War Room Skill

A war room runs personas through a structured two-phase session:

1. 1. Phase 1 — Ideation (5 rounds max): personas debate the research idea question by question.

Ends early on consensus (all [AGREE] or [PASS], no [OBJECT]) or two consecutive all-[PASS] rounds. Output: INLINECODE4

1. 2. Phase 2 — Proposal (5 rounds max): personas collaboratively draft each proposal section.

Output: memory/war-room/proposal-draft.md

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Configurations

Defined in skills/war-room/personas/agents.json under the configurations key.

Name	Participants	Use when
INLINECODE8	Creative, Senior Prof, Young Faculty, Industry Liaison	Deep ideation, novel directions, full proposal needed
INLINECODE9

Senior Professor, Young Faculty | Quick feasibility check, tight scope |

The configuration is specified in PROJECT.md frontmatter under war_room.configuration. Default: full.

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Consensus Protocol

Every persona response must end with one of:

Tag	Meaning
INLINECODE13	I accept the current position
INLINECODE14

No strong view either way |
| [OBJECT: reason] | I reject — give specific reason |

Do not embed tags mid-response. They must be the final line.

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Single-Agent Fallback (Codex / no subagent spawning)

If you cannot spawn subagents, run the same loop inline. For each persona turn:

1. 1. Print a clear header: INLINECODE16
2. Adopt that persona fully for your response — voice, stance, debate style, red lines.
3. End with the consensus tag ([AGREE], [PASS], or [OBJECT: reason]).
4. Return to moderator role between turns to write the log entry and check consensus.

Drift detection still applies: before each turn, re-read the persona definition and note whether your previous response for that persona drifted from their stance.

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Playbook

Follow this sequence exactly. You are the moderator/orchestrator throughout.

Setup

1. 0. Spawn the monitor in a new terminal window so the user can watch the session live:

- macOS:

     osascript -e 'tell application "Terminal" to do script "cd '"'"'<repo_root>'"'"' && python skills/war-room/monitor.py --project <project_path>"'
     

- Linux (with display):

     xterm -title "War Room Monitor" -e "python skills/war-room/monitor.py --project <project_path>" &
     

- If the spawn fails, continue silently — the monitor is optional.

Replace <repo_root> with the absolute path to this repo and <project_path> with the active project folder path. The monitor requires rich (pip install rich).

1. 1. Read skills/war-room/personas/agents.json. Load the selected configuration's participant list and synthesiser index.
2. For each participant, read their persona file (e.g. skills/war-room/personas/senior-professor.md).
3. Read skills/persistent-persona/SKILL.md and skills/memory-checkpoint/SKILL.md — you will apply these every turn.
4. Check if memory/war-room/discussion-log.md exists.

- If yes: load it — you are resuming a session. Read memory/SUMMARY.md for current phase and round. - If no: create memory/war-room/discussion-log.md with a header block (project name, configuration, timestamp).

1. 6. Ensure memory/.private/ folder exists for persona memos.

Phase 1 — Ideation

For each round (up to 5):

For each participant in configuration order:

a. Prepare persona context
- Read memory/.private/agent-<index>-memo.md if it exists.
- Check the most recent Drift flag. If yes, prepend a PERSONA RESET block to the subagent SI:
CODEBLOCK2

b. Call Agent subagent with this SI (in order):
- first-principles content
- Persona definition (full persona file content)
- persistent-persona skill instructions
- (if drift) PERSONA RESET block
- The discussion log so far

User message: INLINECODE37

c. Append to log
- Append the response to memory/war-room/discussion-log.md in this format:
CODEBLOCK3

d. Write persona memo
- Append to memory/.private/agent-<index>-memo.md:
CODEBLOCK4

After all participants have spoken in a round:

e. Check consensus
- If all responses end with [AGREE] or [PASS] and no [OBJECT]: Phase 1 ends early.
- If two consecutive rounds were all [PASS]: Phase 1 ends early.

f. Checkpoint
- Write memory/checkpoints/<timestamp>/agent-0.md (your moderator state: current round, phase, next action).
- Update memory/SUMMARY.md.

g. Synthesiser snapshot (after round 3 or on early exit)
- Call a subagent with the synthesiser persona + discussion log.
- Task: "Summarise the agreed research idea so far in 3-5 bullet points."
- Write output to memory/war-room/idea-snapshot.md.

Phase 2 — Proposal

Read skills/research-proposal/SKILL.md now. The proposal has 6 sections.

Assign one section per round (or pair related sections). Run the same per-turn loop as Phase 1, but each subagent's task is:

INLINECODE48

After each round, the synthesiser appends the agreed section draft to memory/war-room/proposal-draft.md.

Finalization

1. 1. Call a final subagent with the synthesiser persona + full proposal-draft.md.

Task: "Produce the final clean research proposal. Follow the research-proposal skill format exactly. 2 pages max."

1. 2. Write output to memory/war-room/proposal-draft.md (overwrite with final version).
2. Copy discussion-log.md, idea-snapshot.md, and proposal-draft.md to <sandbox_root>/results/.
3. Write final checkpoint and update memory/SUMMARY.md with status: complete.

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Outputs

CODEBLOCK5

The monitor (skills/war-room/monitor.py) reads memory/war-room/discussion-log.md, memory/SUMMARY.md, memory/war-room/idea-snapshot.md, and memory/.private/ in real time.