Borrowing it
Nothing to install: this file belongs to florian101010/awesome-agentic-AI-coding-template. 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/florian101010/awesome-agentic-AI-coding-template/main/.agent/skills/feature-delivery/SKILL.mdgit clone --depth 1 https://github.com/florian101010/awesome-agentic-AI-coding-templateWrote 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/florian101010/awesome-agentic-ai-coding-template/feature-delivery)<a href="https://agentmods.dev/skills/florian101010/awesome-agentic-ai-coding-template/feature-delivery"><img src="https://agentmods.dev/badge/skills/florian101010/awesome-agentic-ai-coding-template/feature-delivery/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/florian101010/awesome-agentic-ai-coding-template/feature-delivery"><img src="https://agentmods.dev/badge/skills/florian101010/awesome-agentic-ai-coding-template/feature-delivery.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 | $0.00030 | $0.00136 |
| Opus 5 | $0.00015 | $0.00068 |
| Sonnet 5 | $0.00006 | $0.00027 |
| Haiku 4.5 | $0.00003 | $0.00014 |
Grade A, and why
feature-delivery 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 10d 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
Feature Delivery
Follow .agent/workflows/feature-delivery.md strictly.
Execution requirements:
- Produce a concise feature brief (goals, non-goals, affected files, risks, acceptance criteria).
- Implement in minimal, reviewable increments.
- Run targeted validation for touched flows.
- Update affected docs and
CHANGELOG.md. - Run pre-commit checks before final handoff.
- End with a DoD checklist status.
Never skip documentation sync.
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.
- 10d ago First seen · 20 lines · 30 tokens per session scan A 50b27864c192
feature-delivery is a skill published in the GitHub repository florian101010/awesome-agentic-AI-coding-template (4 stars, last pushed 6mo ago), licensed MIT. It adds 30 tokens to every session and 136 once invoked, about $0.0002 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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