deal qualification checklists, and pricing guides directly.
When to run
- User asks for sales-facing material: ROI calc, objection handler, discovery guide, competitive one-pager, qualification checklist, pricing guide
- User says "sales enablement", "sales assets", "sales collateral" with no specific asset type → ask which type, route accordingly
- competitor-research or product-messaging just completed → offer to derive battlecards / sales deck / demo script
- User wants a live sales demo for a prospect → route to
/cx-assessmentor/chatbot-assessment - Do not run for: standalone competitor research, standalone messaging, win-loss analysis, landing-page copy. Route to those skills directly
Inputs
Required (at least one):
- URL for research
- Attachment: existing messaging, ICP docs, sales notes
- Skill reference: output from
competitor-research,product-messaging,icp-behavioural,win-loss-analysis
Plus: confirmed asset type (battlecard, ROI calc, sales deck, objections, discovery guide, one-pager, qualification, pricing). If missing, ask before proceeding. Minimum-context-by-asset matrix in the premium reference ("Minimum context by asset type").
Steps
- Route or own. If user asked for sales deck / battlecard / demo script / CX / chatbot → invoke the dedicated sub-skill (see Sub-skills table below) and stop. Otherwise continue here for the 6 asset types this skill owns.
- Validate inputs. Confirm asset type, target (competitor or persona), and at least one context source. Surface gaps explicitly.
- Phase 1 — context gathering. Inventory attachments + URLs + referenced skill outputs. Map to asset requirements. Offer to run upstream skills (
/competitor-research,/product-messaging,/icp-behavioural,/win-loss-analysis) for any gap. Checkpoint: minimum context for selected asset is available. - Phase 2 — asset generation. Select template per asset (objection-handler / discovery-guide frameworks inlined in playbook; full templates in the premium reference). Generate content; source every claim with confidence (High / Medium / Low / [UNVERIFIED]); mark gaps explicitly. Checkpoint: all claims sourced or marked.
- Phase 3 — delivery. Format per asset: Markdown (handlers, guides, qualification, pricing), interactive HTML (ROI calculator), Markdown/PDF (one-pager). Run quality checklist.
- Self-evaluation. Run completeness + evidence + guardrail + actionability checks (full protocol in the premium reference). Roast: would a sales rep actually use this in a call, or is it too generic?
- Review gate 2. User reads + approves; reviews claim accuracy, competitive intel, actionability.
- Chain suggestions. If asset approved → suggest companion assets (battlecard → sales deck; discovery guide → demo script; ROI calc → pricing guide). Offer export to Google Docs / Notion.
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 · 125 lines · 123 tokens per session scan A 353c2347e62b
sales-enablement is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 123 tokens to every session and 1,765 once invoked, about $0.0006 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.
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