From hw
Runs an interactive analysis lane for traceable investigation questions with enter, continue, end, and report commands.
How this skill is triggered — by the user, by Claude, or both
Slash command
/hw:analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
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Read config.yaml -> output.language
Use this skill for the user-visible Analysis lane. Analysis is an interactive investigation workflow for root cause, metric, or repository/system questions. It is not a broad audit, not lightweight chat, and not a build-first Milestone unless the ledger's follow-up proposal explicitly hands off to build work.
.pipeline/config.yaml should exist for a managed project; if missing, explain that /hw:init or /hw:plan is needed before durable Analysis state can be created..pipeline/state.yaml when present to recover prompt_state.analysis_summary..pipeline/cycle.yaml when present to choose the active Cycle or Milestone id..opencode/hypo-workflow.json.analysis on OpenCode before an analysis preset step or any boundary-controlled action.execution.analysis.interaction_mode as manual | hybrid | auto; default is hybrid.Supported forms:
/hw:analysis/hw:analysis enter "<question>"/hw:analysis continue/hw:analysis end/hw:analysis reportMeaning:
enter: start or focus the Analysis lane for one concrete investigation question.continue: resume from prompt_state.analysis_summary.ledger_path or the active continuation.end: conclude the lane with outcome, confidence, conclusion, and next_actions; do not mark a disproved hypothesis as failure by itself.report: summarize the ledger and latest Analysis report without dumping full hypotheses or experiment payloads.If the user omits an operation, infer it safely:
continueenter.pipeline/analysis/<cycle-or-milestone>/ledger.yaml.pipeline/analysis/<milestone-id>-analysis-ledger.yamlenter, initialize the ledger with question, environment_snapshot, empty hypotheses/experiments/observations, outcome: inconclusive, confidence: low, and empty next_actions.prompt_state.analysis_summary: milestone_id, question, ledger_path, hypothesis counts, experiment counts, conclusion, confidence, and updated_at.define_questiongather_contexthypothesizeexperimentinterpretconcludefollowup_proposal with workflow_kind: build, source_analysis, recommended_change, validation_plan, evidence_refs, and mode_required.end, ensure the ledger contains outcome, conclusion, confidence, next_actions, threats_to_validity, and ruled_out_alternatives.report, show the question, ledger path, outcome, confidence, conclusion, next action, and compact hypothesis/experiment counts.hybrid code change experiment.ask or confirm.manual, deny code changes and record the blocked experiment or proposed follow-up instead.auto, code changes may proceed inside configured boundaries, but destructive or external side effects still follow their explicit boundary.Status, report, progress, and final responses must stay compact:
questionledger_pathoutcome and confidencenext_actions.pipeline/analysis/<cycle-or-milestone>/ledger.yaml is the durable source of truth for Analysis evidence..pipeline/state.yaml must not store full hypotheses, experiments, or observations.prompt_state.analysis_summary.ledger_path; otherwise prefer the canonical path and mention the legacy path as imported evidence.safe_resume_command; it is a display and recovery hint only./hw:chat; when the task becomes implementation, use a follow-up proposal instead of silently converting the lane.define_question rather than fabricating a conclusion.status: blocked with blocked_reason; this can still support an inconclusive or blocked outcome.disproved/inconclusive.references/analysis-spec.mdreferences/analysis-ledger-spec.mdreferences/commands-spec.mdreferences/debug-spec.mdreferences/progress-spec.mdreferences/state-contract.mdtemplates/analysis/ledger.yamltemplates/analysis/report.mdSKILL.mdnpx claudepluginhub hypoxanthineovo/hypo-workflow --plugin hwRoot cause analyzer for AI coding sessions. Detects scope drift, rework patterns, and root causes to improve future prompts and repo health.
Auto-generates structured postmortems from completed campaigns, telemetry logs, and git history. Analyzes failures, safety system catches, scope drift, and recurring patterns.
Diagnoses and fixes wrong results, notebook errors, or data changes mid-analysis with structured course-correction.