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/ralfyishere/rules-with-receipts/leverage-firstnpx skills add ralfyishere/rules-with-receipts --skill leverage-firstgit clone --depth 1 https://github.com/ralfyishere/rules-with-receiptsWrote 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/ralfyishere/rules-with-receipts/leverage-first)<a href="https://agentmods.dev/skills/ralfyishere/rules-with-receipts/leverage-first"><img src="https://agentmods.dev/badge/skills/ralfyishere/rules-with-receipts/leverage-first.svg" alt="Measured on agentmods" 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 | $0.00132 | $0.01631 |
| Opus 5 | $0.00066 | $0.00816 |
| Sonnet 5 | $0.00026 | $0.00326 |
| Haiku 4.5 | $0.00013 | $0.00163 |
Grade A, and why
Leverage First 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Leverage First
Purpose
The reliable failure isn't picking a wrong idea — it's executing the first workable method on a single track when a dramatically better one was one cheap question away. Hand-rolling a tool that already exists; collecting data live for hours that history already holds; running five separate passes that could be one; testing your pet hypothesis when the same data answers ten questions. Each is effort spent where leverage was available. This skill inserts one cheap step before the grind: find the higher-leverage path first. It is the "work smarter, not just harder" reflex, made explicit and non-optional.
When to use this skill
- You're about to build a tool, harness, or script — before writing it.
- You're about to collect/gather data the slow way (live polling, scraping, manual).
- You're about to run a heavy process or a long single-track computation.
- "How should we do this?", "is there a faster/better way?", "what else could we try?"
- You notice yourself reaching for the obvious grind, or a task that "will take hours".
When NOT to use
- The leverage pass is itself more expensive than just doing the small task (a one-off, five-minute job — don't spend ten minutes looking for a shortcut to a five-minute task).
- You already did the pass this session for this problem and nothing changed.
- A true emergency where any working path now beats a better path later.
The procedure (one cheap pass, four questions)
Before committing effort, spend a few minutes on:
- Don't reinvent — does it already exist? Has someone solved this? Is there a dataset, API, library, tool, or community knowledge that hands you 80% of it? Search/ask before you build. (A free historical dataset existed instead of hours of live collection; the answer was a documented endpoint away.)
- 10× not 10% — is there a fundamentally more efficient method? Not a faster version of the same grind — a different shape: historical vs live, batch vs loop, existing index vs fresh scrape, closed-form vs simulation. If the best case is "same approach but quicker", keep looking for the shape change.
- Compose, don't isolate — can the steps share a resource and combine? If you're about to run N separate passes over the same data/timeframe, make it one pass that computes all N — it's cheaper AND reveals interactions (overlap, complementarity) siloed runs hide.
- Enumerate the question space — is the pet hypothesis the best use? A new capability (dataset, tool, access) usually answers many questions. List them, rank by value, and don't tunnel on the first one that occurred to you.
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 First seen · 110 lines · 0 tokens per session scan A bc348352a8a6
Leverage First is a skill published in the GitHub repository ralfyishere/rules-with-receipts (2 stars, last pushed 1mo ago), licensed MIT. It adds 132 tokens to every session and 1,631 once invoked, about $0.0007 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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