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run_generated_tests

Execute generated test cases from decision tables to validate functionality using Playwright or API frameworks, returning structured results.

Instructions

Execute generated tests and return results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
test_pathYesPath to the test file to execute
frameworkYesTest framework
reporterNoTest reporter format (default: list)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions execution and returning results, but lacks critical behavioral details: what permissions are needed, whether this modifies state (e.g., runs tests that might affect a system), error handling, or performance implications. For a tool that executes tests, this is a significant gap.

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?

The description is a single, efficient sentence that gets straight to the point without unnecessary words. However, it's slightly under-specified given the tool's complexity, as it could benefit from a bit more context to be fully helpful.

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

Completeness2/5

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

Given no annotations and no output schema, the description is incomplete for a tool that executes tests. It doesn't explain what 'results' entail (e.g., pass/fail status, logs, reports), potential side effects, or how it interacts with the system. This leaves significant gaps for an AI agent to use it correctly.

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?

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no parameter-specific information beyond what's in the schema, such as explaining the relationship between 'test_path' and 'framework'. Baseline 3 is appropriate when the schema does the heavy lifting.

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

Purpose3/5

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

The description 'Execute generated tests and return results' clearly states the action (execute) and resource (generated tests), but it's vague about what 'generated tests' specifically means. It doesn't distinguish this tool from siblings like 'execute_api_test' or 'execute_web_test', which appear to be more specific variants.

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 provides no guidance on when to use this tool versus alternatives. With siblings like 'execute_api_test' and 'execute_web_test' that seem more specialized, there's no indication of whether this tool is a general-purpose executor or when to choose it over those specific ones.

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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