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Cortex

by igrechuhin
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Python
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Fix Quality Issues

autofix

Automatically fix formatting, linting, type errors, and markdown issues after a quality gate failure to prepare code for the next check.

Instructions

Auto-fix formatting, linting, type errors, and markdown lint. Zero args required.

USE WHEN: Phase A fails and automated fixes are needed before re-running checks. Called by commit-checks, commit-final-gate, and implement-code agents after preflight_passed=false. Runs fix_errors, format, type_check, and markdown auto-fix.

INTEGRITY SAFEGUARDS:

  • Do not use this tool output as a "done" signal by itself; always re-run run_quality_gate() and validate changed modules still import cleanly.

  • If a fix iteration introduces new failures/regressions, roll back that attempt and retry with a different approach (max 3 attempts).

EXAMPLES:

  • autofix() immediately after a failing run_quality_gate() call to auto-fix formatting, linting, type, and markdown issues.

  • autofix() inside implement-code or commit-checks agents on the fix path before re-running the quality gate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.9/5.0
Behavior5/5

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

Annotations only provide readOnlyHint and destructiveHint as false. Description adds critical behavioral context: runs multiple fix types, warns about introducing new failures, and specifies rollback and retry behavior.

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?

Well-structured with clear sections: first line summary, USE WHEN, INTEGRITY SAFEGUARDS, EXAMPLES. Every sentence adds value, no fluff.

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

Completeness5/5

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

Complete coverage for a zero-parameter tool: what it does, when to use, side effects, failure handling, and examples. No missing context.

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?

No parameters exist, and description correctly states 'Zero args required'. With 0 params, baseline is 4; description adds clarity beyond schema.

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?

Description explicitly states auto-fix for formatting, linting, type errors, and markdown lint. It distinguishes from sibling tools like run_quality_gate by providing context when to use (Phase A fails) and which agents call it.

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

Usage Guidelines5/5

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

Includes a dedicated 'USE WHEN' section specifying condition: Phase A fails and automated fixes needed before re-running checks. Also details integrity safeguards with explicit warnings and limits (max 3 attempts).

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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