How do I install the Win Loss Dataset skill?

Run npx skillmds@latest add majiayu000/win-loss-dataset in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Win Loss Dataset skill do?

Structure for capturing qualitative + quantitative win/loss insights with consistent tagging. It is listed under AI & ML on SkillMD.

Is Win Loss Dataset safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Win Loss Dataset?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Win Loss Dataset free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Win Loss Dataset?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Win Loss Dataset by majiayu000 — Agent Skill

Name: Win Loss Dataset
Rating: 4.5 (4 reviews)
Author: majiayu000

File contents

Win/Loss Dataset Skill

When to Use

Running structured win/loss programs.
Aligning qualitative interviews with CRM metrics.
Sharing insights across product, sales, pricing, and marketing teams.

Framework

Data Model – deal metadata (segment, region, product, stage), outcome, competitor, primary driver, secondary driver, confidence.
Qualitative Tags – categories for pricing, product gaps, implementation, support, brand, relationships.
Quotes & Evidence – key quotes, call clips, doc references with consent + access controls.
Analytics Layer – dashboards for driver frequency, trendlines, influence on win rate, revenue impact.
Action Tracking – link insights to backlog items, status, owner, and due date.

Templates

Interview note template with pre-defined tags + drop-downs.
Dataset schema (CSV/Sheet/BI) with validated fields.
Dashboard layout for driver trends + revenue impact.

Tips

Keep raw qualitative notes but publish sanitized, anonymized snippets for broader sharing.
Standardize driver taxonomy every quarter to avoid drift.
Pair with run-win-loss-program command for automatic dataset updates.

Frequently asked questions

Win Loss Dataset