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phoenice-labs

io.github.phoenice-labs/universal-test-framework

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generate_tests

Generate a complete test suite with automated language detection, contract validation, and traceability matrix linking tests to requirements.

Instructions

Generate a complete test suite satisfying the 8-section test contract.

The framework automatically:

  • Detects language and framework from source code

  • Generates tests for happy path, failure paths, and boundary cases

  • Validates every test against the 8-section contract before returning

  • Builds a traceability matrix linking tests to requirements

  • Identifies coverage gaps and makes recommendations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoOverride language detection. One of: python | typescript | javascript | java | go | cpp
file_pathNoFile path hint for language detection (e.g., 'src/auth.py')
frameworkNoOverride framework detection. One of: pytest | jest | junit5 | go-test | playwright | k6
test_typeYesType of tests to generate. One of: unit | integration | api | e2e | contract | performance | security
project_dirNoAbsolute path to the caller's project root. The SQLite registry and reports will be stored under <project_dir>/.utf/. Defaults to the current working directory of the MCP client process.
source_codeNoSource code to analyze (function/class/module). Optional but recommended.
requirements_textNoUser stories, acceptance criteria, Jira tickets, or requirements. Include IDs like US-001, AC-2.1, REQ-042 for traceability.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The description discloses key behaviors: automatic language/framework detection, test generation for multiple path types, contract validation, traceability matrix building, and coverage gap identification. Since no annotations are provided, the description carries the full burden. However, it omits the side effect of storing results in <project_dir>/.utf/, which is mentioned only in the parameter description.

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 concise with 6 bullet points and a clear first sentence. Every sentence adds value without redundancy. Slightly more structure (e.g., separating mandatory/optional steps) could improve it, but it is efficiently written.

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?

The description adequately explains the tool's automatic capabilities given the 7-parameter schema and existence of an output schema. However, it fails to mention the persistent storage side effect (registry and reports written to disk), which is important for understanding the tool's full impact. Output schema reduces the need to describe return values, but behavioral completeness is slightly lacking.

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% with all parameters well-documented. The description does not add parameter-specific meaning beyond the schema; it provides high-level context (e.g., automatic detection) but does not elaborate on individual parameters. Baseline 3 is appropriate.

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 'Generate a complete test suite satisfying the 8-section test contract.' The verb is specific (Generate), the resource is a test suite with a defined scope (8-section contract). It distinguishes itself from sibling tools like 'validate_test_contract' and 'analyze_coverage' by focusing on generation.

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?

No explicit guidance on when to use this tool versus alternatives. The description lacks 'when to use', 'when not to use', or mentions of prerequisites. Siblings like 'validate_test_contract' or 'analyze_coverage' exist, but the description does not guide the agent on choosing this tool over them.

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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