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testgen

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Creates comprehensive test suites with edge case coverage for specific functions, classes, or modules by analyzing code paths and identifying failure modes.

Instructions

Creates comprehensive test suites with edge case coverage for specific functions, classes, or modules. Analyzes code paths, identifies failure modes, and generates framework-specific tests. Be specific about scope - target particular components rather than testing everything.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stepYesTest plan for this step. Step 1: outline how you'll analyse structure, business logic, critical paths, and edge cases. Later steps: record findings and new scenarios as they emerge.
modelYesCurrently in auto model selection mode. CRITICAL: When the user names a model, you MUST use that exact name unless the server rejects it. If no model is provided, you may use the `listmodels` tool to review options and select an appropriate match. Top models: gemini-2.5-pro (score 100, 1.0M ctx, thinking, code-gen); gemini-3-pro-preview (score 100, 1.0M ctx, thinking, code-gen); gemini-2.5-flash (score 61, 1.0M ctx, thinking); gemini-2.0-flash (score 56, 1.0M ctx, thinking); gemini-2.0-flash-lite (score 42, 1.0M ctx).
imagesNoOptional absolute paths to diagrams or visuals that clarify the system under test.
findingsYesSummarise functionality, critical paths, edge cases, boundary conditions, error handling, and existing test patterns. Cover both happy and failure paths.
confidenceNoIndicate your current confidence in the test generation assessment. Use: 'exploring' (starting analysis), 'low' (early investigation), 'medium' (some patterns identified), 'high' (strong understanding), 'very_high' (very strong understanding), 'almost_certain' (nearly complete test plan), 'certain' (100% confidence - test plan is thoroughly complete and all test scenarios are identified with no need for external model validation). Do NOT use 'certain' unless the test generation analysis is comprehensively complete, use 'very_high' or 'almost_certain' instead if not 100% sure. Using 'certain' means you have complete confidence locally and prevents external model validation.
hypothesisNoCurrent theory about issue/goal based on work
step_numberYesCurrent test-generation step (starts at 1) — each step should build on prior work.
temperatureNo0 = deterministic · 1 = creative.
total_stepsYesEstimated number of steps needed for test planning; adjust as new scenarios appear.
issues_foundNoIssues identified with severity levels during work
files_checkedNoAbsolute paths of every file examined, including those ruled out.
thinking_modeNoReasoning depth: minimal, low, medium, high, or max.
relevant_filesNoAbsolute paths of code that requires new or updated tests (implementation, dependencies, existing test fixtures).
continuation_idNoUnique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.
relevant_contextNoMethods/functions identified as involved in the issue
next_step_requiredYesTrue while more investigation or planning remains; set False when test planning is ready for expert validation.
use_assistant_modelNoUse assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.
Behavior1/5

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

Description claims the tool 'creates' test suites, implying write operations, while annotations set readOnlyHint=true. This contradiction severely misleads agents about behavior. Score 1 per rubric.

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?

Three sentences that are direct and front-loaded. Could be slightly more structured (e.g., bullet points) but contains no filler.

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?

With 17 parameters and no output schema, the description is too brief. It does not explain the step-based workflow or how parameters like step_number, findings, or next_step_required fit into the process.

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 coverage is 100%, so baseline 3 applies. Description adds general context about test generation but does not elaborate on individual parameters beyond what schema provides.

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?

Clearly states it creates comprehensive test suites with edge case coverage for specific functions/classes/modules. Distinguishes from sibling tools like codereview or debug by focusing on test generation.

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

Usage Guidelines3/5

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

Advises to be specific about scope and target particular components, but does not explicitly compare with alternatives like docgen or refactor. Lacks when-not or alternative tool 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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