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SKILL verified MIT Self-run

Specx Settings

skill-maksimzayats-specx-specx-settings · by maksimzayats

Add runtime configuration to specx Python services with `pydantic-settings`. Use when creating settings classes, environment variables, `.env.example`, injecting settings at delivery, infrastructure, or composition edges, documenting config, mapping configuration into typed core policy collaborators, or removing direct environment reads from core code.

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Install

$ agentstack add skill-maksimzayats-specx-specx-settings

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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22d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

specx Settings

Use this skill whenever runtime configuration is needed. Read references/settings.md before adding settings code.

Rules

  • Model runtime config with classes that inherit BaseRuntimeSettings.
  • Give each settings class a docstring that explains the configuration scope

and includes a concrete Example:.

  • Place settings near the class that consumes them unless the setting is truly

application-wide.

  • Logging settings are application-wide and live beside

infrastructure/logging/configurator.py and its LoggingConfigurator.

  • Use BaseStrEnum for finite configuration values such as logging levels.
  • Inject settings objects only into delivery, infrastructure, and composition

classes. Do not inject BaseRuntimeSettings subclasses into core use cases, services, capabilities, entities, repositories, or gateway ports.

  • When configuration represents a genuine business policy, map it at the

composition root into a typed core value or capability that has no dependency on Pydantic or BaseRuntimeSettings.

  • Let diwire auto-register settings as root-scoped singletons. Register a

settings instance explicitly only for an intentional override.

  • At operational entrypoints, load required runtime values with

SettingsClass.from_environment(). Build explicit test or composition overrides with SettingsClass.model_validate({...}) so strict type checking does not mistake raw input strings for already-validated field types.

  • Do not read os.environ outside settings classes or composition code.
  • Use clear environment variable names and safe defaults only when safe.
  • Type secret fields with SecretStr, keep secrets out of examples, and unwrap

them only at the adapter call that needs the raw value.

  • Update .env.example when adding user-provided environment variables.
  • Isolate settings-source tests from a developer's .env by changing to

tmp_path, then override environment values with monkeypatch.

  • Do not inherit raw BaseSettings; inherit

specx.infrastructure.foundation.settings.BaseRuntimeSettings.

Code Style

Use blank lines as logical separators in all code. Keep related statements together, but separate independent setup, action, assertion, response, branch, and transformation groups so long blocks stay readable.

References

  • references/settings.md - settings placement, examples, env naming, and test

overrides.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.