Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/athola/claude-night-marketWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/athola/claude-night-market/war-room)<a href="https://agentmods.dev/commands/athola/claude-night-market/war-room"><img src="https://agentmods.dev/badge/commands/athola/claude-night-market/war-room/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/athola/claude-night-market/war-room"><img src="https://agentmods.dev/badge/commands/athola/claude-night-market/war-room.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.03311 |
| Opus 5 | $0.00013 | $0.01656 |
| Sonnet 5 | $0.00005 | $0.00662 |
| Haiku 4.5 | $0.00003 | $0.00331 |
Grade A, and why
war-room scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 420 lines — stays where its author put it; the contents beside it link to each section on GitHub.
War Room Command
Orchestrate multi-expert deliberation for complex strategic decisions with reversibility assessment and adversarial review.
When To Use
Use this command when you need to:
- Make critical, high-stakes decisions
- Evaluate irreversible or costly changes
- Compare architectural approaches with trade-offs
- Resolve conflicting expert opinions
- Pressure-test assumptions before commitment
- Build consensus on strategic direction
- Assess decision reversibility
When NOT To Use
Avoid this command if:
- Decision is trivial or easily reversible
- Single obvious path exists
- Already decided and need implementation
- Routine operational choices
- Quick tactical adjustments
Usage
# Basic invocation with problem statement
/attune:war-room "What architecture should we use for the payment system?"
# With context files
/attune:war-room "Best API versioning strategy" --files src/api/**/*.py
# Reversibility assessment only (no deliberation)
/attune:war-room "Database migration to MongoDB" --assess-only
# Force express mode (Type 2 decisions)
/attune:war-room "Which logging library?" --express
# Use startup threshold profile (more aggressive)
/attune:war-room "New feature architecture" --thresholds startup
# Use regulated profile (more conservative)
/attune:war-room "Data retention policy" --thresholds regulated
# Force full council (all experts)
/attune:war-room "Migration approach" --full-council
# High-stakes Delphi mode (iterative until consensus)
/attune:war-room "Platform decision" --delphi
# Resume interrupted session
/attune:war-room --resume war-room-20260120-153022
# Escalate from brainstorm
/attune:war-room --from-brainstorm
What This Command Does
- Assesses reversibility (Phase 0) to determine appropriate deliberation intensity
- Routes to correct mode based on Reversibility Score (RS):
- RS ≤ 0.40: Express (1 expert, < 2 min)
- RS 0.41-0.60: Lightweight (3 experts, 5-10 min)
- RS 0.61-0.80: Full Council (7 experts, 15-30 min)
- RS > 0.80: Full Council + Delphi (iterative, 30-60 min)
- Gathers intelligence via Scout and Intelligence Officer
- Develops courses of action from multiple perspectives
- Pressure tests via Red Team adversarial review
- Synthesizes decision via Supreme Commander
- Persists session to Strategeion (Memory Palace)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 420 lines · 26 tokens per session scan A 21f111d3ad6f
war-room is a command published in the GitHub repository athola/claude-night-market (337 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 3,311 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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data-visualization-specialist
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