agents-schema

v0.0.6 safe
3.0
Low Risk

Populate an in-warehouse agents.* schema from dbt manifests, OSI YAML, and LookML.

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network, shell, or obfuscation risks. The main concern lies in the incomplete author information, which slightly elevates the metadata risk.

  • No network calls detected
  • Incomplete author information
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access to function properly.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
  • Metadata: The author information is incomplete, which raises some concern, but there are no other red flags.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 3 test file(s) found

  • 3 test file(s) detected (e.g. test_connector_root.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (6721 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 55 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 4 unique contributor(s) across 59 commits in fivetran/agents_schema
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: fivetran.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository fivetran/agents_schema appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agents-schema 
Create a data management utility named 'SchemaSync' using the Python package 'agents-schema'. This tool aims to streamline the process of synchronizing schemas within a warehouse environment by leveraging dbt manifests, OSI YAML files, and LookML. SchemaSync will automate the population of the agents.* schema, ensuring consistency and accuracy across different data models and sources.

Step-by-Step Instructions:
1. Set up the initial project structure, including necessary dependencies like 'agents-schema', dbt, and any LookML parser libraries.
2. Develop a command-line interface (CLI) for users to interact with SchemaSync, allowing them to specify input files (dbt manifest, OSI YAML, LookML).
3. Implement a function to parse dbt manifests and extract relevant schema information.
4. Similarly, create functions to parse OSI YAML and LookML files.
5. Use 'agents-schema' to populate the agents.* schema with the extracted information from steps 3 and 4.
6. Add validation checks to ensure the integrity of the populated schema.
7. Integrate logging and error handling mechanisms to provide feedback during execution.
8. Test the utility thoroughly with various inputs to ensure reliability.
9. Document the usage and configuration options clearly.

Suggested Features:
- Support for incremental updates to avoid overwriting existing schema data.
- Option to generate reports summarizing changes made to the schema.
- Ability to handle multiple warehouses and environments.
- Integration with CI/CD pipelines for automated schema synchronization.

How 'agents-schema' is Utilized:
- 'agents-schema' will be the core library responsible for populating the agents.* schema. It provides functions to manage and update schema definitions efficiently. Users will invoke these functions through the CLI after parsing their input files.