agentsclimarketplace

Freeze the session

Skill zakelfassi/skdd-commons/packs/2026-07-frontier/freeze-the-session

Skills that evolve in public — community agent-skill drops for SkDD

Install
npx -y skills add zakelfassi/skdd-commons --skill freeze-the-session

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End-of-session artifact extraction — convert what a session produced into durable assets (a skill, a DESIGN.md, a checklist, a codebase map) and register them in the colony. Use when a substantive working session is ending, when someone says "save this workflow" or "remember how we did this", after a hard-won debugging victory, or whenever model access is scarce and the judgment spent should outlive the session.

SKILL.md

4.3 KB, 796 tokens by cl100k_base, as published. Nobody here has run it

Freeze the Session

Before ending a substantive session, extract what it learned into artifacts the next session — or the next model — can execute without you.

Inputs

  • The session itself: what was built, decided, discovered, or repeated
  • The colony: project skills/ + .skills-registry.md, or the global ~/.skdd/skills/

Steps

  1. Inventory what the session actually learned. Scan for the four freezable shapes:

    • A repeated or repeatable workflow — you did (or will do) this sequence again → skill
    • Judgment applied to a surface — visual direction, copy voice, API shape decisions → convention doc (DESIGN.md, VOICE.md, style rules)
    • Failure modes found the hard way — review findings, attack results, debugging dead-ends → checklist
    • Hard-won orientation — how the codebase actually fits together, which the file tree doesn't reveal → map (architecture note)
  2. Skip what's already frozen. Don't extract what the repo records on its own (git history, existing docs, CLAUDE.md) or what only mattered this once. An empty inventory is a valid result — say so and stop.

  3. Freeze each item in its native format.

    • Skills → follow skillforge: kebab-case name, discovery-grade description (what + when-to-use triggers), steps, conventions, edge cases. The description is the retrieval surface — write it for the agent who doesn't know this skill exists.
    • Convention docs → rules an agent can obey, not prose it must interpret: tokens, scales, allowed/forbidden lists, before/after pairs.
    • Checklists → each entry is checkable: trigger + expected observation, not "make sure it's good".
    • Maps → entry points, the three layers that matter, where the bodies are buried. One page maximum.
  4. Register. Add each artifact to the colony registry (.skills-registry.md) with source and date; refresh harness mirrors (skdd link, or -g for global). An unregistered artifact is a file; a registered one is process memory.

  5. Close with the ledger. End the session report with a "frozen" section: what was extracted, where it lives, and the one-line trigger that should recall each artifact. If nothing was frozen, one line saying why.

Conventions

  • Extraction is part of the session, not an optional epilogue — budget the last few minutes for it the way a surgeon budgets for closing.
  • Prefer updating an existing skill over forging a near-duplicate; the colony's value is density, not count.
  • Write artifacts model-agnostically: no references to a specific model's capabilities, so they run on whatever is standing when it's dark again.

Edge Cases

  • Session was pure toil (mechanical edits, no judgment): nothing to freeze — the inventory correctly comes back empty. Freezing toil creates registry noise that buries the real skills.
  • The learning contradicts an existing artifact. That's an evolution, the most valuable freeze there is: update the existing artifact, note what changed and why in its metadata, bump its version.
  • Mid-session interruption or context running out. Freeze early, not at the end: the moment something feels reusable, extract it — a session that dies unfrozen loses everything it learned.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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