Single tool with minimal definition quality. Tool name 'verify_loop_invariant' lacks action verb clarity (should be 'verify_' prefix is present but compound name is awkward). Description is adequate (67 chars) but generic. No output schema documented. No error handling guidance. Tool appears hardcoded to a specific algorithm (Gauss summation) rather than accepting algorithm parameters, severely limiting reusability.

• Add a description to the 'n_values' parameter: 'List of integer values to test the loop invariant with. Each value is passed as the N variable in the loop state. Example: [1, 5, 10].'
• Document the output schema as a JSON object with fields: {initialization_ok: boolean, preservation_ok: boolean, postcondition_ok: boolean, all_passed: boolean, tested_inputs_count: integer}. Include what each field means.
• Refactor the tool to accept loop specification as parameters instead of hardcoding the Gauss algorithm. Add parameters for precondition, loop_guard, loop_body, invariant, postcondition (as serialized Python expressions or a domain-specific language), so the tool can verify arbitrary loops.
• Add error handling that returns structured failure details: {all_passed: false, failed_step: 'initialization'|'preservation'|'postcondition', failed_input: {...}, reason: '<human-readable explanation>'}.
• Expand the tool description from 67 chars to 150-200 chars explaining: what loop invariant verification is, when to use this tool (e.g., 'to formally verify that a loop correctly computes a result'), and what it returns (pass/fail for each correctness phase).