From mimirs
Answers hard open-ended questions about how a project works by synthesizing code, structure, git history, decisions, and discussion across multiple areas.
How this skill is triggered — by the user, by Claude, or both
Slash command
/mimirs:researchThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Goal: a thorough, cited answer to a specific question — pulled from across the whole project memory, not one file or one area. Where `explore` maps an area's structure, `research` answers a question by combining code, history, decisions, and discussion.
Goal: a thorough, cited answer to a specific question — pulled from across the whole project memory, not one file or one area. Where explore maps an area's structure, research answers a question by combining code, history, decisions, and discussion.
search "<sub-question>" for the relevant files, then read_relevant "<behavior>" for the actual functions/sections with line ranges. Use the extensions/dirs/excludeDirs filters to scope. search_symbols <name> for named things you already know.project_map(focus: <file>), depends_on/dependents <file>, impact <symbol> (transitive callers), trace from=<a> to=<b> (how one reaches another).search_commits "<topic>" for why and when it changed; file_history <file> for how a file evolved.search_checkpoints "<topic>" for recorded decisions and direction changes; search_conversation "<topic>" for the back-and-forth and alternatives considered.get_annotations (search across notes) for known bugs, constraints, and fragile spots that qualify the answer.Finish: answer each sub-question in plain language with a file:line, commit, or checkpoint citation; separate what the source proves from what is inferred; list what stayed unresolved instead of guessing.
npx claudepluginhub thewinci/mimirs --plugin mimirsAnswers factual/explanatory questions about the current project's codebase, architecture, conventions, and constraints with cited file:line evidence. Use for understanding how things work or why they are structured as they are.
Builds a mental model of unfamiliar codebases by searching, reading dependencies, and checking git history. Use when onboarding or before editing unknown code.
Researches codebase questions using parallel specialized agents, documenting existing code structure and behavior without suggesting changes.