Agent skill

Memory

by scott-fryxell in scott-fryxell/brayness

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

MITAuto-check passed

Install Memory

skills CLI
$ npx skills add scott-fryxell/brayness --skill memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install scott-fryxell/brayness memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/scott-fryxell/brayness.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/memory .claude/skills/memory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
memory
GitHub stars
125
Token cost
~668 tokens
SKILL.md length
309 words
Files
1
Skills in repo
27
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 5 steps: Name the exact correction/failure. → Gather evidence: the user's words, the… → Decide whether the fault is in a… → …
  • Tasks that involve Root cause analysis
  • SKILL.md covers Write after a correction or…, Read before you act and Critical refinement loop
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Memory is an agent skill from scott-fryxell/brayness. 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…

Its SKILL.md is about 670 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: A harness for the anxious digital mind. A safe place for creatives to keep their creative soul while exploring digital skills. The licence is MIT.

When your agent uses it

  • Tasks that involve Root cause analysis

Example prompts

  • “/memory”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  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…
  5. Append the learning to AGENTS.local.md Learnings regardless.

What it can do on your machine

Read from SKILL.md and the folder at commit 71f10e2. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Memory loads about 668 tokens when it runs. Until then it costs about 143 tokens; SKILL.md has 309 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~143
When it runs · the whole SKILL.md, loaded when a task matches
~668

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from scott-fryxell/brayness at commit 71f10e2, republished under its MIT licence (© scott-fryxell). 309 words, ~668 tokens.

Download SKILL.mdSave it as .claude/skills/memory/SKILL.md (or your agent's skills folder).
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.

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.

© scott-fryxell, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/memory of scott-fryxell/brayness.

Open the folder on GitHubat commit 71f10e2

Compare with similar skills

Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Memory this skillscott-fryxell/brayness125—~668Automated safety check: PassMIT
Diagnosing Superpowers Sessionsobra/superpowers297k3 repos~1.7kAutomated safety check: PassMIT
Code Design Rationale Investigatorcursor/plugins10k9 repos~2.6kAutomated safety check: PassNone
Pester Failure AnalysisPowerShell/PowerShell56k—~5.1kAutomated safety check: PassMIT
OpenLogi macOS Permissions TriageAprilNEA/OpenLogi23k—~2.5kAutomated safety check: NotesApache-2.0
Paseo Committeegetpaseo/paseo20k1 repos~496Automated safety check: PassCustom licence

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    297k GitHub starsUsed in 3 repos~1.7k tokens
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  • Official

    Digs into why code is shaped the way it is by checking git history, pull requests and connected tools in parallel, then reporting a cited read on the tradeoffs.

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  • Decides whether an OpenLogi device problem on macOS is a privacy-permission (TCC) problem, using agent log lines, and says which identity needs which grant.

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  • Paseo Committee

    getpaseo/paseo

    Forms a two-agent committee with contrasting profiles to analyze a stuck problem in parallel, reconcile their views and return a consensus plan without editing files.

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Questions about Memory

What does Memory do?

Store and retrieve durable learnings about how brayness actually works - success patterns, failure modes, corrections, and next-time hints. Memory is an agent skill from scott-fryxell/brayness. Store and retrieve durable learnings about how brayness actually works - success patterns, failure modes, corrections, and next-time hints.

When should I use Memory?

Memory fits situations like: tasks that involve Root cause analysis.

How do I install Memory in Claude Code?

Run `npx skills add scott-fryxell/brayness --skill memory -a claude-code`. Or copy the skill folder (skills/memory in scott-fryxell/brayness) into .claude/skills/memory in your project. Claude Code loads it when a task matches its description.

How do I install Memory in Codex?

Run `npx skills add scott-fryxell/brayness --skill memory -a codex`. Or copy the skill folder (skills/memory in scott-fryxell/brayness) into .agents/skills/memory in your project. Codex loads it when a task matches its description.

Can I use Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add scott-fryxell/brayness --skill memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memory, .gemini/skills/memory, .github/skills/memory and .opencode/skills/memory in your project.

What does Memory need to run?

SKILL.md names no scripts, command-line tools or credentials: Memory is instructions for the agent only.

Does Memory access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Memory use?

Memory is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Memory use?

About 668 tokens (SKILL.md is roughly 2.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Memory?

Skills that share tags, products or a category with Memory: Diagnosing Superpowers Sessions (obra/superpowers, 297k stars), Code Design Rationale Investigator (cursor/plugins, 10k stars), Pester Failure Analysis (PowerShell/PowerShell, 56k stars) and OpenLogi macOS Permissions Triage (AprilNEA/OpenLogi, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Memory?

scott-fryxell (a GitHub user) maintains it in scott-fryxell/brayness, which has 125 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on September 28, 2026.

Source: scott-fryxell/brayness on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.