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lennytoolslennytools/lenny/skills/gbrain-capture/SKILL.md

gbrain-capture

Skill1 starsChanged 2 months agoMITView on GitHub

Capture durable knowledge into GBrain (a portable memory layer at ~/.gbrain, independent of any coding harness) via the `gbrain` CLI. Use when the user says "G-Brain Capture", "GBrain capture", "remember this in GBrain", "save this to my brain", "capture this lesson/decision/failure mode", or asks to preserve project memory in a substrate that plugs in anywhere.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Verify: export PATH="$HOME/.bun/bin:$PATH".

    line 15
  2. Very specific:

    If the source does not exist, the CLI reports the available sources.

    line 21
  3. Very specific:

    A correction the user gives twice: If the same preference or correction recurs across turns or runs, capture it when you notice the second …

    line 52

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

GBrain Capture

GBrain is a portable memory layer at ~/.gbrain, independent of any coding harness and pluggable into any agent or tool. Capture durable knowledge here; it is a memory layer, not proof. Always verify live files and tests before acting on a recalled memory later.

Step 0: PATH

gbrain is a bun script and may not be on a coding harness's default PATH. Prefix every gbrain command with:

export PATH="$HOME/.bun/bin:$PATH"

Verify: export PATH="$HOME/.bun/bin:$PATH"; which bun gbrain → both should resolve under ~/.bun/bin. If not, stop and tell the user GBrain/bun isn't on PATH.

Capture workflow

  1. Pick the source (a namespace):
    • --source example-project for a named project.
    • the source the user names; omit --source for global/non-project memory.
    • If the source does not exist, the CLI reports the available sources. Create it once with gbrain sources add <name>; it is then searched only when named via --source.
  2. Capture a concise packet (--json, --type note):
export PATH="$HOME/.bun/bin:$PATH"
gbrain capture --json --type note --source <source> --stdin <<'PKT'
Title: <short durable title>
Project: <repo/project if known>
Date: <YYYY-MM-DD>

Context:
<what happened>

Decision / Lesson:
<what should be remembered>

Failure Modes:
<what went wrong / what to watch for>

Verification:
<commands, files, tests, commits, evidence from this session>
PKT
echo "exit=$?"
  1. Don't claim success until exit 0. Report the returned slug / JSON id.

What to capture (durable, not noise)

  • Decisions + the reason they were made.
  • Failure modes + how to detect/prevent them.
  • Verification criteria and known data-quality risks.
  • Shipping summaries with verification commands.
  • Non-obvious project conventions; skill combinations that worked.
  • A correction the user gives twice. If the same preference or correction recurs across turns or runs, capture it when you notice the second occurrence. Recurrence is the durable signal. This mirrors the bayesian repetition trigger; capture it here and draft the guard there.
  • Do NOT capture secrets/credentials, full private logs, or large raw dumps unless the user explicitly asks.

Retrieval (before work, treat as leads and verify afterward)

export PATH="$HOME/.bun/bin:$PATH"
gbrain query "<question>" --source-id <source> --adaptive-return

Notes

  • gbrain sources list shows registered namespaces (default is federated; named sources are searched only when specified).
  • Mirror major learnings here and in the relevant project skill so they persist both in-tool and in the portable layer.

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