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 agentmods add skills/kid-sid/codex-spellbook/feature-flagsnpx skills add kid-sid/codex-spellbook --skill feature-flagsgit clone --depth 1 https://github.com/kid-sid/codex-spellbookWhat 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 | $0.00059 | $0.05413 |
| Opus 5 | $0.00030 | $0.02707 |
| Sonnet 5 | $0.00012 | $0.01083 |
| Haiku 4.5 | $0.00006 | $0.00541 |
Grade A, and why
feature-flags scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sX POST https://unleash.example.com/api/admin/features \ How it starts
The opening of the file, as written. The whole thing — 646 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Flags & A/B Testing
Tactical patterns for flag evaluation, progressive rollouts, controlled experiments, and flag lifecycle — the code-level companion to infrastructure-level canary deployments.
When to Activate
- Adding feature flag support to a new or existing service
- Designing a percentage-based or ring-based rollout
- Setting up A/B experiments or multivariate tests
- Choosing between LaunchDarkly, Unleash, and OpenFeature
- Implementing sticky bucketing or mutual exclusion across experiments
- Writing unit or integration tests for flag-gated code paths
- Auditing, cleaning up, or governing stale flags
Flag Types & Evaluation Context
Four flag types cover all use cases:
| Type | SDK method | Use for |
|---|---|---|
boolean |
getBooleanValue |
On/off gates, kill switches |
string |
getStringValue |
Variant selection (A/B/C), layout names |
number |
getNumberValue |
Numeric config: timeout, batch size, rate limit |
object |
getObjectValue |
Complex config blob, multi-key experiment payload |
Evaluation Context
The context is the set of attributes the flag platform uses to apply targeting rules. Always include a stable user identifier.
// TypeScript — OpenFeature
import { OpenFeature, type EvaluationContext } from "@openfeature/server-sdk";
const ctx: EvaluationContext = {
targetingKey: user.id, // required: stable, not session-scoped
email: user.email,
orgId: user.orgId,
plan: user.plan, // "free" | "pro" | "enterprise"
country: request.geo.country,
appVersion: "2.4.1",
betaTester: user.betaTester, // custom boolean attribute
};
const client = OpenFeature.getClient("payments");
const enabled = await client.getBooleanValue("new-checkout", false, ctx);
const variant = await client.getStringValue("checkout-layout", "control", ctx);
const timeout = await client.getNumberValue("api-timeout-ms", 5000, ctx);
const config = await client.getObjectValue("rate-limit-config", { rpm: 100 }, ctx);
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.
- 2d ago First seen · 646 lines · 59 tokens per session scan A 706b03ca091d
feature-flags is a skill published in the GitHub repository kid-sid/codex-spellbook (21 stars, last pushed 3mo ago), licensed MIT. It adds 59 tokens to every session and 5,413 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…