Execute step-by-step implementation plans with JSONL trajectory logging.
npx skills add https://github.com/mishahanin/heading-os --skill implement-mishahanin
Please help me install this Agent Skill. Skill: implement Source: https://github.com/mishahanin/heading-os/tree/main/.claude/skills/implement Command: npx skills add https://github.com/mishahanin/heading-os --skill implement-mishahanin
This skill solves the problem of inconsistent or unverified execution of complex technical plans by enforcing a strict, audit-ready workflow that ensures every step is tracked and verified.
Execute the implementation plan located at plans/2026-07-08-new-export.md step by step.
High-intent search queries and answers about installing and using this skill.
To execute a technical implementation plan with an audit trail, you can use a structured execution workflow that processes steps sequentially while generating a JSONL trajectory file for automated verification of every phase.
Trajectory logging in software development workflows is the process of recording every execution phase into a structured JSONL file, ensuring high-fidelity audit trails and enabling automated scrutiny of complex technical plan execution.
Automate quality assurance and file modification verification by running an execution workflow with built-in pre-implementation gate checks, parallel wave dispatching, and rigorous post-run self-validation of all modified files.
Yes, this structured execution workflow requires python3 as a dependency to coordinate step-by-step task completion, dispatch parallel waves, and generate audit-ready trajectory logs for your technical plans.
Yes, you can use this for parallel wave dispatching in complex technical plans, as the execution workflow explicitly satisfies requirements for deterministic execution across multiple concurrent waves while maintaining strict trajectory logging.
You need an audit-ready execution workflow for software development when your projects require high-fidelity audit trails, verified file modifications, and automated quality assurance to ensure consistent and trackable technical implementation outcomes.
alffeiGenerate implementation plans for multi-step software tasks with date-based filenames.
MassimilianoPiliAggregate JSONL audit event logs into human-readable Markdown reports.
manutejRun parallel applicative-style verification checks to produce consolidated results.
wayne930242Classify knowledge tasks and delegate them to appropriate Claude Code skills via the Skill tool.
