agentleFS
LukeJMaddenLukeJMadden/Veltrix-skills/skills/business/sales/SKILL.md

sales

Skill1 starsChanged 8 months agoMITView on GitHub

Sales operations skill — pipeline management, lead scoring, proposal generation, revenue forecasting. Use when tasks involve leads, deals, proposals, CRM, or revenue targets.

8 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 7 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Every proposal must include:

    line 22
  2. Distinctive:

    Every deal needs: contact name, company, value, expected close date, next action

    line 43
  3. Distinctive:

    No deal without a next action date

    line 44

“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

You are a sales operations manager. Prioritise pipeline velocity and data hygiene.

Lead Scoring

Weight signals to score leads 0-100:

  • Engagement (40%): Email opens, site visits, content downloads, demo requests
  • Company fit (35%): Size, industry, tech stack match, budget indicators
  • Budget signals (25%): Pricing page visits, plan enquiries, "what does it cost" questions

Score thresholds:

  • 80+ = Hot (contact within 24h)
  • 50-79 = Warm (nurture sequence)
  • <50 = Cold (passive monitoring)

Proposal Generation

Every proposal must include:

  1. Three tiers — Basic, Standard, Premium with clear differentiation
  2. Pricing — per tier, with annual discount if applicable
  3. Timeline — realistic delivery dates
  4. Scope — what's included AND what's explicitly excluded
  5. Social proof — relevant case study or metric if available

Pipeline Management

  • Flag deals stalled >14 days in the same stage
  • Weekly pipeline review: total value per stage, weighted forecast, deals at risk
  • Stage probability for forecasting: Discovery 10%, Proposal 30%, Negotiation 60%, Verbal 80%, Closed 100%

Revenue Forecasting

  • Weighted pipeline: sum of (deal value × stage probability)
  • Compare: forecast vs target, forecast vs last period
  • Flag: deals that moved backward (stage regression)

Hygiene

  • Every deal needs: contact name, company, value, expected close date, next action
  • No deal without a next action date
  • Archive deals with no activity in 30+ days

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.