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open-context_get_python_info

Retrieve and cache Python package details from PyPI, including version-specific information when specified.

Instructions

Fetch and cache information about Python packages from PyPI (Python Package Index)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageNameYesName of the Python package (e.g., 'requests', 'django', 'numpy')
versionNoSpecific version of the package (optional, defaults to latest)
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses caching behavior ('Fetch and cache') which is valuable given no annotations exist. However, lacks critical behavioral details: cache duration/invalidation, what happens when a package doesn't exist, rate limits, or what specific data fields are returned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no redundancy and clear front-loading of action verbs. Efficient length but slightly too terse given the lack of output schema or annotations—could accommodate one more clause about return value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a simple 2-parameter tool with complete schema coverage. However, missing description of return values (no output schema exists) and lacks behavioral specifics like error handling for invalid packages or cache mechanics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage where both parameters have clear descriptions and examples, the schema does the heavy lifting. The description adds domain context ('from PyPI') but doesn't add parameter syntax, validation rules, or semantic details beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States specific action verbs (fetch, cache) and resource domain (Python packages from PyPI), clearly distinguishing it from sibling tools like get_npm_info or get_go_info through the explicit mention of 'PyPI'. Could be improved by specifying what information is retrieved (metadata, versions, dependencies).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides no explicit guidance on when to use this tool versus alternatives, or prerequisites like valid PyPI package names. While the domain is implied by 'Python packages', there's no explicit when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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