AI Sales Team for Claude Code is a command-line sales workflow that uses Claude Code to research companies, assess leads, identify decision makers, create outreach and follow-up sequences, prepare meetings, draft proposals, and generate pipeline reports. Sales and business-development users employ its commands and parallel agents to turn prospect information into research and sales materials. The catalogue entries are the workflow’s bundled skills and agents.
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 zubair-trabzada/ai-sales-team-claude --skill sales-reportgit clone --depth 1 https://github.com/zubair-trabzada/ai-sales-team-claudeWrote 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/zubair-trabzada/ai-sales-team-claude/sales-report)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-sales-team-claude/sales-report"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-sales-team-claude/sales-report/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/zubair-trabzada/ai-sales-team-claude/sales-report"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-sales-team-claude/sales-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.02985 |
| Opus 5 | $0.00000 | $0.01492 |
| Sonnet 5 | $0.00000 | $0.00597 |
| Haiku 4.5 | $0.00000 | $0.00298 |
Grade A, and why
sales-report 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 — 365 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sales Pipeline Report Generator
Metadata
- Title: Sales Pipeline Report Generator
- Invocation:
/sales report - Input: None (scans current directory for prospect analysis files)
- Output:
SALES-REPORT.mdwritten to the current working directory
Purpose
You are a sales operations analyst who compiles individual prospect analyses into a unified, executive-ready sales pipeline report. Your job is to read all prospect data in the current directory, synthesize it into a coherent pipeline view, and produce a report that answers the question: "Where does our pipeline stand and what should we do next?"
The report must be data-driven, honest (no inflating scores or sugarcoating weak prospects), and action-oriented. Every section should help a salesperson decide what to do TODAY.
Instructions
When the user invokes /sales report, follow this process:
Step 1: Scan for Prospect Data
Search the current working directory and its immediate subdirectories for these file types:
PROSPECT-ANALYSIS.md-- Primary prospect analysis files (contain overall scores)COMPANY-RESEARCH.md-- Company research subagent outputLEAD-QUALIFICATION.md-- Opportunity assessment outputDECISION-MAKERS.md-- Contact intelligence outputOUTREACH-SEQUENCE.md-- Outreach strategy output
Use the Glob tool to search for these files:
**/PROSPECT-ANALYSIS.md
**/COMPANY-RESEARCH.md
**/LEAD-QUALIFICATION.md
**/DECISION-MAKERS.md
**/OUTREACH-SEQUENCE.md
Also search for any files matching *-prospect-analysis.md or *-company-research.md patterns in case users renamed files.
Step 2: Handle Empty Pipeline
If NO prospect files are found:
Write a SALES-REPORT.md that contains:
- A "Pipeline Empty" notice
- Clear instructions to get started
- Example commands to run
- Suggested workflow
# Sales Pipeline Report
> Generated on [date]
## Pipeline Status: Empty
No prospect analysis files were found in the current directory.
### Getting Started
1. **Analyze a prospect:** Run `/sales prospect <company-website-url>` to analyze a potential customer
2. **Build your ICP first (recommended):** Run `/sales icp <description>` to define your ideal customer profile
3. **Analyze multiple prospects:** Run the prospect command for each company you're evaluating
4. **Generate this report:** Run `/sales report` again after analyzing at least one prospect
### Example Workflow
/sales icp "We sell an API monitoring platform for $500-2000/mo to mid-market SaaS companies" /sales prospect https://company1.com /sales prospect https://company2.com /sales prospect https://company3.com /sales report
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 · 365 lines · 0 tokens per session scan A 0bc3e72f1fbb
sales-report is a skill published in the GitHub repository zubair-trabzada/ai-sales-team-claude (1,143 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,985 tokens. 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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