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 KingEmma7/cursor-os --skill implementation-loopgit clone --depth 1 https://github.com/KingEmma7/cursor-osWrote 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/kingemma7/cursor-os/implementation-loop)<a href="https://agentmods.dev/skills/kingemma7/cursor-os/implementation-loop"><img src="https://agentmods.dev/badge/skills/kingemma7/cursor-os/implementation-loop/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/kingemma7/cursor-os/implementation-loop"><img src="https://agentmods.dev/badge/skills/kingemma7/cursor-os/implementation-loop.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 | $0.00033 | $0.00381 |
| Opus 5.5 | $0.00013 | $0.00152 |
| Sonnet 5.5 | $0.00007 | $0.00076 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
implementation-loop 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
Implementation Loop
A repeatable loop for shipping a change that actually works and fits the codebase. Follow the phases in order; don't skip to coding.
1. Understand
- Restate the goal as explicit acceptance criteria. If the request is vague, ask or state your assumption.
- Read the relevant code,
AGENTS.md, anddocs/(architecture, repo-memory, decision-log) before designing. Match existing patterns. - Surface conflicts with the current codebase now, not after building.
2. Plan
- For multi-file or risky work, write a short plan: files to touch, the approach, and the verification you'll run.
- Choose the smallest complete solution. Reuse existing utilities and patterns before adding abstractions or dependencies.
3. Build
- Make surgical changes scoped to the goal. Don't refactor unrelated code in the same pass.
- Keep each modified file traceable to the request. Note unrelated issues separately instead of fixing them inline.
4. Verify
- Run the project's checks: types, lint, tests, and a manual check of the actual behavior. Don't assume — run them.
- Compare the result against
docs/quality-rubric.md. Cover edge cases, error states, and the failure modes the change introduces. - If checks cannot be run, explain exactly why and provide the safest manual verification path.
5. Report
- State what changed and why, how you verified it (commands and results), and any remaining risks or follow-ups.
- Update project memory: record durable facts in
docs/repo-memory.mdand append notable decisions todocs/decision-log.md.
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 · 36 lines · 33 tokens per session scan A 9c80de9657eb
implementation-loop is a skill published in the GitHub repository KingEmma7/cursor-os (2 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 381 once invoked, about $0.0001 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 2026-08-31.
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Build this project's verification skill - a small CLI that drives the running app and captures evidence, plus a feature map of what exists and how to reach it - and the CI check that keeps the map current. Use when asked to 'build a verification skill', 'let the agent drive the app', 'make a feature map', 'the agent…
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review-dependency-updates
Review outdated dependencies, security-scan each candidate bump against OSV.dev, then apply only the safe updates and PR them. Use when asked to 'review dependency updates', 'what can/should be updated', 'are we exposed to ', 'bump dependencies safely'.
trellis-sync
Check this project against the template it was made from, show what changed upstream, and apply only what the user picks. Use when asked to "check for template updates", "sync with trellis", "is my template copy out of date", "pull in upstream template changes", "what changed in the template".
grill-design
Decide a UI design by building several genuinely different working prototypes and comparing them side by side, in rounds, until the choice is locked. Use when asked to "grill the design", "design this screen", "show me options", "prototype some variants", "what should this look like", "I can't decide on a layout".