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 mickeyyaya/refactoring-skills --skill feature-flags-progressive-deliverygit clone --depth 1 https://github.com/mickeyyaya/refactoring-skillsWrote 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/mickeyyaya/refactoring-skills/feature-flags-progressive-delivery)<a href="https://agentmods.dev/skills/mickeyyaya/refactoring-skills/feature-flags-progressive-delivery"><img src="https://agentmods.dev/badge/skills/mickeyyaya/refactoring-skills/feature-flags-progressive-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/mickeyyaya/refactoring-skills/feature-flags-progressive-delivery"><img src="https://agentmods.dev/badge/skills/mickeyyaya/refactoring-skills/feature-flags-progressive-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 | $0.00071 | $0.04567 |
| Opus 5 | $0.00036 | $0.02284 |
| Sonnet 5 | $0.00014 | $0.00913 |
| Haiku 4.5 | $0.00007 | $0.00457 |
Grade A, and why
feature-flags-progressive-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 11d 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 — 506 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Flags and Progressive Delivery
Overview
Feature flags (also called feature toggles or feature switches) decouple deployment from release, letting teams ship code dark and turn it on for targeted users without a new deployment. Combined with progressive delivery strategies like canary releases, blue-green deployments, and ring deployments, they form the backbone of modern continuous delivery.
When to use: Designing a feature rollout pipeline; reviewing flag evaluation logic; auditing rollback/kill-switch implementations; designing A/B testing or experimentation infrastructure; reviewing flag hygiene and lifecycle management.
Quick Reference
| Pattern | Core Idea | Primary Red Flag |
|---|---|---|
| Feature Flag / Toggle | Gate code paths behind runtime-evaluated conditions | Hardcoded flags, no remote config, boolean trap |
| Progressive Delivery | Gradually shift traffic to new code paths | Big-bang releases, no health gate between rollout stages |
| Canary Release | Route a small percentage of traffic to new version | No automatic rollback on error spike |
| Blue-Green Deployment | Two identical environments; switch routing instantly | Shared databases making switchover unsafe |
| Ring Deployment | Concentric user rings (internal → beta → GA) | Rings with no dwell time or health checks |
| Percentage Rollout | Gradual rollout by user percentage | Non-sticky allocation; user sees flag flip each request |
| Kill Switch | Instant off switch for a feature in production | Kill switch itself is flag-gated or takes >1 second |
| Flag Lifecycle | Create → active → cleanup → delete | Stale flags accumulating in codebase, flag debt |
| A/B Testing | Randomized controlled experiment with metrics | Peeking at results early, multiple comparisons, survivorship bias |
| Targeting Rules | Evaluate flag per user context (segment, attribute) | Overly complex rule trees, unbounded rule chains |
Patterns in Detail
1. Feature Flags / Feature Toggles / Feature Switches
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.
- 11d ago First seen · 506 lines · 71 tokens per session scan A 91e3e98ba635
feature-flags-progressive-delivery is a skill published in the GitHub repository mickeyyaya/refactoring-skills (6 stars, last pushed 5mo ago), licensed MIT. It adds 71 tokens to every session and 4,567 once invoked, about $0.0004 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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