Research Workflow — Full Pipeline

Research Workflow — Full Pipeline

Description

Runs the complete research pipeline: Brainstorming → Planning → Implementation → Testing & Visualization → Reporting. Orchestrates all phases with user checkpoints between each.

Usage

/research "research topic" [--domain physics|ai_ml|statistics|mathematics|paper] [--weights '{"novelty":0.4,...}'|adaptive] [--depth low|medium|high|max] [--personas N] [--claude-only] [--substitute "Gemini -> Opus"] [--resume <output_dir>]

Arguments

• $ARGUMENTS — The research topic (required) and optional flags:
  • --domain — Research domain (physics, ai_ml, statistics, mathematics, paper). Auto-inferred if omitted.
  • --weights — Scoring mode for direction ranking:
    • Omitted (default): Holistic ranking — Claude ranks directions by expert judgment with detailed rationale. No numeric weights.
    • JSON object: Weighted scoring with dimension weights summing to 1.0.
    • adaptive: Claude analyzes the prompt and recommends weights for user confirmation. See /research-brainstorm for full details.
  • --depth — Controls brainstorm review depth (default: medium):
    • low — Skip cross-review, go directly to synthesis (fastest, lowest cost)
    • medium — Standard one-shot cross-review (default)
    • high — Cross-review + adversarial debate (most thorough, highest cost)
    • max — Hierarchical MAGI-in-MAGI: N persona subagents run parallel mini-MAGI pipelines, then meta-review + adversarial debate across all perspectives (deepest, highest cost)
  • --personas N|auto — Number of domain-specialist subagents for --depth max (default: auto, range: 2-4). When auto, Claude analyzes the topic to determine the optimal persona count. Ignored for other depth levels.
  • --claude-only — Replace all Gemini/Codex MCP calls with Claude Agent subagents across all phases. Use when external model endpoints are unavailable. Forwarded to all sub-skills automatically.
  • --substitute "Agent -> Opus" — Replace a specific MAGI agent with Claude (Opus). Accepted: "Gemini -> Opus", "Codex -> Opus". Can be specified multiple times. Forwarded to all sub-skills. If both agents are substituted, equivalent to --claude-only. Mutually exclusive with --claude-only (--claude-only takes precedence).
  • --resume <output_dir> — Resume an interrupted pipeline from a previous output directory. See Resume Protocol below.

Instructions

Shared rules: Read ${CLAUDE_PLUGIN_ROOT}/shared/rules.md before starting. §MCP, §Visualization, §LaTeX, §PhaseGate, §Substitute apply to this skill. Inline fallback (if shared rules unavailable): Gemini models: gemini-3.1-pro-preview → gemini-2.5-pro → Claude. Codex: gpt-5.4. All math in LaTeX only (no Unicode). scienceplots ['science','nature'], 300dpi PNG+PDF, Nature widths (3.5/7.2in). Use @filepath for MCP file refs; subagents use Read tool.

MCP Tool Rules

See §MCP, §Visualization, §LaTeX in shared rules. Additionally:

• Codex: Use mcp__codex-cli__brainstorm for ideation, mcp__codex-cli__ask-codex for analysis/review.
• Context7: Use during implementation phase for library documentation lookups.
• When to search: prior work verification, methodological precedents, dataset/library availability, related approaches, fact-checking quantitative claims

Path Safety Rule

ALL artifacts MUST be written under {output_dir}/. Never write files directly to the project root or any path outside outputs/.

• {output_dir} is the absolute path stored in .workspace.json at the output directory root.
• Before writing any file: if {output_dir} is uncertain (e.g., after context compression), recover it:
  1. Glob for outputs/*/.workspace.json, select the most recently modified match.
  2. Read the file and extract output_dir.
• Subagent prompts and sub-skill invocations: always include the absolute {output_dir} path.

When this skill is invoked, execute the full research pipeline below. Always pause for user confirmation between phases.

---

Phase Gate Protocol

See §PhaseGate in shared rules. Phase-specific checklists:

Phase	Checklist Items
Plan	Completeness (all objectives addressed), methodology soundness, resource feasibility, risk identification
Implement	Code correctness, alignment with plan, error handling, dependency management
Execute	Exit code 0, results/ populated (or EXISTING/PARTIAL with user acknowledgment), pre_execution_status.json written
Test	Tier 1 unit test coverage, edge case handling, Common Restrictions fulfilled (plot_manifest.json, dual format, dependency spec), result reproducibility

---

Resume Protocol

When --resume <output_dir> is provided, the pipeline skips initialization and infers the current phase from the presence of key artifact files in the output directory. This avoids requiring the LLM to maintain a separate state file — the artifacts themselves serve as checkpoints.

