
War Room Checkpoint
- 105 installs
- 325 repo stars
- Updated August 2, 2026
- athola/claude-night-market
Embed a lightweight reversibility and risk checkpoint inside commands so high-stakes branches escalate to full War Room deliberation instead of silent autopilot.
About
War Room Checkpoint is a journey-wide agent skill library that Athola-style commands call when a workflow hits a high-stakes fork—merge conflicts, irreversible deploys, scope cuts, or security-sensitive PR paths. It scores how reversible the pending choice is, computes confidence against profile thresholds, and either returns a quick express recommendation or escalates to the full War Room skill. Solo builders benefit because one-person teams skip formal review boards yet still need a consistent “stop and think” gate before damage is hard to undo. Wire it into `/do-issue`, `/pr-review`, or similar automation so every risky branch gets the same RS math instead of ad-hoc gut feel. After changes to checkpoint logic, run `make test-checkpoint` to keep escalation behavior trustworthy.
- Library skill invoked by commands—not end users directly—at critical decision points
- Calculates a Reversibility Score (RS) and confidence to choose express recommendation vs full War Room
- Profile thresholds tune how aggressive escalation is for your risk appetite
- Pairs with attune:war-room dependency for deep deliberation when RS is low
- Documented checkpoint flow, output format, and `make test-checkpoint` verification hook
War Room Checkpoint by the numbers
- 105 all-time installs (skills.sh)
- Ranked #1,341 of 3,282 Productivity & Planning skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/athola/claude-night-market --skill war-room-checkpointAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 105 |
|---|---|
| repo stars | ★ 325 |
| Security audit | 3 / 3 scanners passed |
| Last updated | August 2, 2026 |
| Repository | athola/claude-night-market ↗ |
What it does
Embed a lightweight reversibility and risk checkpoint inside commands so high-stakes branches escalate to full War Room deliberation instead of silent autopilot.
Files
War Room Checkpoint Skill
Lightweight inline assessment for determining whether a decision point within a command warrants War Room escalation.
Table of Contents
1. Purpose 2. When Commands Should Invoke This 3. Invocation Pattern 4. Checkpoint Flow 5. Confidence Calculation 6. Profile Thresholds 7. Output Format 8. Examples
Verification
Run make test-checkpoint to verify checkpoint logic works correctly after changes.
Purpose
This skill is not invoked directly by users. It is called by other commands (e.g., /do-issue, /pr-review) at critical decision points to:
1. Calculate Reversibility Score (RS) for the current context 2. Determine if full War Room deliberation is needed 3. Return either a quick recommendation (express) or escalate to full War Room
When Commands Should Invoke This
| Command | Trigger Conditions |
|---|---|
/do-issue | 3+ issues, dependency conflicts, overlapping files |
/pr-review | >3 blocking issues, architecture changes, ADR violations |
/architecture-review | ADR violations, high coupling, boundary violations |
/fix-pr | Major scope, conflicting reviewer feedback |
Invocation Pattern
Skill(attune:war-room-checkpoint) with context:
- source_command: "{calling_command}"
- decision_needed: "{human_readable_question}"
- files_affected: [{list_of_files}]
- issues_involved: [{issue_numbers}] (if applicable)
- blocking_items: [{type, description}] (if applicable)
- conflict_description: "{summary}" (if applicable)
- profile: "default" | "startup" | "regulated" | "fast" | "cautious"Checkpoint Flow
Step 1: Context Analysis
Analyze the provided context to extract:
- Scope of change (files, modules, services affected)
- Stakeholders impacted
- Conflict indicators
- Time pressure signals
Step 2: Reversibility Assessment
Calculate RS using the 5-dimension framework:
| Dimension | Assessment Question |
|---|---|
| Reversal Cost | How hard to undo this decision? |
| Time Lock-In | Does this crystallize immediately? |
| Blast Radius | How many components/people affected? |
| Information Loss | Does this close off future options? |
| Reputation Impact | Is this visible externally? |
Score each 1-5, calculate RS = Sum / 25.
