Grill against the existing domain model. Stress-test a plan's terminology against `CONTEXT.md` and ADRs; update both inline as decisions crystallise. Trigger when user proposes a feature/refactor that touches business concepts and the project has documented domain language to honor — or when domain language is missing and needs capture.
Author a single new skill — produce a SKILL.md plus optional bundled references and scripts following Anthropic's progressive-disclosure conventions. Trigger when the user asks to "write a skill", "create a skill", "draft a SKILL.md", or "add a skill" for a specific capability. Distinct from repo onboarding workflows that write AGENTS.md and project conventions.
Decompose a plan, PRD, or spec into independently-grabbable vertical-slice issues (markdown file by default, GitHub issues via flag). Trigger when the user wants implementation tickets, work decomposition, or to convert an implementation plan into parallelizable work. Takes a plan file and emits atomic vertical slices.
Investigate a reported bug to root cause, then emit a TDD-shaped fix plan as an issue artifact. Trigger when the user reports a bug, says "triage", asks for issue investigation, or wants a fix plan before code changes.
Extract a domain glossary from the current dialogue; flag ambiguities, propose canonical terms, persist to `UBIQUITOUS_LANGUAGE.md`. Trigger when the user is hardening domain terminology, building a glossary, or fresh domain concepts surface in conversation without documented language.
Restructure Web-UI / human-triggered tasks into CLI + file-output loops the LLM can iterate alone. Open LLM-side observability — structured logs, file dumps, addressable scratchpads. Apply the trap-or-abandon decision: if a step cannot be looped, improve the harness rather than babysit. Trigger when the user mentions iterative grunt-work, "I have to push a button in a web UI to trigger this", monitoring dashboards, designing Claude-driven automation, or any workflow whose inner loop currently requires a human in the middle.
Surface concrete in-task-collaboration protocols when the user describes an AI workflow informally — URL-as-entity-reference, durable PR-comment threads as session memory, "fit the protocol" basics. Trigger when the user names entities by colloquial label instead of stable URL, asks "how should I structure this for Claude", pastes a screenshot when a URL would do, or describes a multi-step Claude workflow without a durable handle. Apply tactics reactively, not as a checklist.
Verbalized Sampling (VS) protocol for deep intent exploration before planning, now mode-aware. Default `exhaustive` mode runs the existing VS protocol verbatim (callers without a mode arg get unchanged behavior). Optional `collaborative` mode runs a two-way tip-sharing dialogue; optional `adversarial` mode walks the design tree one fork at a time with recommendations per question. Mode-selection is hybrid — auto-detect from invoking-context phrasing ("help me refine" → collaborative, "poke holes" → adversarial, otherwise exhaustive) with explicit override via `/askme adversarial|collaborative|exhaustive`. Use when starting ambiguous or complex tasks, when multiple interpretations exist, or when you need to explore diverse intent hypotheses and ask maximum clarifying questions before committing to an approach.