Agent skill · Data & Analytics

cs-health-scorecard

Build a customer health scorecard for a specific account. Use when asked to score account health, assess renewal risk, build a health dashboard, or evaluate an account's likelihood to renew or expand. Produces a structured health scorecard with a RAG status, dimension scores, key risks, and recommended actions.

mohitagw15856github.com/mohitagw15856GitHub ↗
claude-codecursorships scriptsMIT
Install
npx skills add mohitagw15856/pm-claude-skills --skill cs-health-scorecard --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 5
SKILL.md size: 9 KB
Bundled scripts: yes
Path: skills/cs-health-scorecard/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,255
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Customer Health Scorecard Skill Produce a structured, data-driven health scorecard for a customer account — giving the CSM and leadership a clear view of renewal risk, expansion potential, and the actions needed to move the account in the right direction. ## Reads from / Writes to the Brain If a [`professional-brain`](../professional-brain/SKILL.md) (`brain/`) exists, ground in it instead of re-asking for what you already know: - **Read first:** the account's `entities/` file, its `stakeholders/` (champion, economic buyer, detractors), and `knowledge/`. Run `python3 ../professional-brain/scripts/brain_query.py ./brain "<account name>"` and carry each fact's provenance tag through. - **📥 Propose to the Brain:** after producing, propose recording the health verdict + key risks to the account `entities/` file, and a renewal-risk entry to `decisions/` if a call is made, each provenance-tagged. Show them, get a yes, then write with `../professional-brain/scripts/brain_write.py … --commit` (append-only, dry-run by default). ## Required Inputs Ask for these if not already provided: - **Account name** and tier (enterprise / mid-market / SMB) - **Contract value** (ARR) and **renewal date

What's inside
Steps it walks through
  1. Reads from / Writes to the Brain
  2. Required Inputs
  3. Scoring Framework
  4. Programmatic Helper
  5. Output Format
  6. Health Score Summary
  7. Dimension Detail
  8. Product Adoption — [Score]/5
  9. Engagement — [Score]/5
  10. Outcomes — [Score]/5
  11. Support Health — [Score]/5
  12. Commercial — [Score]/5
  13. Top Risks
  14. Recommended Actions
Ships with 4 files
  • references/leading-signals.md
  • references/worked-example.md
  • scripts/health_score.py
  • templates/account-scorecard.md
Commands it runs
Five scores 1-5 in order: adoption engagement outcomes support commercial
python3 scripts/health_score.py --scores 4 3 4 2 5 --account "Acme Corp"
Or from JSON (lets you override the default weights per account/segment)
python3 scripts/health_score.py --input account.json
More from pm-claude-skills
All skills →
About this skill
What does the cs-health-scorecard skill do?

Build a customer health scorecard for a specific account. Use when asked to score account health, assess renewal risk, build a health dashboard, or evaluate an account's likelihood to renew or expand. Produces a structured health scorecard with a RAG status, dimension scores, key risks, and recommended actions.

How do I install it?

Run `npx skills add mohitagw15856/pm-claude-skills --skill cs-health-scorecard --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going