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-observabilitygit 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-observability)<a href="https://agentmods.dev/skills/pauljphilp/effectpatterns/effect-patterns-observability"><img src="https://agentmods.dev/badge/skills/pauljphilp/effectpatterns/effect-patterns-observability/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-observability"><img src="https://agentmods.dev/badge/skills/pauljphilp/effectpatterns/effect-patterns-observability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 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 Data Exfiltration · line 569 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 573 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 | $0.00027 | $0.10482 |
| Opus 5.5 | $0.00011 | $0.04193 |
| Sonnet 5.5 | $0.00005 | $0.02096 |
| Haiku 4.5 | $0.00003 | $0.01048 |
Grade A, and why
effect-patterns-observability 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 — 1,587 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Effect-TS Patterns: Observability
This skill provides 13 curated Effect-TS patterns for observability. Use this skill when working on tasks related to:
- observability
- Best practices in Effect-TS applications
- Real-world patterns and solutions
🟢 Beginner Patterns
Debug Effect Programs
Rule: Use Effect.tap and logging to inspect values without changing program flow.
Good Example:
import { Effect, pipe } from "effect"
// ============================================
// 1. Using tap to inspect values
// ============================================
const fetchUser = (id: string) =>
Effect.succeed({ id, name: "Alice", email: "[email protected]" })
const processUser = (id: string) =>
fetchUser(id).pipe(
// tap runs an effect for its side effect, then continues with original value
Effect.tap((user) => Effect.log(`Fetched user: ${user.name}`)),
Effect.map((user) => ({ ...user, processed: true })),
Effect.tap((user) => Effect.log(`Processed: ${JSON.stringify(user)}`))
)
// ============================================
// 2. Debug a pipeline
// ============================================
const numbers = [1, 2, 3, 4, 5]
const pipeline = Effect.gen(function* () {
yield* Effect.log("Starting pipeline")
const step1 = numbers.filter((n) => n % 2 === 0)
yield* Effect.log(`After filter (even): ${JSON.stringify(step1)}`)
const step2 = step1.map((n) => n * 10)
yield* Effect.log(`After map (*10): ${JSON.stringify(step2)}`)
const step3 = step2.reduce((a, b) => a + b, 0)
yield* Effect.log(`After reduce (sum): ${step3}`)
return step3
})
// ============================================
// 3. Debug errors
// ============================================
const riskyOperation = (shouldFail: boolean) =>
Effect.gen(function* () {
yield* Effect.log("Starting risky operation")
if (shouldFail) {
yield* Effect.log("About to fail...")
return yield* Effect.fail(new Error("Something went wrong"))
}
yield* Effect.log("Success!")
return "result"
})
const debugErrors = riskyOperation(true).pipe(
// Log when operation fails
Effect.tapError((error) => Effect.log(`Operation failed: ${error.message}`)),
// Provide a fallback
Effect.catchAll((error) => {
return Effect.succeed(`Recovered from: ${error.message}`)
})
)
// ============================================
// 4. Trace execution flow
// ============================================
const step = (name: string, value: number) =>
Effect.gen(function* () {
yield* Effect.log(`[${name}] Input: ${value}`)
const result = value * 2
yield* Effect.log(`[${name}] Output: ${result}`)
return result
})
const tracedWorkflow = Effect.gen(function* () {
const a = yield* step("Step 1", 5)
const b = yield* step("Step 2", a)
const c = yield* step("Step 3", b)
yield* Effect.log(`Final result: ${c}`)
return c
})
// ============================================
// 5. Quick debug with console
// ============================================
// Sometimes you just need console.log
const quickDebug = Effect.gen(function* () {
const value = yield* Effect.succeed(42)
// Effect.sync wraps side effects
yield* Effect.sync(() => console.log("Quick debug:", value))
return value
})
// ============================================
// 6. Run examples
// ============================================
const program = Effect.gen(function* () {
yield* Effect.log("=== Tap Example ===")
yield* processUser("123")
yield* Effect.log("\n=== Pipeline Debug ===")
yield* pipeline
yield* Effect.log("\n=== Error Debug ===")
yield* debugErrors
yield* Effect.log("\n=== Traced Workflow ===")
yield* tracedWorkflow
})
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 · 1,587 lines · 27 tokens per session scan A d7e4b18e667b
effect-patterns-observability is a skill published in the GitHub repository PaulJPhilp/EffectPatterns (807 stars, last pushed 4mo ago), licensed MIT. It adds 27 tokens to every session and 10,482 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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