Step 3: Mode Selection
Apply profile thresholds to determine mode:
if RS <= profile.express_ceiling:
mode = "express"
elif RS <= profile.lightweight_ceiling:
mode = "lightweight"
elif RS <= profile.full_council_ceiling:
mode = "full_council"
else:
mode = "delphi"Step 4: Response Generation
Express Mode (RS <= threshold)
Return immediately with recommendation:
response:
should_escalate: false
selected_mode: "express"
reversibility_score: {rs}
decision_type: "Type 2"
recommendation: "{quick_recommendation}"
rationale: "{brief_explanation}"
confidence: 0.9
requires_user_confirmation: falseEscalate Mode (RS > threshold)
Invoke full War Room and return results:
response:
should_escalate: true
selected_mode: "{lightweight|full_council|delphi}"
reversibility_score: {rs}
decision_type: "{Type 1B|1A|1A+}"
war_room_session_id: "{session_id}"
orders: ["{order_1}", "{order_2}"]
rationale: "{war_room_rationale}"
confidence: {calculated_confidence}
requires_user_confirmation: {true_if_confidence_low}Confidence Calculation
For escalated decisions, calculate confidence for auto-continue:
confidence = 1.0
- 0.10 * dissenting_view_count
- 0.20 if voting_margin < 0.3
- 0.15 if RS > 0.80
- 0.10 if novel_domain
- 0.10 if compound_decision
+ 0.20 if unanimous (cap at 1.0)
requires_user_confirmation = (confidence <= 0.8)Profile Thresholds
| Profile | Express | Lightweight | Full Council | Use Case |
|---|---|---|---|---|
| default | 0.40 | 0.60 | 0.80 | Balanced |
| startup | 0.55 | 0.75 | 0.90 | Move fast |
| regulated | 0.25 | 0.45 | 0.65 | Compliance |
| fast | 0.50 | 0.70 | 0.90 | Speed priority |
| cautious | 0.30 | 0.50 | 0.70 | Higher stakes |
Command-Specific Adjustments
| Command | Adjustment | Rationale |
|---|---|---|
| do-issue (3+ issues) | -0.10 | Higher risk with multiple issues |
| pr-review (strict mode) | -0.15 | Strict mode = higher scrutiny |
| architecture-review | -0.05 | Architecture inherently consequential |
Output Format
For Calling Command
Return a structured response that the calling command can act on:
## Checkpoint Response
**Source**: {source_command}
**Decision**: {decision_needed}
### Assessment
- **RS**: {reversibility_score} ({decision_type})
- **Mode**: {selected_mode}
- **Escalated**: {yes|no}
### Recommendation
{recommendation_or_orders}
### Control Flow
- **Confidence**: {confidence}
- **Auto-continue**: {yes|no}
{user_prompt_if_needed}Integration Notes
Calling Commands Should
1. Check checkpoint response's requires_user_confirmation 2. If true: present confirmation prompt and wait 3. If false: continue with orders or recommendation 4. Log checkpoint to audit trail
Failure Handling
If checkpoint invocation fails:
- Log warning with context
- Continue command execution without checkpoint
- Do NOT block the user's workflow
Audit Trail
Checkpoints are logged to:
~/.claude/memory-palace/strategeion/checkpoints/{date}/{checkpoint-id}.jsonEach file contains a CheckpointEntry with: checkpoint_id, session_id, phase, action, reversibility_score, dimensions, confidence, files_affected, and requires_user_confirmation.
After a war room session completes and persist_session() is called, an audit report is written automatically to:
~/.claude/memory-palace/strategeion/war-table/{session-id}/audit-report.jsonThe report consolidates: all checkpoints for the session, the expert panel, voting summary with unanimity score, escalation history, final decision and rationale, and a Merkle-DAG integrity verification block. The verification recomputes every node hash against the stored values so any tampering with deliberation content is detectable.
Use AuditTrailManager from scripts.war_room.audit_trail to query checkpoints or generate reports programmatically:
from scripts.war_room.audit_trail import AuditTrailManager
manager = AuditTrailManager()
checkpoints = manager.get_checkpoints("war-room-20260303-100000")
audited = manager.list_audited_sessions()Examples
Example 1: Low RS (Express)
Input:
source_command: "do-issue"
decision_needed: "Execution order for issues #101, #102"
issues_involved: [101, 102]
files_affected: ["src/utils/helper.py", "tests/test_helper.py"]Assessment:
- Reversal Cost: 1 (can revert commits)
- Time Lock-In: 1 (no deadline)
- Blast Radius: 1 (single utility module)
- Information Loss: 1 (all options preserved)
- Reputation Impact: 1 (internal)
RS: 0.20 (Type 2)
Response:
should_escalate: false
selected_mode: "express"
recommendation: "Execute in parallel - no dependencies detected"
confidence: 0.95
requires_user_confirmation: falseExample 2: High RS (Escalate)
Input:
source_command: "pr-review"
decision_needed: "Review verdict for PR #456"
blocking_items:
- {type: "architecture", description: "New service without ADR"}
- {type: "breaking", description: "API contract change"}
- {type: "security", description: "Auth flow modification"}
- {type: "scope", description: "Unrelated payment refactor"}
files_affected: ["src/auth/", "src/api/", "src/payment/", "src/services/new/"]Assessment:
- Reversal Cost: 4 (multi-service impact)
- Time Lock-In: 3 (PR deadline pressure)
- Blast Radius: 4 (cross-team impact)
- Information Loss: 3 (some paths closing)
- Reputation Impact: 2 (internal review)
RS: 0.64 (Type 1A)
Response:
should_escalate: true
selected_mode: "full_council"
war_room_session_id: "war-room-20260125-143025"
orders:
- "Split PR: auth changes separate from payment refactor"
- "Require ADR for new service before merge"
- "API change: add migration path, not blocking"
confidence: 0.75
requires_user_confirmation: trueRelated Skills
Skill(attune:war-room)- Full War Room deliberationSkill(attune:war-room)/modules/reversibility-assessment.md- RS framework
Related Commands
/attune:war-room- Standalone War Room invocation/do-issue- Issue implementation (uses this checkpoint)/pr-review- PR review (uses this checkpoint)/architecture-review- Architecture review (uses this checkpoint)/fix-pr- PR fix (uses this checkpoint)
Exit Criteria
- [ ] A structured checkpoint response is returned with all required fields:
reversibility_score
(0.0-1.0), selected_mode (express / lightweight / full_council / delphi), should_escalate (boolean), and recommendation or orders.
- [ ] Any response with
reversibility_score> profile threshold hasshould_escalate: true
and triggers the full War Room via Skill(attune:war-room) before returning.
- [ ] Any response with
confidence<= 0.8 setsrequires_user_confirmation: trueand presents
a confirmation prompt to the user rather than auto-continuing.
- [ ] The checkpoint is logged to
~/.claude/memory-palace/strategeion/checkpoints/{date}/{checkpoint-id}.json; if this write fails, the calling command proceeds and logs a warning rather than blocking the workflow.
Related skills
FAQ
Is War Room Checkpoint safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.