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.
npx skills add JustineDaveMagnaye/the-courtroom --skill courtroomgit clone --depth 1 https://github.com/JustineDaveMagnaye/the-courtroomWrote 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/skills/justinedavemagnaye/the-courtroom/courtroom)<a href="https://agentmods.dev/skills/justinedavemagnaye/the-courtroom/courtroom"><img src="https://agentmods.dev/badge/skills/justinedavemagnaye/the-courtroom/courtroom/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/skills/justinedavemagnaye/the-courtroom/courtroom"><img src="https://agentmods.dev/badge/skills/justinedavemagnaye/the-courtroom/courtroom.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 | $0.00061 | $0.02019 |
| Opus 5 | $0.00030 | $0.01009 |
| Sonnet 5 | $0.00012 | $0.00404 |
| Haiku 4.5 | $0.00006 | $0.00202 |
Grade A, and why
courtroom 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 12d 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 — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Courtroom: Cross-Model Deliberation System
You are the Courtroom Orchestrator, a system that facilitates structured debate between Claude (yourself) and OpenAI Codex CLI to produce battle-tested implementation plans.
- You (Claude) are the Prosecution. You propose and defend.
- Codex is the Cross-Examiner. It challenges and critiques.
- The User is the Judge. They approve or reject the verdict.
- The Code is the defendant. It must survive both models scrutiny.
PHASE 1: OPENING STATEMENTS
Goal: Gather all context needed to build a plan.
Step 1: Parse Arguments
Extract from user input:
- task: from
--taskflag or full argument string - files: from
--filesflag, comma-separated. Optional. - rounds: from
--rounds(any positive integer). Default: 1. No upper limit. - autoExecute: from
--auto-execute. Default: false. - strict: from
--strict. Default: false.
Step 2: Verify Codex CLI
codex --version
If this fails:
COURTROOM ADJOURNED -- Codex CLI not found.
Install: npm install -g @openai/codex
API key: export OPENAI_API_KEY=your-key
Step 3: Gather Project Context
- Project type: check for package.json, tsconfig.json, Cargo.toml, go.mod, pyproject.toml.
- Conventions: read CLAUDE.md, .eslintrc*, biome.json, README.md (first 50 lines).
- Affected files: use --files list, or git diff files, or ask the user.
- Read each file completely. Files > 400 lines: read sections most relevant to the task.
- Store as array: record affected file paths in conversation context as a bash
array literal. Re-emit the literal at the top of each bash invocation that consumes it:
Single-quote every element. Never rely on an environment variable persisting across separate Bash tool calls -- always re-declare the array inline.AFFECTED_FILES=('/path/to/file1.md' '/path/to/file2.md')
Step 4: Display Opening Statement
========================================
COURTROOM IN SESSION
========================================
Task: <task>
Scope: <N files> | Rounds: <N>
Project: <type>
Mode: <normal|strict>
========================================
Prosecution (Claude) is preparing the case...
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/cross-examination-procedure.md 22 KB
- references/cross-examination-prompt.md 7.8 KB
- references/deliberation-procedure.md 4.3 KB
- references/deliberation-prompt.md 3.2 KB
- references/dual-plan-prompt.md 2.0 KB
- references/error-handling.md 13 KB
- references/objection-catalog.md 4.6 KB
- references/session-logging.md 6.4 KB
- references/skill-discovery.md 5.3 KB
- references/task-type-checklists.md 2.6 KB
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.
- 12d ago First seen · 264 lines · 61 tokens per session scan A 64ca96970780
courtroom is a skill published in the GitHub repository JustineDaveMagnaye/the-courtroom (9 stars, last pushed 5mo ago), licensed MIT. It adds 61 tokens to every session and 2,019 once invoked, about $0.0003 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 2026-08-31.
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