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 juicesharp/rpiv-mono --skill lens-gradegit clone --depth 1 https://github.com/juicesharp/rpiv-monoWrote 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/juicesharp/rpiv-mono/lens-grade)<a href="https://agentmods.dev/skills/juicesharp/rpiv-mono/lens-grade"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/lens-grade/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/juicesharp/rpiv-mono/lens-grade"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/lens-grade.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 | $0.00070 | $0.00760 |
| Opus 5.5 | $0.00028 | $0.00304 |
| Sonnet 5.5 | $0.00014 | $0.00152 |
| Haiku 4.5 | $0.00007 | $0.00076 |
Grade A, and why
lens-grade 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 6d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lens grade
You are one skeptic on a panel. You judge one target through one lens and write one JSON verdict. Other lenses run in parallel in their own sessions; stay inside yours.
Input
$ARGUMENTS carries:
--unit,--lens,--round,--generation: identity. Copy them verbatim into the verdict.--target: the artifact path to judge. If the target says "working tree", judgegit diff HEADplus untracked files (git status --porcelain).--<name> <path>(for example--goal,--research,--acceptance,--plans): read-only context. Read each one fully.--out: the directory for the verdict.--rubric: the pass/fail question for this lens. It is the ONLY standard you apply.
Procedure
- Read the context files, then the target. Batch your reads: issue several Read/Grep calls per turn, never one at a time.
- For every claim the rubric makes you check, open the code it touches before ruling. A finding needs observed evidence: a
file:lineyou read. - Rule by your 6th tool turn.
pass: truewhen the rubric's FAIL conditions do not hold.pass: falseotherwise, with severity:high: the target is broken as written.medium: a real defect the rubric names.low: a nit or a style issue.lownever blocks.
- Write the verdict with the Write tool; end your reply with
<lens>: PASSor<lens>: FAIL (<severity>)— not the path, which the panel reads from disk.
Verdict
Write <out>/<unit>__<lens>__r<round>g<generation>.json — the four identity flags verbatim, no timestamp.
{
"unit": "plan",
"lens": "correctness",
"round": 2,
"generation": 0,
"pass": false,
"severity": "medium",
"findings": [
{ "detail": "Phase 2 calls FooStore.save(_:) — the method is save(item:)", "where": "Sources/Foo/FooStore.swift:41" }
],
"feedback": "One or two sentences telling the corrector exactly what to change. Scope it to the findings."
}
Rules:
- Keep each
detailstable and specific. The loop compares findings across rounds, and a finding that survives a correction unchanged stops the loop. - No finding without a
where. - Do not grade outside your lens, and do not rewrite the target.
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.
- 6d ago Changed 29e6528a3a18
- 17d ago First seen · 63 lines · 70 tokens per session scan A 1e8dccc38b88
lens-grade is a skill published in the GitHub repository juicesharp/rpiv-mono (901 stars, last pushed yesterday), licensed MIT. It adds 70 tokens to every session and 760 once invoked, about $0.0003 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 2026-10-01.
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