mindcockpit.ai
Official@mindcockpit-ai · München
Mindcockpit provides standardized architectural governance, code quality enforcement, and modernization patterns for enterprise software development lifecycles.
Agent Skills by mindcockpit.ai
Showing 52 vetted skills indexed across 1 GitHub repositories.
mindcockpit-aiacceptance-verification
Verify GitHub issue acceptance criteria against codebase evidence.
mindcockpit-aisession-resume
Load the latest session document, MEMORY.md, and git state at session start.
mindcockpit-aicode-review
Automates project-aware code review enforcing configured lint standards and conventions from CLAUDE.md and cognitive-core.conf.
mindcockpit-aitech-intel
Identify and summarize technology developments affecting a software stack.
mindcockpit-aiworkspace-monitor
Detect errors, warnings, and anomalies in project logs and build artifacts.
mindcockpit-aisession-sync
Detect configuration drift between local repositories and remote origin.
mindcockpit-aismoke-test
Run automated smoke tests on web endpoints and create GitHub issues for failures.
mindcockpit-aictf-pentesting
Guide penetration testing and CTF workflows across recon, enumeration, exploitation, and privilege escalation.
mindcockpit-ailint-debt
Scan lint suppression comments and sync them with GitHub issues.
mindcockpit-aisecurity-baseline
Provide OWASP-aware security rules and vulnerability patterns for codebases.
mindcockpit-aisecrets-setup
Scan repositories for plaintext secrets and generate env.tpl templates.
mindcockpit-aiskill-sync
Compare installed agents, skills, and hooks with a source repository and apply updates.
mindcockpit-aie2e-visual-regression
Automate Playwright visual regression testing to detect UI changes across browsers.
mindcockpit-aibatch-review
Coordinate parallel and sequential batches for multi-file code review and migration.
mindcockpit-aitest-scaffold
Generate language-appropriate test file scaffolds from source modules using cognitive-core configuration.
mindcockpit-aifitness
Evaluate code quality against configurable fitness gates from cognitive-core.conf.
mindcockpit-aiworkflow-analysis
Analyze business workflows with stepwise templates and risk assessments.
mindcockpit-aipre-commit
Run configured lint and syntax checks on staged files before commits.
mindcockpit-aiproject-board
Coordinates GitHub Projects, Jira, and YouTrack boards via pluggable scripts.
mindcockpit-aiproject-status
Generate project status reports from git history, session documents, and working tree.
mindcockpit-aisetup
Generate project-specific cognitive-core.conf with interactive prompts and preflight checks.
mindcockpit-aipython-messaging
Coordinate Python async messaging across events, Redis, Celery, and Kafka.
mindcockpit-aipython-patterns
Guide Python 3.12+ codebases through modern typing, Pydantic v2, and async patterns.
mindcockpit-aipython-ddd
Structure Python projects with domain, application, and infrastructure layers.
Frequently Asked Questions About mindcockpit.ai
FAQPage SchemaWhat specific development tasks are enabled by these capabilities?▼
These capabilities enable automated code reviews, technical debt identification, legacy application migration, and the implementation of standardized messaging patterns. They facilitate consistent project scaffolding, security baseline enforcement, and comprehensive end-to-end testing across diverse technology stacks.
Which personas benefit most from these technical capabilities?▼
Software architects, lead developers, and DevOps engineers benefit from these capabilities. They are designed for teams managing complex, multi-language codebases who require standardized governance, automated quality gates, and structured migration paths for legacy enterprise systems.
What are the primary prerequisites for integrating these capabilities?▼
Integration requires a repository-based configuration file, specifically cognitive-core.conf, to define project-specific standards and fitness gates. Users must also maintain a git-based environment to support session synchronization, state tracking, and the application of linting or migration patterns.