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/pauljphilp/effectpatterns/effect-patterns-scheduling-periodic-tasksnpx skills add PaulJPhilp/EffectPatterns --skill effect-patterns-scheduling-periodic-tasksgit clone --depth 1 https://github.com/PaulJPhilp/EffectPatternsWrote 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/pauljphilp/effectpatterns/effect-patterns-scheduling-periodic-tasks)<a href="https://agentmods.dev/skills/pauljphilp/effectpatterns/effect-patterns-scheduling-periodic-tasks"><img src="https://agentmods.dev/badge/skills/pauljphilp/effectpatterns/effect-patterns-scheduling-periodic-tasks.svg" alt="Measured on agentmods" 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 | $0.00033 | $0.04915 |
| Opus 5 | $0.00016 | $0.02457 |
| Sonnet 5 | $0.00007 | $0.00983 |
| Haiku 4.5 | $0.00003 | $0.00492 |
Grade A, and why
effect-patterns-scheduling-periodic-tasks scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 764 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Effect-TS Patterns: Scheduling Periodic Tasks
This skill provides 3 curated Effect-TS patterns for scheduling periodic tasks. Use this skill when working on tasks related to:
- scheduling periodic tasks
- Best practices in Effect-TS applications
- Real-world patterns and solutions
🟡 Intermediate Patterns
Scheduling Pattern 4: Debounce and Throttle Execution
Rule: Use debounce to wait for silence before executing, and throttle to limit execution frequency, both critical for handling rapid events.
Good Example:
This example demonstrates debouncing and throttling for common scenarios.
import { Effect, Schedule, Ref } from "effect";
interface SearchQuery {
readonly query: string;
readonly timestamp: Date;
}
// Simulate API search
const performSearch = (query: string): Effect.Effect<string[]> =>
Effect.gen(function* () {
yield* Effect.log(`[API] Searching for: "${query}"`);
yield* Effect.sleep("100 millis"); // Simulate API delay
return [
`Result 1 for ${query}`,
`Result 2 for ${query}`,
`Result 3 for ${query}`,
];
});
// Main: demonstrate debounce and throttle
const program = Effect.gen(function* () {
console.log(`\n[DEBOUNCE/THROTTLE] Handling rapid events\n`);
// Example 1: Debounce search input
console.log(`[1] Debounced search (wait for silence):\n`);
const searchQueries = ["h", "he", "hel", "hell", "hello"];
const debouncedSearches = yield* Ref.make<Effect.Effect<string[]>[]>([]);
for (const query of searchQueries) {
yield* Effect.log(`[INPUT] User typed: "${query}"`);
// In real app, this would be debounced
yield* Effect.sleep("150 millis"); // User typing
}
// After user stops, execute search
yield* Effect.log(`[DEBOUNCE] User silent for 200ms, executing search`);
const searchResults = yield* performSearch("hello");
yield* Effect.log(`[RESULTS] ${searchResults.length} results found\n`);
// Example 2: Throttle scroll events
console.log(`[2] Throttled scroll handler (max 10/sec):\n`);
const scrollEventCount = yield* Ref.make(0);
const updateCount = yield* Ref.make(0);
// Simulate 100 rapid scroll events
for (let i = 0; i < 100; i++) {
yield* Ref.update(scrollEventCount, (c) => c + 1);
// In real app, scroll handler would be throttled
if (i % 10 === 0) {
// Simulate throttled update (max 10 per second)
yield* Ref.update(updateCount, (c) => c + 1);
}
}
const events = yield* Ref.get(scrollEventCount);
const updates = yield* Ref.get(updateCount);
yield* Effect.log(
`[THROTTLE] ${events} scroll events → ${updates} updates (${(updates / events * 100).toFixed(1)}% update rate)\n`
);
// Example 3: Deduplication
console.log(`[3] Deduplicating rapid events:\n`);
const userClicks = ["click", "click", "click", "dblclick", "click"];
const lastClick = yield* Ref.make<string | null>(null);
const clickCount = yield* Ref.make(0);
for (const click of userClicks) {
const prev = yield* Ref.get(lastClick);
if (click !== prev) {
yield* Effect.log(`[CLICK] Processing: ${click}`);
yield* Ref.update(clickCount, (c) => c + 1);
yield* Ref.set(lastClick, click);
} else {
yield* Effect.log(`[CLICK] Duplicate: ${click} (skipped)`);
}
}
const processed = yield* Ref.get(clickCount);
yield* Effect.log(
`\n[DEDUPE] ${userClicks.length} clicks → ${processed} processed\n`
);
// Example 4: Exponential backoff on repeated errors
console.log(`[4] Throttled retry on errors:\n`);
let retryCount = 0;
const operation = Effect.gen(function* () {
retryCount++;
if (retryCount < 3) {
yield* Effect.fail(new Error("Still failing"));
}
yield* Effect.log(`[SUCCESS] Succeeded on attempt ${retryCount}`);
return "done";
}).pipe(
Effect.retry(
Schedule.exponential("100 millis").pipe(
Schedule.upTo("1 second"),
Schedule.recurs(5)
)
)
);
yield* operation;
});
Effect.runPromise(program);
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.
- 5d ago First seen · 764 lines · 33 tokens per session scan A 2a13914b47db
effect-patterns-scheduling-periodic-tasks is a skill published in the GitHub repository PaulJPhilp/EffectPatterns (796 stars, last pushed 2mo ago), licensed MIT. It adds 33 tokens to every session and 4,915 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 2026-08-30.
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