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 lemoncrow-lab/lemoncrow --skill benchmarkgit clone --depth 1 https://github.com/lemoncrow-lab/lemoncrowWrote 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/lemoncrow-lab/lemoncrow/benchmark)<a href="https://agentmods.dev/skills/lemoncrow-lab/lemoncrow/benchmark"><img src="https://agentmods.dev/badge/skills/lemoncrow-lab/lemoncrow/benchmark/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/lemoncrow-lab/lemoncrow/benchmark"><img src="https://agentmods.dev/badge/skills/lemoncrow-lab/lemoncrow/benchmark.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 | $0.00005 | $0.03911 |
| Opus 5.5 | $0.00002 | $0.01564 |
| Sonnet 5.5 | $0.00001 | $0.00782 |
| Haiku 4.5 | $0.00001 | $0.00391 |
Grade B, and why
benchmark scanned grade B with 1 finding 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Codex, the model pinned in `~/.codex/config.toml`, else Codex's default, priced from the id its The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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 46c19daac15c
- 1mo ago First seen · 331 lines · 5 tokens per session scan B eec0298a061d
benchmark is a skill published in the GitHub repository lemoncrow-lab/lemoncrow (72 stars, last pushed yesterday), with no licence file. It adds 5 tokens to every session and 3,911 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
brain-page
Operating manual for reading and writing a project's brain — every read and write goes through the bundled zero-dependency brain CLI; never hand-edit brain files. Read it before creating or modifying any page or root page.
brain-setup
Bootstrap the Open Project Brain Standard into the current project — prefer brain init (ensure BRAIN.md, scaffold empty brain brainRoot-aware, default-wire CLAUDE.md + AGENTS.md). Optionally install a pre-commit hook and a Claude Code or Codex SessionStart hook.
brain-bootstrap
Seed a freshly-scaffolded brain with real project knowledge — on an existing (brownfield) project read the code, docs, and git log, then draft only the root pages that have meaningful content and capture key historical decisions; on a near-empty (greenfield) project interview the user. Every write goes through the…
brain-ingest
The process for digesting a conversation, document, or research result, classifying it, and writing it down as brain content (a root-page update or a new/updated page) through the brain CLI.
outcome-run
Run one action in an outcome-loop folder. Use when the user wants to execute the outcome loop, start with Superdense reward maintenance, choose one action on a lever, create runs/ /work.md and learnings.md, or use prior outcomes to improve a real-world metric.
outcome-setup
Set up or repair one outcome-loop folder for improving a real-world outcome. Use when the user wants to define goal.md, run.md, analytics/instrumentation, levers, target repos/accounts, or the folder contract for an outcome loop.