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/mmrnpx skills add zigrivers/scaffold --skill mmrgit 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 | $0.00081 | $0.02076 |
| Opus 5 | $0.00041 | $0.01038 |
| Sonnet 5 | $0.00016 | $0.00415 |
| Haiku 4.5 | $0.00008 | $0.00208 |
Grade A, and why
mmr 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 3d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mmr — Multi-Model Review
Dispatch code reviews across several AI model CLIs (Claude, Codex, Grok and
Antigravity by default; OpenCode opt-in), reconcile the findings, and gate on
severity. Its peer mmr critique does the same fan-out for a design and is
advisory (no gate).
Run a review
Pick the input mode that matches the target. Pass --sync --format json to get
reconciled findings back in a single call:
# GitHub PR (fetches the diff via `gh pr diff`)
mmr review --pr <number> --focus "what to focus on" --sync --format json
# Staged changes (pre-commit)
mmr review --staged --sync --format json
# All tracked uncommitted changes (excludes untracked files)
git diff HEAD | mmr review --diff - --sync --format json
# Branch / ref range
mmr review --base main --head <branch> --sync --format json
# A specific file's current contents (tracked-no-changes, untracked, or new)
(diff -u /dev/null path/to/file.ts || true) | mmr review --diff - --sync --format json
The --diff flag expects diff-format content (a .patch/.diff path, or -
for stdin). It does not read raw file content — wrap the target in a diff first.
The || true guard is required because diff exits 1 when files differ, which
breaks pipelines under set -o pipefail.
Severity gate
The verdict blocks on findings at or above fix_threshold (default P2; lower
severities are advisory). Override per run with --fix-threshold P0|P1|P2|P3.
Proceed only on pass or degraded-pass; fix blocking findings on blocked.
The verdict also reflects how many channels reported: fewer than
defaults.min_completed_channels (default 2) completing yields
needs-user-decision even with zero findings — one reviewer is not multi-model
review. Treat that as "fix the channels" (mmr doctor), not as a pass.
Async flow (without --sync)
mmr review … prints a job id → mmr status <job-id> until complete →
mmr results <job-id> --format markdown.
Avoid the nested self-review
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.
- 3d ago First seen · 184 lines · 81 tokens per session scan A 46c31afc5779
mmr is a skill published in the GitHub repository zigrivers/scaffold (5 stars, last pushed 3d ago), licensed MIT. It adds 81 tokens to every session and 2,076 once invoked, about $0.0004 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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