ce-babysit-pr
Babysits an open GitHub PR until merge-ready. Use when asked to watch a PR over time — not for one-shot comment resolution or one CI failure. GitHub (incl.…
Document a solved problem as a durable repo learning. Use when verified work produced non-obvious reasoning absent from its final code, tests, or existing docs; avoid routine fixes whose artifacts already explain the lesson.
$ npx -y skills add everyinc/compound-engineering-plugin --skill ce-compound --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/ce-compoundContext preview
The summary Claude sees to decide when to auto-load this skill.
Document a solved problem as a durable repo learning. Use when verified work produced non-obvious reasoning absent from its final code, tests, or existing docs; avoid routine fixes whose artifacts already explain the lesson.
name: ce-compound description: Document a solved problem as a durable repo learning. Use when verified work produced non-obvious reasoning absent from its final code, tests, or existing docs; avoid routine fixes whose artifacts already explain the lesson. argument-hint: "[optional: brief context] [mode:non-interactive] [depth:lightweight|full]"
**Outcome:** one qualifying solved problem is written as a durable learning under `<root>/solutions/`, grounded against the current tree, discoverable by the next agent.
**Done:** a qualifying doc is written or updated, its frontmatter and claims validated, vocabulary capture recorded, and the mode's completion report emitted; when no learning qualifies, nothing is written and the report says why.
**One learning per run.** A session that produced several gets several sequential runs, never one batched run. Read `references/research.md`; it explains what batching breaks.
Document only a problem that is solved and verified.
<!-- ce-durable-bar:start --> A learning earns its place only when it holds durable project reasoning that is not readily recoverable from the final code, tests, types, comments, or existing documentation, and losing it would plausibly cause recurrence, material risk, or substantial rediscovery. Apply this counterfactual: if the learning document disappeared, would a future engineer reading the final implementation still be likely to repeat the mistake or redo substantial investigation? Completion, effort, and diff size do not establish eligibility. <!-- ce-durable-bar:end -->
If the counterfactual fails, write nothing and report why. Judge this from the session rather than asking. An explicit invocation requests the judgment now but does not lower the bar.
An existing learning that became materially inaccurate or incomplete qualifies because leaving it would mislead. Update that learning instead of creating a duplicate.
`ce-compound` does not bootstrap `CONCEPTS.md`. It seeds the learning's own area as a side effect, never the whole repo. Send a standalone request to create or bootstrap that file to `ce-compound-refresh`, then exit.
/ce-compound [brief context] /ce-compound mode:non-interactive depth:lightweight [context] /ce-compound mode:non-interactive depth:full [context]
Enter non-interactive mode when **either** holds: the arguments you were invoked with contain the `mode:non-interactive` token or its deprecated alias `mode:headless`, **or** the invocation makes non-interactive intent unmistakable, such as a caller or standing instruction asking to run `ce-compound` "headless", "non-interactively", "unattended", or "without prompts/questions". Both tokens together is not a conflict. Bare "automatically" or "auto-run" is **not** on its own a non-interactive signal: it speaks to *invoking* the skill, not to suppressing its prompts. An ambiguous or absent signal defaults to interactive. Tokens starting with `mode:` or `depth:` are flags, not context: strip them before treating the remainder as the brief context hint. Once detected, non-interactive mode applies for the entire run.
Depth is chosen only by an explicit token, only in non-interactive mode, and at most one depth token is accepted. `depth:lightweight` routes directly to Lightweight Mode. `depth:full` or no depth token enters Full Mode, including its automatic session-history probe. A non-interactive call carrying no depth token therefore behaves as it always has. Non-interactive lightweight asks no blocking questions and launches no subagents. If the invocation carries an unknown `depth:` token, multiple `depth:` tokens, or a `depth:` token without non-interactive intent, do not guess: emit the non-interactive failure report with the reason and end with `Documentation skipped`.
**Non-interactive mode asks nothing.** It asks no blocking question of any kind, in any phase, because a caller reaching this path has no human to answer one. Every non-interactive exit, including one taken before any phase runs, ends on a terminal signal a caller parses: `Documentation complete`, or `Documentation skipped` with the reason when no doc was written. Interactive mode asks only where the step's own reference says to, which is the Discoverability Check consent and, when several stale docs are in play, which refresh to run.
Resolve `<root>` when you first compose a `<root>/solutions/` path, and pass a subagent the resolved path rather than the config.
<!-- ce-docs-root:start --> **Resolve the CE artifact root `<root>` before composing any artifact path.**
<!-- ce-docs-root:end -->
**Only the orchestrator writes product files.** Phase 1 subagents write to per-run scratch only, and never touch `<root>/`, project instruction files, or any other tracked path.
The orchestrator writes the one learning under `<root>/solutions/`, plus two maintenance side effects that its own step describes: `CONCEPTS.md` during vocabulary capture, and — **only in interactive Full mode after consent** — a small discoverability line in a project instruction file. Two further writes exist **only in interactive Full mode when the user selects them at the assembly destination step**: a rule file inside a writable declared Compound Pack, and the `packs:
AI skills that make each unit of engineering work easier than the last. Compound Engineering is a plugin of 35 skills for AI coding agents.
Repo: everyinc/compound-engineering-plugin
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