Best for
- Calculate Reversibility Score (RS) for the current context
- Determine if full War Room deliberation is needed
- Return either a quick recommendation (express) or escalate to full War Room
athola/claude-night-market/plugins/attune/skills/war-room-checkpoint/SKILL.md
Assesses decision reversibility and risk at critical checkpoints. Use when a workflow reaches a high-stakes branch needing escalation check.
Decision brief
Lightweight inline assessment for determining whether a decision point within a command warrants War Room escalation.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/athola/claude-night-market --skill "plugins/attune/skills/war-room-checkpoint"Inspect the Agent Skill "war-room-checkpoint" from https://github.com/athola/claude-night-market/blob/6720bb5cdeadeea6de6e4786a449126b3d417536/plugins/attune/skills/war-room-checkpoint/SKILL.md at commit 6720bb5cdeadeea6de6e4786a449126b3d417536. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Run make attune-test from the repository root to verify checkpoint logic still works after changes.
Analyze the provided context to extract: - Scope of change (files, modules, services affected) - Stakeholders impacted - Conflict indicators - Time pressure signals
Calculate RS using the 5-dimension framework:
Apply profile thresholds to determine mode:
Return immediately with recommendation:
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 94/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 331 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Lightweight inline assessment for determining whether a decision point within a command warrants War Room escalation.
Run make attune-test from the repository root to verify checkpoint
logic still works after changes.
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:
| 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 |
| Situation | Use instead |
|---|---|
| A user asks for deliberation directly | Skill(attune:war-room) |
| The decision is cheap to reverse (high RS) | Proceed without a checkpoint |
| A panel already ruled on this decision | The prior verdict |
This skill decides whether deliberation is warranted and returns fast when it is not. A command that checkpoints every decision pays the scoring cost to be told to proceed almost every time, and re-checkpointing a settled call re-litigates it.
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"
Analyze the provided context to extract:
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.
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"
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: false
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}
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 | 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 | 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 |
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}
requires_user_confirmationorders or recommendationIf checkpoint invocation fails:
Checkpoints are logged to:
~/.claude/memory-palace/strategeion/checkpoints/{date}/{checkpoint-id}.json
Each 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.json
The 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()
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:
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: false
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:
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: true
Skill(attune:war-room) - Full War Room deliberationSkill(attune:war-room)/modules/reversibility-assessment.md - RS framework/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)reversibility_score
(0.0-1.0), selected_mode (express / lightweight / full_council / delphi), should_escalate
(boolean), and recommendation or orders.reversibility_score > profile threshold has should_escalate: true
and triggers the full War Room via Skill(attune:war-room) before returning.confidence <= 0.8 sets requires_user_confirmation: true and presents
a confirmation prompt to the user rather than auto-continuing.~/.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.Frequently asked questions
Lightweight inline assessment for determining whether a decision point within a command warrants War Room escalation.
The source record exposes this install command: npx skills add https://github.com/athola/claude-night-market --skill "plugins/attune/skills/war-room-checkpoint". Inspect the command and pinned source before running it.
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