Bootstrap a durable "write like me" skill from the user's own Slack and email writing. Use during Assistant onboarding, after Slack/Gmail or email connectors are available, or when the user asks to learn their voice, infer writing style, create a personal writing persona, generate a write-like-me skill, analyze sent messages, or capture different writing postures across email and Slack.
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Create or update a repo-local writing-style skill from the user's real authored messages. The output should help future assistants draft in the user's voice without copying raw private messages into durable files.
Write the generated skill to .codex/skills/write-like-me/ unless the user asks
for a different name. Use:
.codex/skills/write-like-me/SKILL.md for the durable drafting workflow.codex/skills/write-like-me/references/style-profile.md for compact voice, posture, and examples.codex/skills/write-like-me/agents/openai.yaml if the repo uses skill UI metadataUse references/style-profile-template.md as the target shape.
Use references/generated-skill-template.md as the starting shape for the
generated SKILL.md.
Use connected Slack and email sources when available. Prefer authored messages:
If a connector is unavailable, say what is missing and proceed with available sources or ask whether to retry later.
Do not save raw Slack or email excerpts in durable files. Use short synthetic
examples that preserve style without exposing private content, names, deals,
secrets, or account details. Keep source evidence as compact descriptors such as
sent email follow-ups, March-June 2026 or Slack replies in project channels.
Ask before writing or updating the generated skill. Reading connected context for this bootstrap is allowed only when the user has asked for onboarding or this skill, and writing still requires explicit approval.
write-like-me skill and profile.The generated write-like-me skill should:
During Assistant onboarding, suggest this bootstrap after the first connected Slack/email scan finds enough authored writing to infer voice. The offer should be concrete:
I can also bootstrap a write-like-me skill from your sent email and Slack messages, split by posture like quick replies, pushback, delegation, intros, and status updates. Want me to do that?
If the user says yes, run the source scan, show the posture preview, and ask before writing the generated skill.
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Meet or work with Assistant, the user's relaxed ongoing work support. Use when the user invokes Assistant, starts or resumes an Assistant chat, asks what they should know, wants proactive work awareness, asks for reply drafts, asks to keep an eye on work, or needs follow-up/check-in help. On first contact, start with exactly "Hi, I'm your assistant." then decide whether onboarding is brand new, partial, or already established.
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Audit, de-slop, parameterize, modularize, or safely clean up AI-generated or AI-shaped backend/general code. Use for Python, TypeScript, or other implementation diffs that may contain duplicate helpers, fixture hacks, hard-coded test data, over-defensive control flow, broad exception wrappers, config-bag or boolean-mode soup, speculative scaffolding, hallucinated APIs/dependencies, local-idiom drift, brittle tests, or maintainability/safety/performance gaps after a feature, bugfix, prototype, or agent pass.
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Audit AI-generated, AI-shaped, or AI-looking frontend code, UI screenshots, and design diffs. Use for prompts like "audit AI frontend", "de-slop UI", "componentize this screen", "parameterize this React/Tailwind/shadcn UI", "make it responsive/accessible", or "review design-system drift"; check component APIs, reusable props/data models, modular composition, shared primitives/tokens, responsive resilience, accessibility, copy quality, hard-coded fixture screens, one-off CSS piles, and generic cards/gradients/fonts.
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Audit pasted chatbot output, AI-cleanup diffs, wiki drafts, Markdown/MDX/docs, and source-backed articles for generic AI fluff, LLM writing tells, weak audience model, lack of theory of mind, inflated significance, vague attribution, leaked tokens, placeholders, broken markup, fabricated or mismatched citations, and detector false positives. Use for requests like "AI writing audit", "check for AI slop", "find writing fluff", "does this sound like ChatGPT", "cleanup LLM tells", "make this less generic", "verify these citations", "detector flagged this", or text containing turn0search0, oaicite, oai_citation, contentReference, utm_source=chatgpt.com, malformed references, or wrong target-format markup.
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Help address review/issue comments on the open GitHub PR for the current branch using `oai_gh` or `gh`; verify auth first and prompt the user to authenticate if not logged in.
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Review git changes and split them into semantic commits with clear messages. Use when the user asks to commit work, clean up local history, or group a mixed diff into logical commits. Do not commit on main or master unless the user explicitly asks.
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