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 agentmods add skills/zigrivers/scaffold/multi-model-dispatchnpx skills add zigrivers/scaffold --skill multi-model-dispatchgit clone --depth 1 https://github.com/zigrivers/scaffoldWhat 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 | $0.00047 | $0.03363 |
| Opus 5 | $0.00023 | $0.01682 |
| Sonnet 5 | $0.00009 | $0.00673 |
| Haiku 4.5 | $0.00005 | $0.00336 |
Grade A, and why
multi-model-dispatch 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 2d 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 — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Model Dispatch
This skill teaches Claude Code how to correctly invoke Codex and Antigravity CLIs for independent review of artifacts. Use this whenever a pipeline step needs multi-model validation at depth 4-5.
When This Skill Activates
- A review or validation step is running at depth 4+ and wants independent model validation
- User asks to "run multi-model review" or "get a second opinion from Codex/Antigravity"
- The
automated-pr-reviewstep is using local CLI review mode - The
implementation-plan-reviewstep dispatches to external CLIs at depth 4+
CLI Detection & Auth Verification
Before attempting any dispatch, detect what's available AND verify authentication. A CLI that's installed but not authenticated is useless in headless mode — it will hang on an interactive auth prompt or fail silently.
Step 1: Check CLI Installation
command -v codex && echo "codex installed" || echo "codex not found"
command -v agy && echo "agy installed" || echo "agy not found"
Step 2: Verify Authentication
CRITICAL: Do not skip this step. Auth tokens expire mid-session. A CLI that worked 30 minutes ago may fail now.
CRITICAL: Previous auth failures do NOT exempt subsequent dispatches. Auth tokens refresh — a CLI that failed auth during user story review may work fine for domain modeling review. Always re-check auth before EACH review step, not once per session.
Codex auth check (has a built-in status command):
codex login status 2>/dev/null && echo "codex authenticated" || echo "codex NOT authenticated"
Antigravity auth check (detect auth-failure sentinel text):
AGY_AUTH_CHECK=$(agy -p "respond with ok" --print-timeout 12s 2>&1)
if echo "$AGY_AUTH_CHECK" | grep -qiE "authentication required|authentication timed out"; then
echo "agy NOT authenticated (auth error)"
else
echo "agy authenticated"
fi
Antigravity's agy -p "hello" recovery command prints a Google OAuth URL when credentials need refreshing.
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.
- 2d ago First seen · 310 lines · 47 tokens per session scan A 054d9bcdc614
multi-model-dispatch is a skill published in the GitHub repository zigrivers/scaffold (5 stars, last pushed 2d ago), licensed MIT. It adds 47 tokens to every session and 3,363 once invoked, about $0.0002 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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