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 arunveersingh/ai --skill day-08-self-graded-greengit clone --depth 1 https://github.com/arunveersingh/aiWrote 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/arunveersingh/ai/day-08-self-graded-green)<a href="https://agentmods.dev/skills/arunveersingh/ai/day-08-self-graded-green"><img src="https://agentmods.dev/badge/skills/arunveersingh/ai/day-08-self-graded-green/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/arunveersingh/ai/day-08-self-graded-green"><img src="https://agentmods.dev/badge/skills/arunveersingh/ai/day-08-self-graded-green.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 | $0.00000 | $0.00533 |
| Opus 5.5 | $0.00000 | $0.00213 |
| Sonnet 5.5 | $0.00000 | $0.00107 |
| Haiku 4.5 | $0.00000 | $0.00053 |
Grade A, and why
self-graded-green 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 15d 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.
What it actually says
Self-graded green
The requirement: "Refunds must not exceed the amount paid." The agent reads "each refund," writes the check and a test (20000 on 10000: rejected), and everything passes. You meant the total. Two refunds of 6000 on a 10000 payment both go through.
Self-graded is not passed. Green means the agent agrees with itself. The fix: see its reading as examples before it builds, and approve that first.
Part A — Ask (paste and adapt)
Before writing any code:
1. For each requirement, give 2-4 concrete examples:
input -> expected result. Include repeats, totals,
boundaries, and retries where they apply.
2. If a requirement reads two ways, write TWO READINGS:
<requirement>, show an example of each, and don't pick.
3. Stop and wait for my approval.
After I approve: build to those examples, turn them into
tests, and don't change them. If one looks wrong, ask.
In an orchestrated flow (spec → plan → tasks → implement): run this as one step right after the spec. On a big requirement, run it per slice, just before that slice's tasks.
Part B — Read the examples (you do this)
- Write your own first for one line you care about, then compare. A mismatch is a misreading caught for free.
- Look for the split. For each requirement ask: would the other reading give the same result here? If yes for every example, add one where it wouldn't (two refunds, not one).
- Answer every TWO READINGS in the spec itself, so the next reader doesn't have to pick.
- Hold the line. Later tasks build to the approved examples. If the agent wants to change one, that's a spec question for you, not an edit.
Done when: every requirement has examples you read, at least one per line where the readings would differ, and no open TWO READINGS.
Lesson: Day 8 — Self-Graded Green
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.
- 15d ago First seen · 38 lines · 0 tokens per session scan A 30ac1c965155
self-graded-green is a skill published in the GitHub repository arunveersingh/ai (3 stars, last pushed 3d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 533 tokens. 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 2026-10-11.
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