pstack/skills/principle-sequence-verifiable-units/SKILL.md
Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a reviewer.
npx skillsauth add cursor/plugins principle-sequence-verifiable-unitsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Order work as a sequence of small units, each ending in a state you can check, and don't advance until the current one is green. The same discipline runs at two altitudes, how you execute and how you deliver.
Why: A break caught at the unit that caused it is cheap to localize. A break caught after a batch is buried, and you have already built further on a broken base. Sequencing those same units into a delivery a reviewer can replay turns "trust me" into "watch it go red, then green."
Execution. In a sweep, migration, or any run of similar edits, verify each change before starting the next. Never batch the edits and verify once at the end. Each unit is a before/after bracket: known-good state, one change, run the check, then proceed. Rebase onto clean trunk first so every check measures against the real baseline. When a lever does the edits, the per-unit check is nearly free; run it anyway.
Delivery. Stack commits and PRs in the order that proves the work. The canonical shape is the failing test first, then the fix on top. The first unit shows the bug is real (red), the next shows it resolved (green), so a reviewer sees both the problem and the proof. Other story orders are a subtraction before the reshape, a baseline capture before the treatment, the scaffold before the feature. Each commit lands on its own and the sequence reads as an argument.
Pattern:
The sequencing complement to the prove-it-works principle skill, which keeps each check real, and the build-the-lever principle skill, which makes the per-unit check cheap.
documentation
Configure which models pstack uses per role. Detects your available models and writes an always-applied rule that overrides the skill defaults. Use for /setup-pstack, "configure pstack models", or changing pstack's model choices.
development
Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions via show-me-your-work. Use for /figure-it-out, 'figure it out', a large migration, or when no narrower playbook applies.
tools
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
data-ai
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill. Use when the user says reflect.