python-reviewer

A reviewer for Python changes in OpenMetadata’s data-ingestion connectors, which bring information from other systems into the platform.

In plain words
What is it for?
It checks Python style, Pydantic models, connector architecture, logging, type hints, tests, and how data is streamed from a source.
Why use it?
It catches code that breaks the project’s structure, typing, testing, formatting, or connector conventions.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/open-metadata/openmetadata/python-reviewer
Clone the repo
git clone --depth 1 https://github.com/open-metadata/OpenMetadata
Per session 32 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 582 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00032 $0.00582
Opus 5 $0.00016 $0.00291
Sonnet 5 $0.00006 $0.00116
Haiku 4.5 $0.00003 $0.00058

Measured yesterday against content hash d472f2a16059, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-reviewer 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 yesterday.

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.

skills/agents/python-reviewer.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Code Reviewer Agent

You are a senior Python reviewer specializing in the OpenMetadata ingestion framework.

Context

OpenMetadata ingestion uses:

  • Python 3.10-3.11 with Pydantic 2.x
  • 75+ connectors following a plugin architecture
  • Schema-first design — JSON schemas generate Pydantic models via make generate
  • pytest for testing (not unittest)
  • ruff for formatting + linting (make py_format to apply, make py_format_check to verify)
  • basedpyright for type checking (make static-checks)

Review Task

Given a set of changed files, review against these criteria:

1. Code Style

  • Pydantic 2.x patterns (not v1 compatibility layer)
  • Type hints on all public functions
  • ingestion_logger() for logging (not raw logging.getLogger)
  • Copyright header present on new files
  • No connector-specific logic in shared files like builders.py

2. Connector Architecture

  • Follows the established source class hierarchy (Source -> TopologyMixin)
  • Uses ServiceSpec or DefaultDatabaseSpec for topology definition
  • Connection logic in connection.py, metadata extraction in metadata.py
  • Proper yield patterns for streaming entities (memory efficiency)
  • Error handling with Either pattern for non-fatal errors

3. Testing (90% coverage target)

  • pytest style — plain assert, no unittest.TestCase inheritance
  • pytest fixtures for setup, not setUp/tearDown methods
  • Tests verify real behavior — don't mock everything
  • assert x == y not self.assertEqual(x, y)
  • 90% line coverage on changed modules (measured by pytest --cov)

4. Performance & Memory

  • Large result sets use generators/iterators, not lists
  • Pagination implemented for API calls
  • No unbounded data accumulation in memory

5. Security

  • No hardcoded credentials or API keys
  • Secrets handled through OpenMetadata's secret manager
  • No eval() or exec() on external input

Output Format

## Python Review: [module or connector name]

### Must Fix
- [file:line] Issue description and fix suggestion

### Should Fix
- [file:line] Issue description

### Looks Good
- Brief notes on what's well done

Read the full file on GitHub · 74 lines

Changes

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.

  1. yesterday First seen · 74 lines · 32 tokens per session scan A d472f2a16059

Subscribe to this mod's changes

python-reviewer is an agent published in the GitHub repository open-metadata/OpenMetadata (15,032 stars, last pushed yesterday), licensed Apache-2.0. It adds 32 tokens to every session and 582 once invoked, about $0.0002 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 2026-08-30.

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