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 chhoumann/t3-pstack --skill arenagit clone --depth 1 https://github.com/chhoumann/t3-pstackWrote 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/chhoumann/t3-pstack/arena)<a href="https://agentmods.dev/skills/chhoumann/t3-pstack/arena"><img src="https://agentmods.dev/badge/skills/chhoumann/t3-pstack/arena/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/chhoumann/t3-pstack/arena"><img src="https://agentmods.dev/badge/skills/chhoumann/t3-pstack/arena.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 | $0.00058 | $0.01419 |
| Opus 5.5 | $0.00023 | $0.00568 |
| Sonnet 5.5 | $0.00012 | $0.00284 |
| Haiku 4.5 | $0.00006 | $0.00142 |
Grade A, and why
arena 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 yesterday.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- chimera — 86% identical, 65 lines differ
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arena
Open a todolist with one entry per phase (Frame, Fan out, Cross-judge, Pick, Graft, Verify) before launching anything.
Phase A: Frame
Every candidate gets the same prompt, so the prompt is the contract.
- State the artifact each candidate is producing.
- Derive the rubric, 3-6 concrete gradeable criteria for what success looks like on this task. It is the picker's tool in Phase D. Candidates only see the task.
- Pick the runners. Use the
arena runnersline in the model sheet. If the sheet or that line is missing, run one each on the defaults in Models. Anautoorinherit-parententry in this line or the cross-judge line means the parent model, so omittargetfor it. Ifdelegate_taskrejects a configured entry, run that seat on another target of the same family fromorchestrator_capabilitiesand say so. A model's family is the first segment of its ID's last/part, such asclaude,gpt, orgrok, whatever provider instance serves it. With no family match, use the firstarena runnersdefault in Models. If it rejects a default, use another target of the same family fromorchestrator_capabilities. Spawn more runners when the arena covers multiple design directions. Use the same model N times when the work is generation-bound rather than judgment-sensitive. Pick each subagent's reasoning level and fast or standard speed for the job, per the Subagents section of the poteto-mode skill. - Give each candidate its own output location (a git worktree where possible, otherwise
/tmp/arena-<slug>/candidate-<n>/), per the separate-before-serializing-shared-state principle skill.
Phase B: Fan out
Spawn all N subagents in one message with mode: "async", each with the task, the path to the shared grounding, its own output path, and instructions to produce the artifact and a short rationale naming the alternatives it considered and what it rejected.
If a candidate produces no output, proceed with N-1 and note the dropout.
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.
- yesterday Changed · -7 lines 5d4a35f8e673
- 3d ago First seen · 63 lines · 58 tokens per session scan A efa3d2e28afe
arena is a skill published in the GitHub repository chhoumann/t3-pstack (190 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 1,419 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-13.
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