Enforces staged execution discipline on large tasks: a written stage plan, parallel delegation where the runtime supports it, a failable verification check at each stage, and a skeptical self-review before delivery. Trigger when the user explicitly asks ("do this thoroughly", "be systematic", "deep work mode") OR when the task objectively spans multiple files, multiple sources, or multiple sessions. Do NOT trigger on ordinary multi-step requests that a direct attempt handles fine. For a run pinned to a specific model, use fable-sonnet or fable-haiku instead.
Structured brainstorming when the user asks to explore options, compare approaches, or solve an ambiguous product, prompt, architecture, workflow, or design problem. Generates diverse options, clusters ideas, scores tradeoffs, and converges without generic ideation bloat. Avoid for straightforward implementation/debugging tasks.
Design lightweight evaluations for prompts, skills, agents, and workflow changes: before/after test prompts, success criteria, negative cases, edge cases, regression risks, and manual or scripted eval plans.
Review, debug, and improve user-provided or repo-visible prompts and agent instructions: AGENTS.md, skills, custom instructions, model configs, and prompt libraries. Optimizes for contradiction removal, trigger quality, context bloat reduction, eval ideas, and minimal high-leverage edits.
Search and read Atlassian Confluence content.
Interact with GitLab using `glab` CLI.
Access to Atlassian Jira with `jira` CLI.
Cheap first-stop for discovering private/internal/team/company agent skills from a local registry config before inventing a workflow or searching public skills. Finds hidden or unloaded SKILL.md files without adding every private repo to context or dotfiles.