---

name: component-development description: "Create and maintain Langflow Python components, extension bundles, component indexes, and component tests." disable-model-invocation: true metadata: disco-role: operating license: MIT

Langflow Component Development

Use this sub-skill when adding, updating, packaging, or testing Langflow Python components. It covers Component subclasses, inputs/outputs, extension bundles, dynamic loading, component index rebuilds, and component test structure.

Route First

• Use this sub-skill for Python component classes, inputs, outputs, Message/Data/DataFrame returns, bundle manifests, extension entry points, LFX_DEV, component index rebuilds, and component unit tests.
• Route backend API routes, services, auth, database, and graph internals to ../backend-runtime/SKILL.md.
• Route frontend icon import maps, React UI wiring, Vite, Jest, and Playwright work to ../frontend-development/SKILL.md.
• Route release automation, broad monorepo formatting/linting, version bumps, and CI policy to ../repo-maintenance/SKILL.md.

Core Workflow

1. Preserve identity before changing code: do not rename a released component class or its name attribute unless you intentionally create a new component and keep the old one as legacy = True.
2. Define or update the Component subclass with stable metadata, serializable inputs, and Output(..., method="...") entries that point to real instance methods.
3. Return Langflow schema objects (Message, Data, DataFrame) or integration objects expected by downstream handles; avoid returning raw provider responses unless the output contract says so.
4. For built-in components, place the class in the correct component category and update category exports or dynamic import maps consistently with the existing package pattern.
5. For extension bundles, package components behind a valid extension.json or [tool.langflow.extension] manifest and a langflow.extensions entry point.
6. Validate with the bundled skeleton helper first, then use focused native checks such as component unit tests, extension validation, and component index rebuilds when safe.

References

• references/component-api.md explains component class shape, metadata, inputs, outputs, return values, async behavior, and compatibility rules.
• references/bundles-and-indexes.md explains extension manifests, pyproject entry points, bundle IDs, dynamic loading, and component index rebuilds.
• references/troubleshooting.md maps common import, schema, CLI/API, runtime, credential, network, and hardware failures to fixes.

Helper Script

Run the local skeleton checker from this skill tree before deeper tests:

python scripts/check_component_skeleton.py path/to/component.py
python scripts/check_component_skeleton.py path/to/component.py --class MyComponent --import-module

The default mode parses Python only and is safe for components with missing optional dependencies. --import-module performs runtime checks and can import provider SDKs, so use it only in an environment with the component's dependencies installed.

Focused Validation Commands

Use the smallest safe command that covers the change:

python -m py_compile path/to/component.py
python scripts/check_component_skeleton.py path/to/component.py
make build_component_index
lfx extension validate path/to/extension/root
python -m pytest src/backend/tests/unit/components/<category>/test_<component>.py -q

For components requiring API keys, databases, GPUs, local OCR, Torch, or network services, keep the static checks runnable and mark native tests with the appropriate skip/credential guard instead of forcing credentials into tests.

Evidence Distilled

This guidance is distilled from Langflow component contribution docs, component test docs, extension manifest docs, the lfx Component implementation, the langflow compatibility shim, IO exports, bundle pyproject.toml/manifest patterns, the component index builder, and existing component tests. Runtime files here are self-contained; source paths are evidence names, not required reading for future agents.