Unified semantics: --resume always accepts the workspace root directory (e.g., outputs/topic_20260309_v1/). Whether resuming a research pipeline or a write sub-pipeline, the same root path is used. The system infers the correct sub-context internally.

Phase inference rules (evaluated top-down; first match wins):

Condition	Inference	Action
report.md exists	Pipeline complete	Inform user; offer to re-run specific phases
plots/plot_manifest.json exists	Test phase complete	Resume from the Report phase
results/pre_execution_status.json exists (or pre_execution_status.md for legacy v0.8.x)	Execute phase complete	Resume from the Test phase
src/ contains at least one source file	Implement phase complete	Resume from the Execute phase
plan/research_plan.md exists	Plan phase complete	Resume from the Implement phase
brainstorm/synthesis.md exists	Brainstorm phase complete	Resume from the Plan phase
None of the above	No phase complete	Start from the Brainstorm phase

Checkpoint hash validation (when checkpoint files exist): After determining the resume phase from artifact presence, check if a checkpoint file exists for the detected completed phase (e.g., plan/plan_checkpoint.json). If found:

1. Read the input_hashes field
2. Recompute hashes of the referenced input files
3. If hashes match: proceed with resume (inputs unchanged)
4. If hashes differ: warn the user that upstream artifacts have changed since this phase completed. Ask: "(a) Re-run this phase with updated inputs, or (b) Proceed anyway with existing outputs?"

Checkpoint validation is additive — if no checkpoint file exists (e.g., from a pre-v0.9.0 run), fall back to the existing artifact-presence inference.

Resume procedure:

1. Read {output_dir}/.workspace.json to restore the absolute output path and metadata.
2. Use the Glob tool to check for each artifact in the order above.
3. Read the first few lines of the matched artifact to confirm it is non-empty.
4. Announce to the user: detected phase, output directory, and which phase will be resumed.
5. Read the domain template if brainstorm/personas.md or brainstorm/weights.json exist (to restore context).
6. Continue the pipeline from the inferred phase, skipping all prior phases.

Important: On resume, do NOT re-create the output directory or overwrite existing artifacts. Append or create only the artifacts for the resumed phase and beyond.

---

Artifact Contract Protocol

Before starting each phase (2 through 5), verify that the required predecessor artifacts exist and are non-empty. Use the Glob and Read tools for deterministic, tool-based validation — do not rely on memory or assumptions.

Required artifacts per phase:

Phase	Required Artifacts	Validation Method
Plan	brainstorm/synthesis.md	Glob + Read first 3 lines (non-empty)
Implement	plan/research_plan.md	Glob + Read first 3 lines (non-empty)
Execute	At least one source file in src/, plan/research_plan.md with execution_cmd in frontmatter	Glob src/**/* + Read frontmatter
Test	At least one source file in src/, plan/research_plan.md	Glob src/**/* + Glob for plan. Note: results/pre_execution_status.json is optional — its absence means Tier 2 integration tests will be skipped (fall back to .md for legacy)
Report	brainstorm/synthesis.md, plan/research_plan.md, at least one source file in src/, plots/plot_manifest.json	Glob for each path

On validation failure:

1. List the missing or empty artifacts with specific file paths.
2. Ask the user: "The following artifacts are missing: [list]. Would you like to (a) go back and generate them, or (b) proceed anyway?"
3. If the user chooses to proceed, continue with a warning note in the phase gate.

---

Initialization

1. Parse $ARGUMENTS:
   • Extract the research topic (everything before flags or the entire string)
   • Extract domain if --domain is specified; otherwise infer from topic keywords
   • Parse --resume <output_dir>: If provided, skip steps 2-6 and execute the Resume Protocol above. The pipeline will jump directly to the inferred phase.
2. Create the output directory structure:

   outputs/{sanitized_topic}_{YYYYMMDD}_v{N}/
   ├── .workspace.json            # Workspace anchor (absolute path)
   ├── brainstorm/
   ├── plan/
   ├── src/
   ├── tests/
   └── plots/
   

