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 modest-curator478/claude-skills --skill sales-marketing-slagit clone --depth 1 https://github.com/modest-curator478/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/modest-curator478/claude-skills/sales-marketing-sla)<a href="https://agentmods.dev/skills/modest-curator478/claude-skills/sales-marketing-sla"><img src="https://agentmods.dev/badge/skills/modest-curator478/claude-skills/sales-marketing-sla/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/modest-curator478/claude-skills/sales-marketing-sla"><img src="https://agentmods.dev/badge/skills/modest-curator478/claude-skills/sales-marketing-sla.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 | $0.00219 | $0.03059 |
| Opus 5 | $0.00110 | $0.01529 |
| Sonnet 5 | $0.00044 | $0.00612 |
| Haiku 4.5 | $0.00022 | $0.00306 |
Grade A, and why
sales-marketing-sla 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.
This is a copy
100% identical to sales-marketing-sla — 0 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 — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sales-Marketing SLA: Defining, Documenting, and Enforcing the Handoff
This skill builds the operational agreement between marketing and sales around lead quality and follow-up. The marketing-to-sales handoff is the most common source of revenue leakage in B2B SaaS. Marketing generates leads that sales does not work. Sales blames marketing for bad lead quality. Marketing blames sales for ignoring good leads. Both sides have data that supports their position. Neither side has a shared definition of what a good lead actually is.
The problem is almost never lead quality or sales effort in isolation. It is the absence of a written, agreed-upon, and measured definition of what marketing is responsible for delivering and what sales is responsible for doing with it. This skill builds that definition.
HOW TO SET UP THIS SKILL
This skill works out of the box. For more specific output, provide:
- Average deal size and sales cycle length
- Current MQL definition if one exists
- Current SLA if one exists, even informally
- How many MQLs marketing generates per month and what percentage sales works within the expected timeframe
- The primary source of conflict between sales and marketing right now
- Whether this is being built from scratch or rebuilt after a breakdown
Why Most MQL Definitions Fail
Most MQL definitions fail for one of three reasons.
Reason 1: The definition was built by marketing without sales input.
Marketing defined an MQL based on what data they could track: a form fill, a content download, a demo request. Sales was told about the definition after it was built. Sales never agreed to it, never believed in it, and never prioritized MQLs that came from that definition.
Reason 2: The definition is based on activity, not fit.
An MQL defined as "any contact who downloads a whitepaper" captures students, competitors, and consultants doing research. It does not filter for the companies that can actually buy. Activity-based MQL definitions produce high volumes of low-quality leads and erode sales confidence in the MQL program entirely.
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 · 361 lines · 219 tokens per session scan A 0d2a4b474997
sales-marketing-sla is a skill published in the GitHub repository modest-curator478/claude-skills (4 stars, last pushed yesterday), licensed MIT. It adds 219 tokens to every session and 3,059 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to sales-marketing-sla, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
TEMPLATE
../../../agents/personas/TEMPLATE.md.
code-review
Pre-commit code review using code-reviewer agent for bug detection, security analysis, and quality assurance. Manual invocation only. Use before git commits to catch issues early. Blocks commits on REQUESTCHANGES verdict.
debug
Systematic debugging using error-detective and debugger agents instead of manual investigation. Triggers automatically on: error, bug, broken, failing, exception, stack trace, test failure. Orchestrates RCA-first approach with parallel agent investigation.
deep-context
Build deep codebase understanding using Capsule context, progressive-reader, and specialist agents instead of overwhelming main context. Triggers on: don't have context, understand codebase, learn about, need background. Implements progressive context building.
workflow
Systematic task orchestration for complex multi-step tasks. Triggers automatically when detecting: complex task, multi-step work, coordinate, orchestrate, break down. Guides through Understand → Strategy → Plan → Execute → Verify phases for comprehensive systematic approach.
task-router
Decision matrix for choosing optimal approach to any task. Helps Claude decide when to delegate to sub-agents vs. working directly. Use when starting a new task or unsure of best approach.