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check_obfuscation_risks

Scan a Python project to detect patterns that break obfuscation, such as eval/exec, dynamic attribute access, and unsafe model loading. Get severity counts, detected frameworks, and a suggested preset.

Instructions

Scan a Python project for patterns that may break obfuscation (eval/exec, dynamic attribute access, framework reflection, unsafe model loading). Returns severity counts, detected frameworks (FastAPI/Django/Flask/Pydantic/Click/SQLAlchemy/ML), and a suggested preset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description must carry the burden. It implies a read-only operation via 'scan' and lists return values, but does not explicitly state that the tool does not modify files, execute the project, or require special permissions. It also does not mention any limitations or edge cases beyond the listed patterns.

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

Conciseness5/5

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

The description is two sentences and front-loads the main purpose. The first sentence lists example patterns, the second lists return items. Every word adds value, and there is no redundancy or filler.

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

Completeness4/5

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

Given the tool's complexity and single parameter, the description is reasonably complete: it states what it scans, what it returns, and includes a suggested preset. However, it lacks context on when to invoke it in a workflow and does not explain how to interpret the results. With an output schema present, the return values are partially covered, so the description covers the essentials.

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

Parameters4/5

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

The input schema has a single 'path' parameter with no description, but the tool description says 'Scan a Python project,' clarifying that 'path' refers to the project location. This adds meaning beyond the raw schema, though it does not specify whether path should be a directory, file, or path format.

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

Purpose5/5

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

The description clearly states the tool scans a Python project for patterns that may break obfuscation, listing specific examples (eval/exec, dynamic attribute access, etc.). It also specifies the output (severity counts, frameworks, suggested preset), making it distinct from sibling tools that generate configs or obfuscate projects.

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?

The description does not explicitly state when to use this tool versus alternatives like protect_project or recommend_tier. There is no mention of prerequisites, whether to run before obfuscation, or exclusions for other tools. Usage is only implied by the verb 'scan'.

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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