Validate FastGPT System Plugin Submissions Before Deployment

This page provides a structured verification checklist for FastGPT system plugin submissions, ensuring all plugins meet platform requirements before deployment. Following this checklist reduces post-submission errors, ensures compliance with FastGPT plugin standards, and validates end-to-end functionality.

Manifest & Core Configuration Checks

This section covers mandatory metadata and structural validation for the plugin codebase. Confirm each of the following requirements are met:

• The index.ts entry file exports a valid default export compatible with FastGPT’s plugin system.
• The top-level manifest object includes all required core fields: pluginId, version, bilingual (Chinese and English) display names, and bilingual descriptive text.
• All entries in the toolkit’s children[] array have stable, unique id values to avoid conflicts during plugin registration.
• The inputSchema definition includes every user-facing input field, with explicit type and range constraint specifications for mandatory inputs.
• The outputSchema exactly matches the data structure returned by the plugin’s handler function to ensure consistent data formatting for FastGPT workflows.
• The secretSchema covers all sensitive configuration fields, with each sensitive value marked using isSecret: true to prevent accidental exposure of credentials or private data.

Functional Testing & Validation

This step-by-step workflow validates the plugin’s runtime behavior and code integrity:

1. Execute the official FastGPT plugin validation commands: run pnpm run build, pnpm run check, and pnpm run pack to confirm all build, lint, and packaging processes complete successfully.
2. Run the test suite with pnpm run test; if testing is not feasible for this plugin, document the explicit reason for skipping test execution.
3. Validate external API integration handling: confirm the plugin correctly processes all possible API response scenarios, including successful requests, failed calls, empty responses, timeout events, and authentication failures.
4. Audit all error messages generated by the plugin: ensure each error provides actionable context to help debug issues, and never exposes sensitive secrets or raw external API response data.

Post-Packaging Deployment Checks

After packaging the plugin, confirm final deployment readiness:

• Inspect the generated dist/manifest.json file to verify that all icons and schema definitions match the expected configuration from your source code.
• Complete remote debugging: perform a real invocation of the plugin in a FastGPT test environment, or document the explicit reason remote debugging is not required for this change.
• Install the packaged .pkg plugin file in a test FastGPT environment, then run a full real-world invocation to confirm the plugin operates as intended.

Source: FastGPT official source

Applicability and version scope

Use this page for the documented Model guides scenario. Confirm the FastGPT, dependency, API, and deployment versions in the official source before applying a change.

Safety guardrails

Use [REDACTED_CREDENTIAL] for credentials and private data. Confirm the documented environment and version before review.

Rollback guidance

Restore the prior technical-content authority snapshot. Restore saved configuration and data snapshots, then repeat the smallest verification scenario.