effect-patterns-scheduling-periodic-tasks

effect-patterns-scheduling-periodic-tasks is a skill for Claude Code from PaulJPhilp/EffectPatterns. It costs 33 tokens per session (4,915 once invoked), scanned A, original, MIT.

A set of three Effect-TS examples for running work on a schedule, including delaying repeated actions and controlling how often rapid events trigger a task. Debouncing waits for activity to stop; throttling limits the execution rate.

In plain words
What is it for?
Use it for periodic tasks, delayed retries, search input handling, and other Effect-TS code that needs debouncing, throttling, or scheduled execution.
Why use it?
It helps prevent repeated or overly frequent work, such as sending a request for every keystroke in a search box.

Skill for Claude Code

Written for Claude Code: a Claude Code plugin manifest.

Part of the effect-patterns plugin — 24 skills, 2 commands shipped together

Good fit Use it for periodic tasks, delayed retries, search input handling, and other Effect-TS code that needs debouncing, throttling, or scheduled execution.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pauljphilp/effectpatterns/effect-patterns-scheduling-periodic-tasks
Install

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.

Any agent
npx skills add PaulJPhilp/EffectPatterns --skill effect-patterns-scheduling-periodic-tasks
Clone the repo
git clone --depth 1 https://github.com/PaulJPhilp/EffectPatterns

Made for: Claude Code.

Or install effect-patterns, the plugin that ships this one along with the rest of its 24 skills, 2 commands.

Wrote 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.

agentmods badge for effect-patterns-scheduling-periodic-tasks

README.md
[![agentmods](https://agentmods.dev/badge/skills/pauljphilp/effectpatterns/effect-patterns-scheduling-periodic-tasks/github.svg)](https://agentmods.dev/skills/pauljphilp/effectpatterns/effect-patterns-scheduling-periodic-tasks)
Your own site
<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/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.

agentmods 80×15 button for effect-patterns-scheduling-periodic-tasks

Your own site · 80×15
<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="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,915 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 3 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Rogue Agent · line 196
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
  • medium Data Exfiltration · line 594
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 595
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.04915
Opus 5.5 $0.00013 $0.01966
Sonnet 5.5 $0.00007 $0.00983
Haiku 4.5 $0.00003 $0.00492

Measured 1mo ago against content hash 2a13914b47db, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 1mo 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.

config/.claude-plugin/plugins/effect-patterns/skills/effect-patterns-scheduling-periodic-tasks/SKILL.md · 764 lines

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);

Read the full file on GitHub · 764 lines

Changes

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.

  1. 1mo ago First seen · 764 lines · 33 tokens per session scan A 2a13914b47db

Subscribe to this mod's changes

effect-patterns-scheduling-periodic-tasks is a skill published in the GitHub repository PaulJPhilp/EffectPatterns (807 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 4,915 once invoked, about $0.0001 per session on Opus 5.5. 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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