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memory

Store and retrieve durable learnings about how brayness actually works - success patterns, failure modes, corrections, and next-time hints.

Skill by scott-fryxell

IndexedMIT★ 125
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/scott-fryxell-memory

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Store and retrieve durable learnings about how brayness actually works - success patterns, failure modes, corrections, and next-time hints. Use before doing a task similar to a past one (check AGENTS.local.md Learnings first), and after a notable outcome or a user correction (append a dated learning to AGENTS.local.md, which is injected into every session). Also runs the critical refinement loop: on a correction or repeated failure, prove it with evidence, note the root cause, and propose a fix to the skill/process at fault rather than mutating it directly.

Use cases: productivity

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/memory

What's inside

Skill name
memory
Description
Store and retrieve durable learnings about how brayness actually works - success patterns, failure modes, corrections, and next-time hints. Use before doing a task similar to a past one (check AGENTS.local.md Learnings first), and after a notable outcome or a user correction (append a dated learning to AGENTS.local.md, which is injected into every session). Also runs the critical refinement loop: on a correction or repeated failure, prove it with evidence, note the root cause, and propose a fix to the skill/process at fault rather than mutating it directly.
License
MIT
Instructions
49 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Memory

Learnings are written to `AGENTS.local.md` (or
`AGENTS.md` for rules everyone must see). `AGENTS.local.md` is loaded into the
system prompt every session by the agents-local extension, so a lesson
written there is guaranteed to be in context next session - no on-demand
recall needed. The same extension syncs the `work/` project table in that
file from disk each session; edit descriptions there, not the row list. This separates it from the vault (your knowledge) and
from `AGENTS.md` (standing rules).

Only cross-cutting lessons learned from experience belong here. Standing
policies go in `AGENTS.md`; fix-specific trivia stays with the project. Keep `AGENTS.local.md` small - every line costs tokens
in every session.

## Write after a correction or outcome

On a user correction, a repeated failure, or a notable outcome, append a dated
bullet under a `## Learnings` section in `AGENTS.local.md`:

```markdown
## Learnings

- YYYY-MM-DD: [the one reproducible lesson / hint]
```

Keep every entry to 5-7 words - one hint, no reasoning. If the lesson should
guide every agent, put it in `AGENTS.md` instead - other harnesses read
that, not `AGENTS.local.md`.

## Read before you act

`AGENTS.local.md` is already in your system prompt every session - check it
before acting. If a past entry says a given approach failed, say so and take
the other route.

## Critical refinement loop

On a user correction or a repeated failure, work the loop:

1. Name the exact correction/failure.
2. Gather evidence: the user's words, the failing command/output, the file path.
3. Decide whether the fault is in a skill/process or was a one-off mistake.
4. If it points at a skill defect, propose the change as a diff to that skill's `SKILL.md` (in chat, or a file under `plans/` for bigger rewrites) and wait for a human to approve before editing the
   production skill.
5. Append the learning to `AGENTS.local.md` Learnings regardless.

The producer never grades its own homework: when reviewing your own work, reason from evidence and state what is wrong plainly.

From scott-fryxell/brayness, MIT.

More from scott-fryxell/brayness

Signals

Stars
125
Forks
15
Open issues
0
Last commit (this folder)
Sep 28, 2026 (29 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

memory skill. Agent Mart. https://agentmart.dev/skills/scott-fryxell-memory (last updated 2026-10-24)