PM Skills is a collection of plain-Markdown instructions that teach AI assistants structured methods for handling professional, personal, and life-admin tasks. People use it with Claude, ChatGPT, Gemini, Cursor, Codex, and other supported agents for work such as writing product requirements, reviewing documents, or planning difficult situations.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skillsnpx agentmods add skills/mohitagw15856/pm-claude-skills/cs-health-scorecardWrote 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/mohitagw15856/pm-claude-skills/cs-health-scorecard)<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/cs-health-scorecard"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/cs-health-scorecard/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/mohitagw15856/pm-claude-skills/cs-health-scorecard"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/cs-health-scorecard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00088 | $0.02962 |
| Opus 5.5 | $0.00035 | $0.01185 |
| Sonnet 5.5 | $0.00018 | $0.00592 |
| Haiku 4.5 | $0.00009 | $0.00296 |
Grade A, and why
cs-health-scorecard 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 2d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill de Cuadro de Mando de Salud del Cliente
Produce un cuadro de mando de salud estructurado e impulsado por datos para una cuenta de cliente, dando al CSM y la dirección una vista clara del riesgo de renovación, potencial de expansión y las acciones necesarias para mover la cuenta en la dirección correcta.
Lee desde / Escribe en el Brain
Si existe un professional-brain (brain/), usa la información disponible en lugar de volver a preguntar lo que ya sabes:
- Lee primero: el archivo
entities/de la cuenta, susstakeholders/(campeón, comprador económico, detractores) yknowledge/. Ejecutapython3 ../professional-brain/scripts/brain_query.py ./brain "<nombre de la cuenta>"y transmite cada etiqueta de procedencia del hecho. - 📥 Propón al Brain: después de producir, propón registrar el veredicto de salud + riesgos clave en el archivo
entities/de la cuenta, y una entrada de riesgo de renovación endecisions/si se toma una decisión, cada una etiquetada con procedencia. Muéstrales, obtén un sí, luego escribe con../professional-brain/scripts/brain_write.py … --commit(solo adjuntar, seco por defecto).
Entradas Requeridas
Pide estas si no se proporcionan ya:
- Nombre de la cuenta y nivel (enterprise / mid-market / SMB)
- Valor del contrato (ARR) y fecha de renovación
- Datos de uso del producto — inicios de sesión, ratio DAU/MAU, adopción de características clave
- Datos de soporte — tickets abiertos, puntuación CSAT o NPS, escaladas recientes
- Datos de engagement — fecha del último QBR, estado del patrocinador ejecutivo, nombre del campeón
- Datos comerciales — historial de pagos, conversaciones de expansión, asientos usados vs. licenciados
- Cualquier riesgo conocido o cambio reciente en la cuenta
Marco de Puntuación
Puntúa cada dimensión del 1 al 5. Pondera como se muestra. Calcula el total ponderado sobre 100.
| Dimensión | Peso | Qué Puntuar |
|---|---|---|
| Adopción de Producto | 30% | Ratio DAU/MAU, amplitud de características utilizadas, usuarios avanzados identificados |
| Engagement | 20% | Cadencia de QBR, patrocinador ejecutivo activo, fortaleza del campeón |
| Resultados | 20% | Cliente logrando sus objetivos declarados / métricas de éxito |
| Salud del Soporte | 15% | Tendencia de volumen de tickets, escaladas sin resolver, CSAT |
| Comercial | 15% | Pagos puntuales, asientos utilizados, señales de expansión |
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.
- 2d ago First seen · 197 lines · 88 tokens per session scan A 867e9ac47d9d
cs-health-scorecard is a skill published in the GitHub repository mohitagw15856/pm-claude-skills (1,449 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 2,962 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-12.
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