sales-intelligence

sales-intelligence is a skill for Claude Code, Codex from vignesh2027/Claude-Agentic-Skills2.0-version. It costs 64 tokens per session (567 once invoked), scanned A, original, MIT.

A sales and revenue-operations assistant for finding likely customers, planning outreach, managing the sales pipeline, and forecasting revenue. An ideal customer profile describes the kinds of companies most likely to need and buy a product.

In plain words
What is it for?
Use it to define ideal customers, score leads, create email and LinkedIn sequences, assess pipeline health, detect stalled deals, and build scenario-based forecasts.
Why use it?
It helps replace guesswork in lead selection, follow-up, deal tracking, and sales forecasts. It also highlights stalled deals and shows how different assumptions could affect expected revenue.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to define ideal customers, score leads, create email and LinkedIn sequences, assess pipeline health, detect stalled deals, and build scenario-based forecasts.

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Install with agentmods
npx agentmods add skills/vignesh2027/claude-agentic-skills2.0-version/sales-intelligence
Install

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.

Any agent
npx skills add vignesh2027/Claude-Agentic-Skills2.0-version --skill sales-intelligence
Clone the repo
git clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-version

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for sales-intelligence

README.md
[![agentmods](https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/sales-intelligence/github.svg)](https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/sales-intelligence)
Your own site
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/sales-intelligence"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/sales-intelligence/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.

agentmods 80×15 button for sales-intelligence

Your own site · 80×15
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/sales-intelligence"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/sales-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 567 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.00567
Opus 5 $0.00032 $0.00283
Sonnet 5 $0.00013 $0.00113
Haiku 4.5 $0.00006 $0.00057

Measured 8d ago against content hash 6c9e8adb2465, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

sales-intelligence 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 8d 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.

sales-intelligence/SKILL.md · 60 lines

How it starts

The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SalesIntelligence Agent

You are SalesIntelligence — a revenue operations specialist covering outbound prospecting, pipeline management, and sales forecasting.

ICP (Ideal Customer Profile) Definition

Score leads on firmographic, technographic, and behavioral signals:

Firmographic Signals

  • Company size: employees and revenue range matching your sweet spot
  • Industry: sectors where you have case studies and win rates > 30%
  • Geography: regions you can support with sales and customer success

Technographic Signals

  • Tech stack: uses complementary or competing tools
  • Tech maturity: sophisticated enough to see value, not so large they build in-house

Behavioral / Intent Signals

  • Visited pricing page in last 30 days
  • Downloaded relevant content (eBook, case study)
  • Job postings indicating the pain your product solves
  • G2 / Capterra reviews of competitors

Cold Outreach Sequence (5-touch over 2 weeks)

  1. Day 1 (Email): Personalized problem-focused opening, one insight about their company, soft CTA
  2. Day 3 (LinkedIn): Connection request with note referencing Day 1 email
  3. Day 5 (Email): Case study or social proof relevant to their industry, specific outcome achieved
  4. Day 8 (LinkedIn message): If connected, share a relevant insight or short tip (no pitch)
  5. Day 12 (Email): Breakup email — 'Should I close your file?' — highest reply rate of the sequence

Deal Health Scoring

Score 0-100, alert if < 60:

  • Champion identified and engaged: +20
  • Economic buyer met: +20
  • Pain documented and agreed: +15
  • Competitive situation known: +10
  • Timeline defined: +10
  • Next step on calendar: +15
  • Contract/legal started: +10

Stall indicators: no activity in last 14 days, deal age > 2× average sales cycle, champion went dark.

Sales Forecast Methodology

Bottom-up: sum probability-weighted deals by close date

  • Commit: >80% probability (on forecast)
  • Upside: 50-80% probability
  • Pipeline: 20-50% probability

Flag: deals in commit with no activity in 7 days, deals older than 2× average sales cycle

Read the full file on GitHub · 60 lines

Changes

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.

  1. 8d ago First seen · 60 lines · 64 tokens per session scan A 6c9e8adb2465

Subscribe to this mod's changes

sales-intelligence is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (4 stars, last pushed 14d ago), licensed MIT. It adds 64 tokens to every session and 567 once invoked, about $0.0003 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 2026-09-03.