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Knowledge Management · Agent Development / AGENT SKILL

memory-discipline

rohitg00/agentmemory
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Apply a session memory routine that recalls context, saves decisions, and learns from corrections.
The session loop that makes agentmemory pay off, recall before starting work, save at decision points, learn from corrections. Use when starting a nontrivial task, after settling a decision or debugging a gotcha, or whenever deciding if something belongs in memory.

Low community score

memory-discipline: This skill has a community score below −5, meaning it has received more downvotes than upvotes. Review its source and assessment before installing. Community votes are not a security review.

BEFORE YOU INSTALL

Understand the trade-offs.

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The full skill.

Original instructions from the publisher’s SKILL.md

Memory only pays off when reads happen before the work and writes happen at decision points. This loop is the skill; every tool call in it is mechanical.

## Quick start

```json
memory_smart_search { "query": "auth refresh flow", "project": "myrepo", "limit": 5 }
```

at task start, then at each settled decision:

```json
memory_save { "content": "Chose cursor pagination over offset; offset scans broke past 100k rows in db/list.ts.", "concepts": "cursor-pagination, offset-scan-limit", "files": "src/db/list.ts" }
```

## Why

Hooks capture what happened automatically. What they cannot capture is judgment: which fact mattered, which decision was settled, which correction should change future behavior. That judgment applied at the right moments is this discipline.

## Workflow

1. Task start, before reading code for any nontrivial task: `memory_smart_search` with the task topic and the project name. Spend the first tool call here; a hit saves rediscovery, a miss costs one call.
2. Mid-task, the moment a decision settles or a gotcha resolves: `memory_save` with the decision AND the reason, 2-5 specific concepts, real file paths. Save at the moment of resolution; end-of-session batch saves lose the reasons.
3. On user correction of your approach: save a lesson instead of a memory (the `lesson` skill). Lessons carry confidence and resurface before similar work; memories carry facts.
4. Before repeating a task type you have been corrected on: `memory_lesson_recall` with the task type as query.
5. Session end: stop. Hooks summarize and consolidate; a manual recap save duplicates them.

## What qualifies

Save: settled decisions with reasons, non-obvious constraints discovered by debugging, environment facts not derivable from the repo. Skip: anything readable from the code, transient state, secrets, and step-by-step narration (hooks already captured it).

## Anti-patterns

WRONG: finish implementing, then search memory to double-check, and batch-save a summary of everything done.

RIGHT: search first, save each decision as it settles, let hooks own the summary.

## Checklist

- First tool call on a nontrivial task was a project-scoped search.
- Every save carries the reason, not just the conclusion.
- Corrections became lessons, not memories.
- Nothing saved that the repo or hooks already record.

## See also

- `recall`, `remember`: the user-invoked forms of the read and write sides.
- `lesson`: the correction loop this discipline hands off to.

## Troubleshooting

See ../_shared/TROUBLESHOOTING.md if `memory_smart_search` or `memory_save` is not available.

Skill folder

Files included alongside SKILL.md in the publisher’s repository.