   • Sanitize topic: lowercase, spaces→underscores, remove special chars, max 50 chars
   • Date format: YYYYMMDD (today's date)
   • Version: Glob for outputs/{sanitized_topic}_{YYYYMMDD}_v*/ and set N = max existing + 1 (start at v1)
   • Write workspace anchor: Save .workspace.json at the output directory root:

     {
       "output_dir": "{absolute_path_to_output_dir}",
       "topic": "{original_topic}",
       "domain": "{domain}",
       "created_at": "{ISO-8601 timestamp}"
     }
     

     Use pwd or equivalent to resolve the absolute path. This file anchors all subsequent file writes across all phases.
3. If the domain has a template in ${CLAUDE_PLUGIN_ROOT}/templates/domains/, read it as context.
4. Parse --weights: If provided, validate and store. If omitted, domain defaults will be used by the brainstorm sub-skill.
5. Parse --depth: Accept low, medium (default), high, or max.
6. Parse --personas N|auto: Accept integer 2-4 or the string auto (default: auto). Only used when --depth max; ignored otherwise.
   • If auto: Defer persona count determination to the Brainstorm phase (sub-skill Step 0b), where Claude analyzes the topic to select the optimal N.
   • If an explicit integer is given: Use that value directly.
7. Parse --claude-only: Boolean flag (default: false). When present, all Gemini/Codex MCP calls across all phases are replaced with Claude Agent subagents. This flag is forwarded to every sub-skill invocation.
8. Parse --substitute: Accept zero or more --substitute "Agent -> Opus" flags. Valid agent names: Gemini, Codex. Valid target: Opus. Forwarded to every sub-skill invocation. Mutually exclusive with --claude-only (--claude-only takes precedence). If both agents are substituted, treat as --claude-only.

Flag forwarding: --claude-only and --substitute flags are forwarded to every sub-skill invocation (brainstorm, plan, implement, execute, test, report). Each sub-skill applies the replacement rules to its own MCP calls.

9. Announce to the user: topic, domain, output directory, active weights (user-provided, holistic, or domain default), depth level, persona count (if max; show auto if no explicit --personas was given), claude-only mode (if active), and agent substitutions (if any).

---

Brainstorm Phase

Execute the /magi-researchers:research-brainstorm workflow, forwarding all flags: --domain, --weights, --depth, --personas (only when --depth max), --claude-only (if active), and --substitute (if any).

Step 0 — Setup:

• Brainstorm sub-skill parses weights and depth flags
• Outputs: brainstorm/weights.json

Step 0a — Research Direction Document (Phase 1-4):

• Generates the research direction document including a broad literature survey (Phase 2: OpenAlex + WebSearch)
• Outputs: brainstorm/research_direction.md

Step 0b — Persona Casting (informed by research_direction.md):

• Assigns expert personas based on the research direction established in Step 0a
• Outputs: brainstorm/personas.md
• Personas are used in all subsequent phases where MAGI models are invoked

Step 0c — Adaptive Weights (if --weights adaptive):

• Claude analyzes the prompt and research_direction.md to recommend scoring weights for user confirmation
• Outputs: updated brainstorm/weights.json

Step 0d — Pre-flight (persona-targeted searches):

• Loads Phase 2 literature from brainstorm/research_direction.md (Sections 5 and 5a) as baseline context
• Runs only persona-targeted supplemental searches (no broad re-query of Step 0a literature)
• Outputs: brainstorm/preflight_context.md, per-persona briefing files

Step 1a — Parallel Brainstorming (with personas):

• Gemini and Codex brainstorm independently with assigned personas
• Save to brainstorm/gemini_ideas.md and brainstorm/codex_ideas.md

Step 1b — Cross-Check (--depth medium|high):

• Gemini reviews Codex ideas → brainstorm/gemini_review_of_codex.md
• Codex reviews Gemini ideas → brainstorm/codex_review_of_gemini.md
• Skipped if --depth low

Step 1b+ — Adversarial Debate (--depth high only):

• Top 3 disagreements identified → Round 2 defend/concede/revise
• Outputs: brainstorm/debate_round2_gemini.md, brainstorm/debate_round2_codex.md

Steps 1-max-a~d — Hierarchical MAGI-in-MAGI (--depth max only):

• Layer 1: N persona subagents spawned in parallel, each running a mini-MAGI pipeline (Gemini brainstorm + Codex brainstorm + cross-review + conclusion) → brainstorm/persona_{i}/
• Layer 2: Gemini and Codex meta-review all N conclusions; Claude extracts top 3 disagreements; adversarial debate (defend/concede/revise) → brainstorm/meta_review_*.md, brainstorm/meta_debate_*.md
• Layer 3: Claude produces enriched synthesis with cross-persona consensus, unique contributions, debate resolution, and emergent insights → brainstorm/synthesis.md

