Governed execution for AI work
Musketeer is a governed execution harness for role-separated AI work. It structures planning, challenge, execution, and review into explicit stages with clear handoffs, bounded loops, and auditable outcomes.
Not an agent framework. Not a chat wrapper. Not another orchestration toy.
Musketeer does not replace model runtimes, coding agents, or SDKs. It governs how work moves through them.
Use the models and tools you already trust. Musketeer adds execution discipline around them.
Why it exists
Most failures in AI-assisted engineering are not model failures. They are workflow failures. Intent drifts. Planning and execution collapse into the same thread. Validation is performed by the same system that produced the output. Context bloats. Constraints blur. Trust drops.
Musketeer exists to impose separation, control, and accountability on that process.
What Musketeer enforces
How it works
Stage intent
Define the task, constraints, acceptance criteria, and operating boundaries before work begins.
Challenge the plan
Run an independent examination phase to expose weak assumptions, missing detail, or protocol drift.
Execute with boundaries
Perform bounded work against an explicit handoff package instead of vague conversational momentum.
Review and continue cleanly
Inspect results, accept or reject outcomes, and resume from a known state without losing the thread.
The execution model
Musketeer supports a role-separated work cycle built around three operational responsibilities:
Originator
Forms intent. Shapes scope. Defines constraints and acceptance criteria. Prepares the handoff package.
Examiner
Challenges assumptions. Checks alignment. Exposes drift. Strengthens handoffs or reviews results.
Executor
Acts against explicit instructions. Stays inside defined boundaries. Produces concrete outputs.
These are not personalities. They are control boundaries. One provider can fill multiple roles. Different providers can fill different roles. The point is not which model is used. The point is that the responsibilities stay separated.
Built to work with the ecosystem around it
Musketeer is compatible with model runtimes and agent systems. It is designed to govern work around them, not replace them.
Use GPT, Gemini, Claude, Codex, local models, or custom workers. Musketeer controls how work is staged, challenged, executed, reviewed, and resumed.
Musketeer does not try to make models smarter. It makes model-driven work more governable.