engram-lessons

Record or reinforce an Engram lesson — the self-learning loop. Use when the user corrects a mistake, when an action failed in a generalizable way, when the user confirms an approach as right, or when you just applied a previously recalled lesson.

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Repositorio: behl1anmol/Engram
Última actividad en el origen: 18 de julio de 2026 a las 08:13
Idioma detectado de SKILL.md: inglés
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Opciones de instalación

De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.

Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.

Un comando directo omite el prompt de revisión. Revisa el origen antes de ejecutarlo.

npx skills add https://github.com/behl1anmol/Engram --skill engram-lessons

El comando permanece en una sola línea. Desplázate horizontalmente para revisarlo antes de copiarlo.

¿Prefieres una copia local? Descarga los archivos que SkillsMP tiene disponibles ahora.

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Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.

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engram-recall

Query Engram persistent memory mid-session for context about the user or their work. Use when the current task might touch something the user has history with, or when the user asks "what do you remember about X".

2026-07-18

engram-remember

Store a durable fact in Engram persistent memory. Use when the user says "remember this/that", shares a lasting preference, role, goal, or project fact, or corrects you in a way worth keeping. Enforces update-over-create and the one-fact-per-file rule.

2026-07-18

engram-distill

End-of-session distill flow: persist what this session produced that is durable. Use when the user says goodbye, wraps up, or asks to "save context/memories", or when substantial work is concluding.

2026-07-18

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name	engram-lessons
description	Record or reinforce an Engram lesson — the self-learning loop. Use when the user corrects a mistake, when an action failed in a generalizable way, when the user confirms an approach as right, or when you just applied a previously recalled lesson.

Lessons make you measurably better with this user over time, in any agent. CLI path is in the session-start conventions block.

Capture (§7.3 triggers)

Record when: the user corrected you; your action failed and a general check would have prevented it; the user confirmed "always do it this way".

Quality bar — apply before writing: would this lesson change behavior in a future session? One-off trivia (flaky network, typo) is not a lesson.

Body must follow this shape:

**Mistake:** <what went wrong, concrete>
**Why it happened:** <the assumption or missing check>
**How to apply:** <the behavior-changing rule for next time>

echo "<body>" | ENGRAM_AGENT=claude-code python3 "<engram_py>" add \
  --type lesson --name kebab-case-slug \
  --description "Discriminating one-liner recall can match" --tags ...

For a confirmed-good approach, same shape with Mistake: replaced by Approach:.

Reinforce (§7.4)

When a recalled lesson actually changed what you did this session:

python3 "<engram_py>" lesson applied <name>

This bumps times_applied (ranks it higher) and renews its expiry. Unapplied lessons lapse naturally — that is the decay model, don't fight it.

engram-lessons

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Más de este repositorio

Más de este repositorio

Capture (§7.3 triggers)

Reinforce (§7.4)

Capture (§7.3 triggers)

Reinforce (§7.4)