Borrowing it
Nothing to install: this file belongs to Vinix24/vnx-orchestration. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Vinix24/vnx-orchestration/main/.claude/skills/panel/SKILL.mdgit clone --depth 1 https://github.com/Vinix24/vnx-orchestrationWrote 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/vinix24/vnx-orchestration/panel)<a href="https://agentmods.dev/skills/vinix24/vnx-orchestration/panel"><img src="https://agentmods.dev/badge/skills/vinix24/vnx-orchestration/panel/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/vinix24/vnx-orchestration/panel"><img src="https://agentmods.dev/badge/skills/vinix24/vnx-orchestration/panel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00100 | $0.01435 |
| Opus 5 | $0.00050 | $0.00718 |
| Sonnet 5 | $0.00020 | $0.00287 |
| Haiku 4.5 | $0.00010 | $0.00144 |
Grade A, and why
panel 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 10d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/panel — multi-provider deliberation
For hard questions where you want several strong models to genuinely deliberate, not just answer in parallel. Each stage builds on the last, so the panel converges through disagreement and verification instead of averaging opinions.
When to use
- architecture — a feature/system design where the tradeoffs are non-obvious.
- strategy — a business/product call that rests on assumptions worth stress-testing.
- research — market/competitive questions where claims need refuting.
- sweep — a codebase audit (security / correctness / dead-code / refactor).
Reach for it when a single model's answer would be a guess, and you'd otherwise open five terminals yourself.
How it works (4 stages)
- Diverge — every fleet provider (codex / kimi / claude / glm-5.2 / deepseek-harness) analyses the SAME question through a DIFFERENT mode-specific lens.
- Contrarian — one designated seat red-teams the emerging consensus: what did everyone miss, which "this is fine" is wrong.
- Verify — the top claims are adversarially checked (against the CODE for sweeps — real
file:line; against SOURCES for research — try to refute). - Synthesis — one cited report: consensus + surviving dissent + verified/refuted claims, ranked and deduped.
How seat coverage is counted (OI-1519)
"N of M lenses present" is reconciled against the t0 receipt ledger
(t0_receipts.ndjson), never taken from the exit_code a seat writes about ITSELF in
its own report frontmatter. After each stage completes, every seat's dispatch-id is
looked up in the ledger via receipt_provenance.find_receipts_by_dispatch and lands in
one of THREE outcomes:
- present — the ledger holds a decisive SUCCESS record for the seat's dispatch-id
(
statusin the ADR-035 success setdone/success/complete/completed, orverdict.decision=accept). - failed — the ledger holds a decisive FAILURE record (
statusin the ADR-035 hard-failure setfailed/failure/error/blocked/timeout/contract_invalid, orverdict.decision=reject; multiple receipts for one dispatch-id reconcile failure-beats-success — a success record never launders a recorded failure). A dispatcher that RAISED before the seat completed is failed on direct local evidence. - unmeasured — the ledger has NO decisive record for the dispatch-id (no receipt
at all, or only indecisive ones). This is a third BRANCH, not a third value: the
seat counts as NEITHER present NOR failed and is named in the report
(
**Unmeasured seats:**,[SEAT UNMEASURED — no decisive ledger record]). Reading "unmeasured" as "probably fine" repeats exactly the bug OI-1519 repaired — a measurement gap is not a lens.
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.
- 10d ago First seen · 97 lines · 100 tokens per session scan A 7a34e00df1ea
panel is a skill published in the GitHub repository Vinix24/vnx-orchestration (61 stars, last pushed yesterday), licensed MIT. It adds 100 tokens to every session and 1,435 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
agent-teams
Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
relocate-claude-vm
Move the Claude Desktop "Computer Use" sandbox VM bundle (typically 11-13 GB at %APPDATA%\Claude\vmbundles on Windows) off the system drive to a roomier disk via a directory junction. Transparent to Claude Desktop, reversible. Use when the system drive is low on space and a disk scan shows vmbundles as a top consumer.…
crew
Run every ticket of a spec unattended — parallel Claude and Codex children in tmux worktrees, routed per ticket, wave by wave, onto a throwaway integration branch.
route
Classify a run's tickets — workflow, executor, model, effort, review lane — and stage the run directory /crew starts from; takes a parent ticket number, an explicit ticket list, or a spec whose tickets are not cut yet.
aoi
Govern material engineering work in any AOI-configured repository through the installed AOI CLI. Use when AOI hooks report an active project, before edits or external actions, and when planning, claiming, delegating, verifying, checkpointing, delivering, or closing AOI tasks.
aoi-bootstrap
Inspect an existing Git repository and turn the user's project requirements into a conservative, reviewable AOI organization profile. Use when the user asks to initialize AOI, create or review aoi.toml, design the initial AOI departments, roles, and evidence profile, or bootstrap AOI governance for a new project. Do…