Skip to content
cccskills
FreePublished on GitHub

plan-interrogate

Stress-test a plan by walking its decision tree one question at a time. Use when the user wants to pressure-test a design before implementation.

The English summary is being prepared. Showing the original description.

See how to install

Files included (1)

  • SKILL.md3.3 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

plan-interrogate

Drive a plan from sketch to commitment by resolving every open decision before any code is written.

Method

  1. Restate the plan in one paragraph. Confirm with the user that this is the plan being interrogated. Do not proceed on a mis-restatement.
  2. Extract the decision tree. Every branch point becomes a node. Mark each node as open (undecided) or resolved. A resolved node carries a source tag: user (the user answered), inferred (the codebase or an existing constraint settled it).
  3. Resolve in dependency order. A node is ready when every node it depends on is resolved.
  4. For each ready open node, ask exactly one question. Keep the question tight and binary or small-multiple-choice when possible.
  5. Pair every question with a recommended answer and one sentence of reasoning. The user can confirm, pick a different option, or push back.
  6. Before asking, check whether the answer already lives in the codebase, prior commits, or an existing doc. If so, skip the question and mark the node resolved with source inferred: <path>.
  7. Exit only when zero nodes are open. Print the resolved tree as a flat list: Decision - Choice - Source (user | inferred: <path>).

Anti-patterns

  • Asking multiple questions at once. The user loses context and you lose the ability to react to each answer individually.
  • Asking before exploring. If a fifteen-second read would answer the question, read first.
  • Asking without a recommendation. A question without a stance is a survey; it offloads design onto the user.
  • Rolling past an unresolved node. If a dependency is not pinned, the downstream question is premature.

Outputs

The interrogation produces three artifacts, not just answers. Offer to write each; do not force it.

  1. Decision ledger (always). The resolved tree as a flat list: Decision - Choice - Source (user | inferred: <path>).

  2. CONTEXT.md (when the interrogation surfaced project-specific terms). A short shared-language file: every domain term you and the user had to pin down, with a one-line definition in the project's own words. This is what stops the agent from using twenty words where one will do next session, and keeps names in code consistent. One term per line: term - what it means here. Point future sessions at it. On re-run, merge new terms in place rather than overwriting existing ones.

  3. Decision records (for contested or hard-to-reverse nodes only). One short record per decision that a future reader would question: the context, the choice, the alternatives rejected, and why. Keep them in docs/decisions/NNNN-slug.md. Read the directory first and number from the highest existing record so two records never collide. Skip the obvious ones - a record for a trivial choice is noise.

Output contract

The decision ledger the user can paste into the plan doc. No prose summary. No hedging. If the user declines to decide a node, mark it DEFERRED with the reason the user gave - this is not the same as open. When you write CONTEXT.md or a decision record, keep it in the project's language, not a generic template.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Coordinate multiple Claude Code sessions as a team — lead + teammates with shared task lists, mailbox messaging, and file-lock claiming. Patterns for team sizing, task decomposition, and when to use teams vs sub-agents vs worktrees.

The English summary is being prepared. Showing the original description.

rohitg00/pro-workflow2.9KUpdated Sep 29, 2026

Auto-configure quality gates, hooks, and settings for a new project. Detects project type and sets up appropriate tooling. Use when onboarding a new codebase.

The English summary is being prepared. Showing the original description.

rohitg00/pro-workflow2.9KUpdated Sep 29, 2026

Decompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.

The English summary is being prepared. Showing the original description.

rohitg00/pro-workflow2.9KUpdated Sep 29, 2026

Capture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".

The English summary is being prepared. Showing the original description.

rohitg00/pro-workflow2.9KUpdated Sep 29, 2026

Smart context compaction with state preservation. Saves critical files, task progress, and working state before compaction, restores after. Use before manual compact or when auto-compact triggers.

The English summary is being prepared. Showing the original description.

rohitg00/pro-workflow2.9KUpdated Sep 29, 2026

Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.

The English summary is being prepared. Showing the original description.

rohitg00/pro-workflow2.9KUpdated Sep 29, 2026

See all skills by rohitg00

Report a problem with this skill