Borrowing it
Nothing to install: this file belongs to mepuka/effect-ontology. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mepuka/effect-ontology/main/.claude/skills/effect-config-schema/SKILL.mdgit clone --depth 1 https://github.com/mepuka/effect-ontologyWrote 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/mepuka/effect-ontology/effect-config-schema)<a href="https://agentmods.dev/skills/mepuka/effect-ontology/effect-config-schema"><img src="https://agentmods.dev/badge/skills/mepuka/effect-ontology/effect-config-schema.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 5.1 | $0.00020 | $0.00844 |
| Opus 5 | $0.00010 | $0.00422 |
| Sonnet 5 | $0.00004 | $0.00169 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
effect-config-schema 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 7d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Config & Schema
When to use
- Validating request bodies, params, or external inputs
- Loading environment configuration with types
Config (example)
import { Config } from "effect"
const Server = Config.nested("SERVER")(Config.all({
host: Config.string("HOST"),
port: Config.number("PORT")
}))
Schema Validate
import { Schema as S } from "effect"
const User = S.Struct({ id: S.Number, name: S.String })
const decodeUser = (u: unknown) => S.decodeUnknown(User)(u)
Transform
const IsoDate = S.String // then transform to Date in pipeline where needed
Real-world snippet: Layer selecting AWS credentials via Config options
class AwsCredentials extends Effect.Service<AwsCredentials>()("AwsCredentials", {
effect: Effect.gen(function* () {
const accessKeys = yield* Config.option(
Config.all([Config.string("CAP_AWS_ACCESS_KEY"), Config.string("CAP_AWS_SECRET_KEY")])
)
const vercelAwsRole = yield* Config.option(Config.string("VERCEL_AWS_ROLE_ARN"))
const credentials = yield* Effect.gen(function* () {
if (Option.isSome(vercelAwsRole)) return awsCredentialsProvider({ roleArn: vercelAwsRole.value })
if (Option.isSome(accessKeys)) {
const [accessKeyId, secretAccessKey] = accessKeys.value
return { accessKeyId, secretAccessKey }
}
return fromContainerMetadata()
})
return { credentials }
})
})
Guidance
- Prefer schemas close to boundaries; keep core logic typed
- For branded types (Email, PositiveInt), use transform/brand helpers
- Validate early, map to domain errors in one place
Pitfalls
- Accepting
unknowninto core → always decode first - Large ad-hoc validation code → centralize in Schema
Cross-links
- HTTP & Routing for endpoint validation
- Foundations for operator style
Local Source Reference
CRITICAL: Search local Effect source before implementing
The full Effect source code is available at docs/effect-source/. Always search the actual implementation before writing Effect code.
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.
- 7d ago First seen · 114 lines · 20 tokens per session scan A dda5a51d38eb
effect-config-schema is a skill published in the GitHub repository mepuka/effect-ontology (5 stars, last pushed 8mo ago), licensed MIT. It adds 20 tokens to every session and 844 once invoked, about $0.0001 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 2026-08-31.
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