Step 1c — Synthesis (with weighted scoring):

• Claude reads all documents, applies weights from weights.json to rank directions
• Creates brainstorm/synthesis.md with weighted scores and debate resolution (if applicable)
• Present top research directions to user

Checkpoint: Emit brainstorm/brainstorm_checkpoint.json:

{
  "schema_version": "1.0.0",
  "phase": "brainstorm",
  "completed_at": "{ISO-8601 timestamp}",
  "input_hashes": {},
  "output_artifacts": ["brainstorm/synthesis.md", "brainstorm/gemini_ideas.md", "brainstorm/codex_ideas.md"]
}

>>> USER CHECKPOINT: Confirm research direction <<<

---

Plan Phase

Artifact Contract: Verify brainstorm/synthesis.md exists and is non-empty (Glob + Read first 3 lines). On failure, follow the Artifact Contract Protocol above.

Step 2a — Plan Drafting:

1. Based on user-confirmed direction from the Brainstorm phase:
   • Define specific research objectives
   • Outline the technical approach (algorithms, models, data)
   • Specify implementation requirements (language, libraries, compute)
   • Design the test strategy
   • Plan visualizations
2. Save to plan/research_plan.md, beginning with a YAML frontmatter block:

   ---
   title: "{research topic}"
   domain: "{physics|ai_ml|statistics|mathematics|paper}"
   languages: ["{primary language(s) planned}"]
   ecosystem: ["{package manager(s) planned}"]
   execution_cmd: ""          # filled in after the Implement phase
   dry_run_cmd: ""            # filled in after the Implement phase
   expected_outputs: []       # filled in after the Implement phase
   estimated_runtime: ""      # filled in after the Implement phase
   ---
   

   Leave execution fields empty for now — the Implement phase will populate them.

Step 2b — Murder Board:

Submit the research plan to Gemini as a hostile reviewer to stress-test for critical flaws:

mcp__gemini-cli__ask-gemini(
  prompt: "You are a hostile but fair research reviewer. Your job is to find fatal flaws in this research plan — flaws that would cause the research to fail, produce invalid results, or waste significant effort.\n\nAttack the plan on these dimensions:\n1. **Methodological flaws**: Are there fundamental errors in the proposed approach?\n2. **Missing assumptions**: What unstated assumptions could invalidate results?\n3. **Scalability risks**: Will this approach break on realistic problem sizes?\n4. **Data/resource gaps**: Are required datasets, compute, or libraries actually available?\n5. **Novelty concerns**: Has this exact approach been tried and failed before?\n\nFor each flaw found, rate its severity (Critical/Major/Minor) and explain the likely failure mode.\n\nResearch Plan:\n@{output_dir}/plan/research_plan.md",
  model: "gemini-3.1-pro-preview"  // fallback chain applies
)

Save to plan/murder_board.md.

If --claude-only or Gemini is substituted: Per §SubagentExec — Adversarial-Critical reviewer: Read research_plan.md. Attack on methodological flaws, missing assumptions, scalability risks, data/resource gaps, novelty concerns. Save to plan/murder_board.md.

Step 2c — Mitigations:

Claude reviews each flaw from the murder board and documents a mitigation strategy:

1. For each identified flaw:
   • Acknowledge or dispute the flaw (with reasoning)
   • If acknowledged: propose a concrete mitigation (plan modification, fallback strategy, or scoping change)
   • Rate mitigation confidence: High, Medium, Low
2. If any mitigation has Low confidence, perform one revision pass: update the relevant section of research_plan.md and re-assess.
3. Save to plan/mitigations.md.

Phase Gate: Plan — Execute the Phase Gate Protocol with Plan checklist.

Checkpoint: Emit plan/plan_checkpoint.json:

{
  "schema_version": "1.0.0",
  "phase": "plan",
  "completed_at": "{ISO-8601 timestamp}",
  "input_hashes": {
    "brainstorm/synthesis.md": "sha256:{hash}"
  },
  "output_artifacts": ["plan/research_plan.md", "plan/murder_board.md", "plan/mitigations.md", "plan/phase_gate.md"]
}

>>> USER CHECKPOINT: Approve research plan <<< Present to user: plan summary, murder board highlights, mitigations, and gate result.

