Borrowing it
Nothing to install: this file belongs to marcoemrich/EXACT-Coding-Exercises. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/marcoemrich/EXACT-Coding-Exercises/main/.claude/skills/green/SKILL.mdgit clone --depth 1 https://github.com/marcoemrich/EXACT-Coding-ExercisesWrote 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/marcoemrich/exact-coding-exercises/green)<a href="https://agentmods.dev/skills/marcoemrich/exact-coding-exercises/green"><img src="https://agentmods.dev/badge/skills/marcoemrich/exact-coding-exercises/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/marcoemrich/exact-coding-exercises/green"><img src="https://agentmods.dev/badge/skills/marcoemrich/exact-coding-exercises/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 | $0.00073 | $0.00511 |
| Opus 5.5 | $0.00029 | $0.00204 |
| Sonnet 5.5 | $0.00015 | $0.00102 |
| Haiku 4.5 | $0.00007 | $0.00051 |
Grade A, and why
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 1mo 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
Green — one phase, manually driven
This is a manual phase control, not a separate method. It runs step 3 of the predictive cycle and then stops. Use it when you want to steer Red-Green-Refactor yourself instead of invoking the whole
exact-codingworkflow. The method lives in one place; this skill only selects which part of it to execute now.
What to read
.claude/skills/predictive-tdd/SKILL.md— sections Core rules and 3. Reach Green minimally. Those are binding as written.- The matching profile under
.claude/skills/predictive-tdd/stacks/for the commands to run. .claude/skills/exact-coding-shared/human-in-the-loop.mdfor the prediction-mismatch rule.
What to do
Confirm there is an active behavioral Red to satisfy. If the suite is already
green, say so and stop — there is nothing for this phase to do; offer red or
refactor instead.
Then execute exactly step 3 of the cycle:
- make the smallest production change likely to pass the active test, without anticipating inactive examples — hardcoded values and narrow conditionals are valid intermediate steps,
- predict the focused test's outcome, including expected pass/fail and todo counts where the stack reports them,
- run it and compare prediction with reality.
Where to stop
Stop after the active test is green. Report the change, the prediction, and the
actual result. Do not refactor, and do not start the next behavior — even
though Green has no default checkpoint in .claude/skills/exact-coding-shared/human-in-the-loop.md. The human invoked a single
phase; that invocation is the checkpoint.
On a prediction mismatch, follow Prediction mismatch in the Predictive TDD skill and stop there. Never change production behavior merely to make an unexplained failure disappear.
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.
- 1mo ago First seen · 47 lines · 73 tokens per session scan A a39061b729e6
green is a skill published in the GitHub repository marcoemrich/EXACT-Coding-Exercises (18 stars, last pushed 1mo ago), licensed MIT. It adds 73 tokens to every session and 511 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 2026-09-20.
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