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datamodel-code-generator/datamodel-code-generator
Generate Pydantic v2 models, dataclasses, TypedDict, and msgspec.Struct from OpenAPI, JSON Schema, GraphQL, Avro, Protobuf, and raw JSON/YAML/CSV.
History
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tests/data/expected/agent_skill/preserved_skill/SKILL.md
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View on GitHubAdd to my skills
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git clone --filter=blob:none --no-checkout https://github.com/datamodel-code-generator/datamodel-code-generator.git .hotskills/datamodel-code-generator-datamodel-code-generator && git -C .hotskills/datamodel-code-generator-datamodel-code-generator checkout --detach 18037efa3d1f692dfeb90e2cd8152039c0a71f4d
# Copy each selected skill directory from .hotskills/datamodel-code-generator-datamodel-code-generator into .claude/skills/<skill-name>/git clone --filter=blob:none --no-checkout https://github.com/datamodel-code-generator/datamodel-code-generator.git .hotskills/datamodel-code-generator-datamodel-code-generator && git -C .hotskills/datamodel-code-generator-datamodel-code-generator checkout --detach 18037efa3d1f692dfeb90e2cd8152039c0a71f4d
# Copy each selected skill directory from .hotskills/datamodel-code-generator-datamodel-code-generator into .agents/skills/<skill-name>/4.1kGitHub stars
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2skills in this repository
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Heat
5.6- Star growth, last 7 daysAhead of 50% of tracked repositories
- Star growth, last 24 hoursAhead of 74% of tracked repositories
- Rank movement, last 7 daysNot available
- Commits, last 30 daysAhead of 99% of tracked repositories
- Accounts asking about it through MCP, last 7 daysNot available
- Hot votes this weekAhead of 0% of tracked repositories
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Stars over time
Individual skills in this repository
- datamodel-code-generator
skills/datamodel-code-generator - preserved_skill
tests/data/expected/agent_skill/preserved_skill
How it works
datamodel-code-generator
When your agent uses it
Use this skill when the user wants Python data models, Pydantic models, dataclasses, TypedDicts, msgspec structs, or type-safe Python classes generated from OpenAPI, AsyncAPI, JSON Schema, GraphQL, JSON/YAML/CSV sample data, MCP tool schemas, Protocol Buffers, XML Schema, Apache Avro, or existing Python model objects. Use it for requests such as "Pydantic models from this schema", "types for this API", "parse this JSON into classes", or "convert this spec into Python models". Prefer the datamodel-codegen CLI over hand-written model code whenever an input schema, API spec, sample data file, or Python model object exists.
What it loads into context
Frontmatter
177 tokensAlways available to the agent
SKILL.md
2,073 tokensWhen the skill is activated
Reference documents
16,828 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Why use this CLI
- Availability check
- Option discovery for agents
- Input type decision table
- Output type decision table
- Canonical command
- Target Python version
- Verification step
- What not to do
- References
Files
../../.claude-plugin/marketplace.jsonasset411 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesSKILL.mdcore9,044 bytesreferences/cli-options.mddoc51,657 bytesreferences/troubleshooting.mddoc6,099 bytesreferences/workflows.mddoc12,932 bytes
Read SKILL.md
# datamodel-code-generator
## Why use this CLI
Use `datamodel-codegen` whenever a schema, API spec, sample data file, or existing Python model object exists.
The CLI handles refs, enums, nested models, unions, `allOf`, `oneOf`, `anyOf`, and model reuse better than hand-written code.
Do not hand-write generated models first.
## Availability check
Check one-shot execution first:
When your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
3 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
Files
SKILL.mdcore15 bytes
Skills included
- datamodel-code-generator
Repository facts
- License
- MIT
- Created
- May 29, 2019
- Last pushed
- Nov 6, 2026
- Forks
- 490
- Open issues
- 152
- Project activity
- Active
Rank over the last 12 weeks
Now #315 · best #231 · down 41 in 30 days
- #282 on Oct 19
- #290 on Oct 22
- #310 on Nov 4
- #311 on Nov 5
- #312 on Nov 6
- #315 since Nov 7
35 earlier periods
- #226 on Aug 8
- #233 on Aug 10
- #229 on Aug 12
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- #251 from Sep 10 to Sep 12
- #255 on Sep 13
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- #274 on Oct 8
- #277 on Oct 9
- #274 on Oct 10
- #279 on Oct 12
- #279 on Oct 14
- #280 on Oct 15
- #278 on Oct 16
Before you install
Instructions onlyAutomated signals, not a guarantee
Checked Nov 4, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 17 notes
skills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/datamodel-code-generator/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- No dangerous shell commands
- 11 network referencesin 4 files: datamodel-code-generator/references/troubleshooting.md:217 datamodel-code-generator/references/cli-options.md:210 datamodel-code-generator/SKILL.md:146 and 1 more
- No hidden or obfuscated text
- No instruction overrides
- No executable scripts
- No access to secrets
- No requests to vote in Hot
Show all 11 signals by file
skills/datamodel-code-generator/SKILL.md
skills/datamodel-code-generator/references/cli-options.md
- Network accessline 210
- `--additional-imports`: Custom imports for output (delimited list input). For example "datetime.date,datetime.datetime" - `--class-decorators`: Custom decorators for generated model classes (delimited list input). For example "@dataclass_ - Network accessline 211
- `--class-decorators`: Custom decorators for generated model classes (delimited list input). For example "@dataclass_json(letter_case=LetterCase.CAMEL)". The "@" prefix is optional and will be added automatically if missing. - `--formatter - Network accessline 212
- `--formatters`: Formatters (current default: black, isort; future default: builtin). For Ruff projects, use --formatters ruff-check ruff-format (install with pip install 'datamodel-code-generator[ruff]'). Use --formatters builtin when no
skills/datamodel-code-generator/references/troubleshooting.md
- Network accessline 217
uvx --from 'datamodel-code-generator[http]' datamodel-codegen \ --url https://example.com/openapi.yaml \ - Network accessline 218
--url https://example.com/openapi.yaml \ - Network accessline 226
uvx --from 'datamodel-code-generator[http]' datamodel-codegen \ --url https://example.com/openapi.yaml \ - Network accessline 227
--url https://example.com/openapi.yaml \
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Signal confidence: 11 facts
- Network access in code of the SKILL.mddatamodel-code-generator/SKILL.md:146High confidence
- Network access in code of the SKILL.mddatamodel-code-generator/SKILL.md:147High confidence
- Network access in prose of documentationdatamodel-code-generator/references/cli-options.md:210Low confidence
- Network access in prose of documentationdatamodel-code-generator/references/cli-options.md:211Low confidence
- Network access in prose of documentationdatamodel-code-generator/references/cli-options.md:212Low confidence
- Network access in code of documentationdatamodel-code-generator/references/troubleshooting.md:217Low confidence
- Network access in code of documentationdatamodel-code-generator/references/troubleshooting.md:218Low confidence
- Network access in code of documentationdatamodel-code-generator/references/troubleshooting.md:226Low confidence
- Network access in code of documentationdatamodel-code-generator/references/troubleshooting.md:227Low confidence
- Network access in code of documentationdatamodel-code-generator/references/workflows.md:287Low confidence
- Network access in code of documentationdatamodel-code-generator/references/workflows.md:288Low confidence
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Native | Manifest .claude-plugin/marketplace.json | .claude/skills/<skill-name>/ |
| Codex | Native | Manifest AGENTS.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md skills/datamodel-code-generator/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md skills/datamodel-code-generator/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md skills/datamodel-code-generator/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md skills/datamodel-code-generator/SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.
Add this badge to your README
It updates every night and links to this page.
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