---

Implement Phase

Artifact Contract: Verify plan/research_plan.md exists and is non-empty (Glob + Read first 3 lines). On failure, follow the Artifact Contract Protocol above.

Execute the /magi-researchers:research-implement workflow:

1. Follow research_plan.md to implement code in src/
2. Use Context7 for library documentation as needed
3. Validate basic functionality

Phase Gate: Implement — Execute the Phase Gate Protocol with Implement checklist.

Checkpoint: Emit src/implement_checkpoint.json:

{
  "schema_version": "1.0.0",
  "phase": "implement",
  "completed_at": "{ISO-8601 timestamp}",
  "input_hashes": {
    "plan/research_plan.md": "sha256:{hash}"
  },
  "output_artifacts": ["src/phase_gate.md"]
}

4. Present implementation summary to user, including gate result.

>>> USER CHECKPOINT: Review implementation <<<

---

Execute Phase

Artifact Contract: Verify at least one source file in src/ and plan/research_plan.md with execution_cmd in frontmatter. On failure, follow the Artifact Contract Protocol above.

Execute the /magi-researchers:research-execute workflow:

• Read execution_cmd and dry_run_cmd from plan/research_plan.md YAML frontmatter
• Run dry-run first (fast sanity check); fix minor errors before full run
• Run full execution; capture output to results/run_log.txt
• Write results/pre_execution_status.json (state: SUCCESS / FAILED / PARTIAL / EXISTING)
• For long-running jobs (> 15 min): inform user, recommend running externally then resuming

Phase Gate: Execute — Execute the Phase Gate Protocol with Execute checklist.

Checkpoint: Emit results/execute_checkpoint.json:

{
  "schema_version": "1.0.0",
  "phase": "execute",
  "completed_at": "{ISO-8601 timestamp}",
  "input_hashes": {
    "plan/research_plan.md": "sha256:{hash}",
    "src/": "sha256:{combined_hash}"
  },
  "output_artifacts": ["results/pre_execution_status.json", "results/run_log.txt"]
}

>>> USER CHECKPOINT: Review execution results <<< Present: execution status, generated artifacts, any errors encountered.

---

Test & Visualize Phase

Artifact Contract: Verify at least one source file exists in src/ (Glob src/**/*) and plan/research_plan.md exists. results/pre_execution_status.json is optional — its absence causes Tier 2 integration tests to be skipped (not a pipeline failure). Fall back to .md for legacy workspaces.

Execute the /magi-researchers:research-test workflow:

Step 0 — Workspace Detection:

• Scan src/ for package managers and file extensions to detect languages and ecosystems
• Check results/pre_execution_status.json to determine data availability for Tier 2 tests

Step 1 — Test Strategy Discussion:

• Consult Gemini for test suggestions; propose two-tier plan (Tier 1 unit / Tier 2 integration)
• Choose testing tools matching detected workspace languages
• Present to user for approval

Step 2 — Test Implementation:

• Write Tier 1 unit tests (mock-based, always run)
• Write Tier 2 integration tests (guarded by results/ availability)
• Run tests with the native test runner for each detected language
• Report results

Step 3 — Visualization:

• Choose visualization tools matching detected workspace
• Load data from results/ if available; compute inline otherwise
• All plots must follow Common Restrictions: PNG + PDF/SVG, registered in plot_manifest.json

Step 4 — Plot Manifest:

• Generate plots/plot_manifest.json using the fixed schema
• All plots registered here regardless of which tool generated them
• This manifest is the primary input for the Report phase's plot integration

Phase Gate: Test — Execute the Phase Gate Protocol with Test checklist.

Checkpoint: Emit tests/test_checkpoint.json:

{
  "schema_version": "1.0.0",
  "phase": "test",
  "completed_at": "{ISO-8601 timestamp}",
  "input_hashes": {
    "src/": "sha256:{combined_hash}",
    "results/pre_execution_status.json": "sha256:{hash} (omit key if file absent)"
  },
  "output_artifacts": ["plots/plot_manifest.json"]
}

If results/pre_execution_status.json does not exist, omit it from input_hashes rather than storing a placeholder.

>>> USER CHECKPOINT: Review test results and visualizations <<<

---

Report Phase

Artifact Contract: Verify all of the following exist (Glob for each): brainstorm/synthesis.md, plan/research_plan.md, at least one source file in src/, and plots/plot_manifest.json. On failure, follow the Artifact Contract Protocol above.

