audit-agents
Audit or rewrite AGENTS.md so it holds only lasting principles. Run it only when the user…
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a
$ npx -y skills add dzhng/skills --skill explore-unknowns --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/explore-unknownsContext preview
The summary Claude sees to decide when to auto-load this skill.
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a
name: explore-unknowns description: Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the codebase or domain is unfamiliar, the user will "know it when they see it", a reference implementation must be understood before porting, mid-build deviations from the plan need capturing, or a finished change needs buy-in or verified understanding before merge. Pairs with [write-spec](../write-spec/SKILL.md) — walk the quadrants to burn off fog before slicing, and feed the finished map into the spec.
The map is not the territory. The prompt, the plan, and the context window are the map; the codebase, the domain, and the user's actual intent are the territory. The gap between them is the unknowns — and an unknown found before code is written costs minutes, while the same unknown found three PRs later costs the three PRs.
This skill is a guided conversation: the **quadrant walk**. Together with the user you fill in a four-quadrant map of the task, one quadrant per stage, and the user walks away holding the completed map. The map is the deliverable; implementation is a different task that starts only after the map is handed over.
Two moves apply at every stage:
when you can hand them something concrete to react to — a rendered option, a clickable mock, a decisions table. Reacting extracts knowledge the user has but cannot articulate unprompted.
next message pre-drafted: steal/skip chips, resonate checkboxes, a decisions table, a copyable sharpened prompt — so their reaction becomes their next message with near-zero typing.
Five stages, walked in order, one at a time. **When you enter a stage, read its reference file and follow it.** Name the current quadrant as you go — the user should always know where they stand on the map — and finish the stage in front of you before opening the next.
1. **[Known knowns](references/stage-1-known-knowns.md)** — scan the territory, then open with the settled ground. 2. **[Known unknowns](references/stage-2-known-unknowns.md)** — the questions you can name; resolve them one at a time. 3. **[Unknown knowns](references/stage-3-unknown-knowns.md)** — extract the taste and tacit context nobody has put into words. 4. **[Unknown unknowns](references/stage-4-unknown-unknowns.md)** — sweep the territory for landmines. 5. **[Hand over the map](references/stage-5-hand-over-the-map.md)** — the completed four-quadrant map, the walk's only done-condition.
When the user moves on to build, review, or merge what the walk mapped, read [after the walk](references/after-the-walk.md) — the map lives on past planning.
Count questions the user has answered across the walk, not turns or answers found in the territory. After about five or six, if their preferences form a clear pattern and questions remain, pause the interview for this checkpoint. If the pattern is still unclear, continue targeted questions and offer once it becomes clear; do not manufacture questions just to reach the count.
1. List the preferences you have inferred, grounded in their answers, and invite corrections. Ask whether it would help for you to answer matching questions on their behalf: **confirm or edit these preferences and opt in, or keep answering yourself**. This replaces the next interview question. 2. Wait for explicit opt-in. Confirming the preferences alone is not consent to delegate; silence is not consent either. If they only confirm the preferences, clarify the delegation choice once, then default to the interview if it remains unanswered. If they decline, continue without repeatedly offering. 3. Once opted in, answer questions whose answers follow clearly from the confirmed preferences, within the scope they delegated. Ask the user when preferences conflict or a new tradeoff falls outside that scope. Investigate missing facts in the territory first; ask only when it cannot resolve them. Preferences cannot substitute for facts about the territory. 4. Disclose every delegated answer as you make it: **question → answer → preference and reason**, labeled **Answered by the agent on your behalf**. Small batches are fine; never collapse distinct questions into a hidden decision. Carry each entry into the map with that attribution, rather than implying the user personally answered it. Invite corrections without requiring approval of every answer. 5. Honor corrections and withdrawal immediately. Corrections update the preference summary and reopen decisions they invalidate. Withdrawal stops future delegated answers; keep earlier answers attributed unless the user asks to revisit them. Delegation lasts for this walk and does not authorize implementation or skip the remaining quadrants.
**Done when** the user has chosen whether to delegate and, if opted in, the confirmed preferences and delegation scope are recorded alongside the map's decision ledger.
quadrant. The walk ends with the map in the user's hands — no map, not done.
materially bears on a decision in flight is disclosed the moment you have it, then filed on the map under its quadrant — never held back for its stage's scheduled turn.
closed must have been shown to the user first — including ones the t
AI skills for building software factories. My personal library of domain-agnostic agent skills, reused across every project.
Repo: dzhng/skills
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