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 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/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/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>- NVIDIA SkillSpector warn
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.
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 | $0.00033 | $0.04915 |
| Opus 5.5 | $0.00013 | $0.01966 |
| Sonnet 5.5 | $0.00007 | $0.00983 |
| Haiku 4.5 | $0.00003 | $0.00492 |
Grade A, and why
effect-patterns-scheduling-periodic-tasks scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 764 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Effect-TS Patterns: Scheduling Periodic Tasks
This skill provides 3 curated Effect-TS patterns for scheduling periodic tasks. Use this skill when working on tasks related to:
- scheduling periodic tasks
- Best practices in Effect-TS applications
- Real-world patterns and solutions
🟡 Intermediate Patterns
Scheduling Pattern 4: Debounce and Throttle Execution
Rule: Use debounce to wait for silence before executing, and throttle to limit execution frequency, both critical for handling rapid events.
Good Example:
This example demonstrates debouncing and throttling for common scenarios.
import { Effect, Schedule, Ref } from "effect";
interface SearchQuery {
readonly query: string;
readonly timestamp: Date;
}
// Simulate API search
const performSearch = (query: string): Effect.Effect<string[]> =>
Effect.gen(function* () {
yield* Effect.log(`[API] Searching for: "${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.
- 1mo 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 (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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