If --depth max was used: also check for brainstorm/all_conclusions.md, brainstorm/meta_review_gemini.md, brainstorm/meta_review_codex.md, brainstorm/meta_debate_gemini.md, brainstorm/meta_debate_codex.md (these replace debate_round2_*.md files)

Execute the /magi-researchers:research-report workflow:

Step 0 — Gather & Health Check:

• Inventory all phase outputs
• Read plots/plot_manifest.json (create if missing but plots exist)
• Verify all plot files are present and valid

Step 0.5 — Plot Style Validation:

• Validate all existing plots for scienceplots compliance (['science', 'nature'] style)
• Regenerate non-compliant plots before content assembly
• Update plots/plot_manifest.json with style metadata

Step 1 — Content Assembly & Plot Mapping:

• Read all phase artifacts
• Map manifest plots to report sections using section_hint tags

Step 2 — Report Draft with Integrated Plots:

• Generate report.md using ${CLAUDE_PLUGIN_ROOT}/templates/report_template.md structure
• Actively embed plots from the manifest with contextualizing paragraphs and quantitative observations
• Include all sections: Background, Brainstorming, Methodology, Implementation, Results, Testing, Conclusion

Step 3 — Gap Detection & Plot Generation Loop (max 2 iterations):

• Identify claims without supporting figures or results needing visualization
• Generate new plots (write matplotlib code → execute → save to plots/ → update manifest)
• Re-draft affected sections with newly generated plots

Step 4 — MAGI Traceability Review (parallel cross-verification):

• Inject personas: If brainstorm/personas.md exists, prepend the assigned personas to Gemini and Codex review prompts for continuity
• Agent substitution: If --claude-only or --substitute is active, substituted agents use Claude Agent subagents with their respective cognitive styles (Creative-Divergent for Gemini, Analytical-Convergent for Codex). Non-substituted agents use their MCP tools normally.
• Gemini (BALTHASAR) reviews for scientific rigor: orphaned claims, orphaned plots, weak claim-evidence links, caption quality
• Codex (CASPER) reviews for visualization quality: missing visualizations, plot-narrative mismatch, encoding improvements, reproducibility gaps, and scienceplots style compliance
• Claude (MELCHIOR) synthesizes both reviews — consensus issues are high-priority fixes, divergent suggestions evaluated on merit

Step 5 — Write Final Report:

• Save finalized report.md with version tracking (report_versions.json)
• Schema version is 1.1.0; each version entry includes a structured changes array tracking what was modified
• Present summary with plot integration statistics

Step 6 — Feedback Loop:

• Report skill handles Tier 1 (Cosmetic) and Tier 2 (Visualization) internally
• If Tier 3 escalation occurs, control returns to orchestrator Step R2

>>> USER CHECKPOINT: Review and finalize report <<<

---

Report Outer Loop (Tier 3 Handling)

Step R1: Checkpoint

Present report location, version, any Tier 1/2 revisions already applied. Options:

• Approve → Completion
• Cosmetic/Visualization → re-enter Report skill Step 6
• Substantive → Step R2

Step R2: Pipeline Re-entry (max 2 iterations)

1. Classify re-entry point from feedback:

   Trigger	Re-entry Phase	Phases to re-run
   Methodology/approach change	Plan	Plan → Implement → Execute → Test → Report
   Code bug, new analysis	Implement	Implement → Execute → Test → Report
   Different parameters, rerun	Execute	Execute → Test → Report
   New visualization strategy	Test	Test → Report

2. Present re-entry plan to user for confirmation.

3. On confirmation: a. Archive report.md → report_v{N}.md, update report_versions.json b. Delete report.md (reset resume protocol)

   Rollback note: If the re-entry pipeline fails before a new report.md is produced, inform the user that the previous report is preserved as report_v{N}.md and can be restored by copying it back to report.md. c. Execute pipeline from re-entry phase d. Report skill generates new version → return to Step R1

---

Completion

Announce completion with:

• Output directory location
• Final report version and revision history
• Summary of all generated artifacts
• Any follow-up suggestions

Notes

• If any phase fails, stop and inform the user with clear error context
• User can skip phases by saying "skip" at any checkpoint
• The workflow state is maintained through artifact files — use --resume <output_dir> to resume an interrupted pipeline from the last completed phase
• Each phase skill can also be run independently outside this pipeline