Borrowing it
Nothing to install: this file belongs to satanyakiv/NutriSport. 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/satanyakiv/NutriSport/main/.claude/skills/feature/SKILL.mdgit clone --depth 1 https://github.com/satanyakiv/NutriSportWrote 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/satanyakiv/nutrisport/feature)<a href="https://agentmods.dev/skills/satanyakiv/nutrisport/feature"><img src="https://agentmods.dev/badge/skills/satanyakiv/nutrisport/feature/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/satanyakiv/nutrisport/feature"><img src="https://agentmods.dev/badge/skills/satanyakiv/nutrisport/feature.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 | $0.00240 | $0.08014 |
| Opus 5 | $0.00120 | $0.04007 |
| Sonnet 5 | $0.00048 | $0.01603 |
| Haiku 4.5 | $0.00024 | $0.00801 |
Grade A, and why
feature 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 9d 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 — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.
feature — long-running feature pipeline
Composes new-feature, figma-handoff, figma-mcp-budget, gen-test, superpowers:using-git-worktrees, /codex:review, and claude-in-mobile (CLI) into a single long-running pipeline. One run = one feature flow (all screens of an auth, cart, profile, …).
Per-screen interleaved cycle. Phase B does NOT batch all Figma calls upfront. Instead, for each screen it runs a tight loop: fetch design context → scaffold the screen → visually compare @Preview against Figma → fix drift → next screen. This naturally spreads Figma MCP calls across implementation time (5-15 min between calls per screen), eliminating Pro-plan rate-limit bursts (10 calls/min, 200 calls/day). After all screens build and install, a final end-to-end visual fidelity check compares emulator screenshots against the cached Figma frames (zero additional Figma MCP calls).
This skill is the executable contract.
Manual invocation only. This skill is launched by the user explicitly — there is no scheduler, no cron, no autorun. "Long-running" means real wall-clock minutes burning real tokens in the foreground; the user controls when to start, when to checkpoint, and when to resume.
When to use
Activate when the user:
- Types
/feature(preferred) or the legacy alias/overnight-feature, or asks to "queue a feature pipeline" - Hands you a feature description + Figma URL and expects a complete branch from a single batched build
- Says "build the auth flow autonomously", "spin up cart end-to-end", "do profile as one pass"
Do NOT use for: single-screen tweaks (use new-feature), pure refactors, or anything that touches a real :network data source (the pipeline runs against FakeXxxDataSource only — see Group B in .claude/features/00-orchestrator.md).
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 293 lines · 0 tokens per session scan A dd96791c2a04
feature is a skill published in the GitHub repository satanyakiv/NutriSport (11 stars, last pushed 3mo ago), licensed MIT. It adds 240 tokens to every session and 8,014 once invoked, about $0.0012 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 2026-08-30.
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