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epic-blitz
// Three-round adversarial critique of epic drafts (high / mid / low abstraction) with revision after each round. Produces a chain-ready revised epic.
// Three-round adversarial critique of epic drafts (high / mid / low abstraction) with revision after each round. Produces a chain-ready revised epic.
| name | epic-blitz |
| description | Three-round adversarial critique of epic drafts (high / mid / low abstraction) with revision after each round. Produces a chain-ready revised epic. |
A three-round pipeline for rigorous epic critique and revision. Fifteen
independent critics across three abstraction levels (high, mid, low) review
the epic in panels of five. After each panel, a senior reviser adjudicates
the findings — accepting, rejecting, deferring, clarifying, or escalating —
and produces a revised epic. The final readiness stage assesses whether the
epic is ready for megaplan chain decomposition into milestone briefs.
Use Epic Blitz when:
megaplan chain.Do NOT use Epic Blitz for:
writing-panel-strict for that).draft (file, required): Path to the epic markdown draft to review.# Run with default profile
megaplan run epic-blitz path/to/epic.md
# Run with explicit inputs flag
megaplan run epic-blitz --inputs draft=path/to/epic.md
# Run with a specific profile
megaplan run epic-blitz path/to/epic.md --profile @epic-blitz:standard
Epic Blitz runs three critique-and-revision rounds, each at a different abstraction level:
existing_system_reuse — does the repo already solve this?conceptual_fit — does this belong in megaplan's model?missing_abstraction — is there a shared abstraction opportunity?epic_decomposition — are milestones sliced correctly?strategic_risk — is this solving the right problem?codebase_convention_fit — does the approach match existing patterns?data_artifact_model — are files and schemas shaped correctly?orchestration_semantics — do phase transitions and failures make sense?agent_model_assignment — are the right models on the right jobs?blast_radius — what could regress?implementation_feasibility — can an agent execute without guessing?testability — are concrete tests specified?edge_cases — what about empty findings, malformed output, interrupted runs?cli_ux_details — are names, flags, and errors clear?migration_backcompat — does this preserve existing behavior?After a successful run, the plan directory contains:
<plan_dir>/
├── high_panel/
│ ├── existing_system_reuse/v1.md
│ ├── conceptual_fit/v1.md
│ ├── missing_abstraction/v1.md
│ ├── epic_decomposition/v1.md
│ └── strategic_risk/v1.md
├── high_revise/v1.md
├── mid_panel/
│ ├── codebase_convention_fit/v1.md
│ ├── data_artifact_model/v1.md
│ ├── orchestration_semantics/v1.md
│ ├── agent_model_assignment/v1.md
│ └── blast_radius/v1.md
├── mid_revise/v1.md
├── low_panel/
│ ├── implementation_feasibility/v1.md
│ ├── testability/v1.md
│ ├── edge_cases/v1.md
│ ├── cli_ux_details/v1.md
│ └── migration_backcompat/v1.md
├── readiness/v1.md
└── state.json
The terminal artifact is readiness/v1.md — the final revised epic with a
chain-readiness assessment.
| Profile | Description |
|---|---|
@epic-blitz:standard | Default — Claude low-effort for all 15 critics and 3 revisers |
Pick the right megaplan profile, thinking-strength tier, and robustness level for the work in front of you — for both Codex and Claude harnesses. Consult before invoking megaplan.
Observe an in-flight megaplan — introspect state, trace events, diagnose blockages, detect drift. Companion to megaplan-decision. Use during and after a run, not before.
AI agent harness for coordinating Claude and GPT to make and execute extremely robust plans.
Methodology for running multi-profile LLM bake-offs via megaplan and presenting fair, blind-assessed comparisons. Cost/quality discipline, prompt hygiene, pre-merge gates, and reporting patterns. Use when the user says "bakeoff", "bake off", "megaplan bakeoff", or asks to compare profile mixes head-to-head.
Run megaplan plans and chains inside a provider-managed container (today, Railway) with a persistent workspace volume. Use when the run needs to outlast a local terminal session, span multiple repos, or share a long-lived dev box across concurrent chains. Covers `cloud.yaml` fields, `extra_repos[]` + `chain_session` multi-tenancy, the operator loop, and the gotchas that wedge fresh runs.
Run an epic — a chain of sprint-sized megaplans driven sequentially via `megaplan chain`. Use when the work is bigger than ~2 weeks and needs to be decomposed into multiple plans with state, ordering, and failure semantics handled by the harness.