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doctor

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Mis à jour2 avril 2026 à 02:10

Run health diagnostics on the amem memory database. Use when the user wants to check memory health, embedding coverage, stale memories, or diagnose issues.

Installation

Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.

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Source

amanasmuei

amanasmuei/amem

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Métiers associésSOC

Basé sur la classification professionnelle SOC

Administrateurs de réseaux et de systèmes informatiquesProfessions informatiques et mathématiques·SOC 15-1244

SKILL.md

readonly

name	doctor
description	Run health diagnostics on the amem memory database. Use when the user wants to check memory health, embedding coverage, stale memories, or diagnose issues.

Health Diagnostics

Run health diagnostics on the amem memory database.

Instructions

Run via Bash:
```
npx @aman_asmuei/amem doctor
```
Present the results to the user, explaining any issues found.
Key metrics reported:
- Memories — total count
- Embeddings — percentage with semantic search enabled
- Core tier — token budget usage
- Graph edges — knowledge graph connections
- Stale — memories not accessed in 60+ days with low confidence
- Overdue reminders — any reminders past their due date
If issues are found, explain the suggestions:
- Low embedding coverage: restart MCP server or install @huggingface/transformers
- Core tier near budget: review core memories and demote less critical ones
- Stale memories: run memory_consolidate to clean up
- No corrections: suggest storing corrections when the AI makes mistakes

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name	doctor
description	Run health diagnostics on the amem memory database. Use when the user wants to check memory health, embedding coverage, stale memories, or diagnose issues.

Health Diagnostics

Run health diagnostics on the amem memory database.

Instructions

Run via Bash:
```
npx @aman_asmuei/amem doctor
```
Present the results to the user, explaining any issues found.
Key metrics reported:
- Memories — total count
- Embeddings — percentage with semantic search enabled
- Core tier — token budget usage
- Graph edges — knowledge graph connections
- Stale — memories not accessed in 60+ days with low confidence
- Overdue reminders — any reminders past their due date
If issues are found, explain the suggestions:
- Low embedding coverage: restart MCP server or install @huggingface/transformers
- Core tier near budget: review core memories and demote less critical ones
- Stale memories: run memory_consolidate to clean up
- No corrections: suggest storing corrections when the AI makes mistakes