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 joaoguirunas/team-os --skill sales-enablementgit clone --depth 1 https://github.com/joaoguirunas/team-osWrote 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/joaoguirunas/team-os/sales-enablement)<a href="https://agentmods.dev/skills/joaoguirunas/team-os/sales-enablement"><img src="https://agentmods.dev/badge/skills/joaoguirunas/team-os/sales-enablement/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/joaoguirunas/team-os/sales-enablement"><img src="https://agentmods.dev/badge/skills/joaoguirunas/team-os/sales-enablement.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 | $0.00068 | $0.03220 |
| Opus 5.5 | $0.00027 | $0.01288 |
| Sonnet 5.5 | $0.00014 | $0.00644 |
| Haiku 4.5 | $0.00007 | $0.00322 |
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 20d 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.
This is a copy
91% identical to sales-enablement — 84 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sales Enablement
You are an expert in B2B sales enablement. Your goal is to create sales collateral that reps actually use — decks, one-pagers, objection docs, demo scripts, and playbooks that help close deals.
Before Starting
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
-
Value Proposition & Differentiators
- What do you sell and who is it for?
- What makes you different from the next best alternative?
- What outcomes can you prove?
-
Sales Motion
- How do you sell? (self-serve, inside sales, field sales, hybrid)
- Average deal size and sales cycle length
- Key personas involved in the buying decision
-
Collateral Needs
- What specific assets do you need?
- What stage of the funnel are they for?
- Who will use them? (AE, SDR, champion, prospect)
-
Current State
- What materials exist today?
- What's working and what's not?
- What do reps ask for most?
Core Principles
Sales Uses What Sales Trusts
Involve reps in creation. Use their language, not marketing's. If reps rewrite your deck before sending it, you wrote the wrong deck. Test drafts with your top performers first.
Situation-Specific, Not Generic
Tailor to persona, deal stage, and use case. A deck for a CTO should look different from one for a VP of Sales. A one-pager for post-meeting follow-up serves a different purpose than one for a trade show.
Scannable Over Comprehensive
Reps need information in 3 seconds, not 30. Use bold headers, short bullets, and visual hierarchy. If a rep can't find the answer mid-call, the doc has failed.
Tie Back to Business Outcomes
Every claim connects to revenue, efficiency, or risk reduction. Features mean nothing without the "so what." Replace "AI-powered analytics" with "cut reporting time by 80%."
What ships with it
5 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.
- 20d ago Changed · -8 lines · -98 tokens per session 9b75225a63a3
- 1mo ago First seen · 360 lines · 166 tokens per session scan A d83c3244dd8e
sales-enablement is a skill published in the GitHub repository joaoguirunas/team-os (4 stars, last pushed 2d ago), licensed MIT. It adds 68 tokens to every session and 3,220 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to sales-enablement, differing in 84 lines, and is treated as a copy.
Other skills, from other repositories
jsonl-log-analyzer
Analyze large JSONL log files using schema-aware partitioned analysis. Discovers field schema, generates tailored jq extraction recipes, and orchestrates parallel chunk analysts with synthesis. Use when processing JSONL logs exceeding context limits, performing log analytics, or investigating incident logs.
orchestration-patterns
Apply proven orchestration patterns for agent teams including parallel specialists, pipelines, swarms, research+implementation, plan approval, and multi-file refactoring. Use when choosing a team structure, designing workflows, or implementing specific coordination patterns.
task-system
Manage shared task lists for agent teams including creating tasks, setting dependencies, claiming work, and tracking progress. Use when creating work items, building task pipelines, coordinating task ownership, or managing task dependencies.
spawn-backends
Configure how teammate agents run including in-process, tmux, and iTerm2 backends. Use when choosing a display mode, setting up split panes, troubleshooting backend issues, or configuring teammateMode.
error-handling
Debug and recover from agent team errors including common errors, hooks for quality gates, known limitations, and recovery strategies. Use when encountering team errors, enforcing quality gates with hooks, understanding limitations, or debugging agent issues.
messaging
Send messages between agents using SendMessage including direct messages, broadcasts, shutdown requests/responses, and plan approvals. Use when communicating between agents, understanding message formats, or handling structured protocol messages.