agentsclimarketplace

Capture learning

Skill Chulinuwu/skillloom/skills/capture-learning

Private, local-first second brain for AI agents, with shared memory and governed skills across Claude Code, Codex, and your Tailnet.

Install
npx -y skills add Chulinuwu/skillloom --skill capture-learning

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 21 days oldThe repository was created 21 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Capture a reusable workflow as a Skillloom-managed Agent Skill candidate with provenance, validation, trust scanning, approval, promotion, and rollback evidence. Use after a complex task reveals repeatable steps, when the user asks to learn or save a workflow as a skill, or when verified task evidence should become a portable skill. Do not use for one-off notes or autonomous promotion.

SKILL.md

2.3 KB, 379 tokens by cl100k_base, as published. Nobody here has run it

Capture Learning

Turn verified task evidence into one focused, harness-neutral Agent Skill candidate. Treat drafting and promotion as separate decisions. Respond in the language of the user's latest message. Keep exact identifiers, hashes, paths, and source titles unchanged.

Workflow

  1. Confirm that the workflow is reusable and identify the narrow behavior the skill should preserve.
  2. Create a temporary skill directory containing SKILL.md and only the resources required by that workflow. Exclude credentials, full transcripts, unrelated artifacts, symlinks, binaries, and machine-specific instructions.
  3. Record concise provenance such as a task or issue identifier. Do not store conversation bodies as evidence.
  4. Run skillloom capture <skill-directory> --created-by agent --evidence <reference> and retain the candidate and operation identifiers.
  5. Run skillloom validate <candidate-id>. Review structural validation and every trust finding. Treat the scan as preflight evidence, not proof that content is safe.
  6. Present the candidate summary, provenance, content hash, findings, intended targets, and reload impact. Stop when a danger finding exists. Ask before accepting warnings or promoting.
  7. Only after explicit approval, run skillloom promote <candidate-id> --target <targets> --scope <scope> --yes. Add --accept-warnings only when the user explicitly accepts the reported warnings.
  8. Verify the promotion record, destination hashes, and target results. Report the promotion identifier and whether a reload or new session is required.
  9. If verification fails, inspect skillloom status and use skillloom resume <operation-id> --yes only when its staged evidence still agrees. Otherwise run skillloom rollback <promotion-id> --yes and report the restored hashes.

Never promote autonomously. A request to capture or validate is not approval to publish.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.