@dzhng: Fed this article to Fable and we created an explore-unknowns skill It scans your codebase, then interviews you one ques…

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Summary

A personal library of composable AI skills for building software factories, including an explore-unknowns skill that scans codebases and interviews developers to close known and unknown unknowns.

Fed this article to Fable and we created an explore-unknowns skill It scans your codebase, then interviews you one question at a time to close the known unknowns Then sweeps for the unknown unknowns you never thought of Now part of my software factory: https://github.com/dzhng/skills
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Fed this article to Fable and we created an explore-unknowns skill It scans your codebase, then interviews you one question at a time to close the known unknowns Then sweeps for the unknown unknowns you never thought of Now part of my software factory: https://github.com/dzhng/skills


dzhng/skills

Source: https://github.com/dzhng/skills

Skills

skills.sh

AI skills for building software factories

AI skills for building software factories. My personal library of domain-agnostic agent skills, reused across every project. Small, composable, and hackable — works with any harness that supports skills: Claude Code, Codex, opencode, Cursor, duet, and 70+ others.

npx skills add dzhng/skills

Add --list to pick individual skills, or copy any skills/<category>/<name>/ folder into your harness’s skills directory (e.g. .claude/skills/).

Why

Software is moving from tasks to factories: agents that pursue a goal autonomously until the output can be trusted. The hard part isn’t breaking the goal into tasks — it’s breaking it into independently verifiable pieces, and knowing where the pieces even are.

These skills run that loop. Treat the unknown as fog of war: map the terrain, carve it into territories that build and verify in isolation, and recursively re-slice whatever hides more map. And re-planning doesn’t stop when planning ends — the spec is a living document, updated and re-sliced mid-implementation whenever the work teaches the agent that the plan is stale. Every piece must prove itself — architecture review, code review, and visual review against a baseline — before the loop moves on. Each iteration gets less wrong, until the goal is done.

A single autonomous run — 1 day, 16 hours pursuing one goal

Proof: one unattended Codex run pursuing a single goal for 1d 16h on top of these skills, slicing and iterating until done.

How to use

  1. Plan. Ask your agent to /write-spec the goal. It interviews you, researches the unknowns, and materializes a spec under specs/<feature>/ — a slice graph where every slice is independently verifiable.

  2. Build. Kick off the loop:

    /goal /implement-spec specs/<feature>
    

    Add whatever framing fits: on the xyz branch, or using /codex as the implementer while you stay the parent orchestrator and reviewer.

  3. The rest fires on its own. The spec tells the loop when to call the other skills — /refactor-clean and a review pass at the end of every slice, /screenshot-critique and /compare-screenshots on anything visual, /close-spec when the last slice lands — and to update and re-slice the plan whenever implementation proves it stale. Every skill is also independently useful: invoke any of them manually whenever you want.

Skills

Engineering — slice, build, verify, repeat

SkillWhat it does
explore-unknownsWalk the user through mapping a task’s unknowns quadrant by quadrant — known knowns first, then interviews, reactable artifacts, and blindspot passes — ending with a complete four-quadrant map.
write-specBreak a large feature into independently verifiable, human-reviewable slices with API seams and playable checkpoints.
implement-specBuild an existing spec to completion, one reviewable pass at a time, delegating independent slices in parallel.
implement-spec-with-codexRun implement-spec with Codex writing the code — you orchestrate, integrate, and review every pass.
close-specArchive a shipped spec and rewrite it from a build plan into a durable rationale record that points back at the code.
refactor-cleanRefactor by moving ownership to one clean concept instead of layering compatibility sediment beside the problem.
write-docsWrite docs as a glossary of principles and pointers, never a mirror of the code that will rot.
codexUse the local Codex CLI as an independent second agent for review and (on explicit ask) delegated implementation.
claudeUse Claude Code (claude -p) as an independent second agent for consultation and (on explicit ask) delegated implementation.

Visual review — never accept visuals on vibes

SkillWhat it does
compare-screenshotsJudge which image is less wrong against a target you establish — telemetry to locate divergence, not a baseline match. Ships a reusable diff script.
screenshot-critiqueUse an unprimed subagent as a second set of eyes on visual work before accepting it.
preview-shotsOpen a curated set of image shots in one macOS Preview window for the user to eyeball.

Authoring — keep the skills themselves sharp

SkillWhat it does
write-skillsCreate or revise agent skills: triggers, leading words, progressive disclosure, and the failure modes to prune.
eval-skillsEval a skill against golden cases — blind runs in fresh subagents, a separate judge, and gap-driven edits.

Graphics

SkillWhat it does
rendererBuild, debug, or review WebGPU renderer work — three.js/TSL scene layers, node materials, WGSL passes, depth semantics, and browser-verified visuals.

License

MIT

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