strikersam

pro-workflow

Core AI coding workflow. Orchestrates 8 patterns: Scout → Plan → Implement → Review, with smart commits, session rituals, and continuous learning capture. This is the master skill — invoke it at the start of any non-trivial task.

strikersam 11 8 Updated 4mo ago
GitHub

Install

npx skillscat add strikersam/autonomous-ai-agency/pro-workflow

Install via the SkillsCat registry.

SKILL.md

Skill: pro-workflow

The 8 Core Patterns

# Pattern Skill
1 Scout before you implement scout agent
2 Plan before you code implementation-planner
3 Test first test-first-executor
4 Review before merge council-review
5 Commit with quality gates smart-commit
6 Persist corrections learn-rule
7 Surface past patterns replay-learnings
8 Hand off cleanly wrap-up + session-handoff

Workflow: Research → Plan → Implement

┌─────────────┐     ┌─────────────┐     ┌─────────────────┐
│  RESEARCH   │────▶│    PLAN     │────▶│   IMPLEMENT     │
│             │     │             │     │                 │
│ Scout scores│     │ Planner     │     │ Phased execution│
│ readiness.  │     │ breaks down │     │ Reviewer gates  │
│ GO / HOLD   │     │ steps.      │     │ each checkpoint │
└─────────────┘     └─────────────┘     └─────────────────┘
       │                   │                     │
  Validation          Validation            Validation
  gate: must          gate: must            gate: must
  pass before         pass before           pass before
  proceeding          proceeding            merge

Validation gate between each phase — must pass before proceeding.


Instructions

Phase 1 — Research (Scout)

  1. Invoke the Scout agent with the task description.
  2. If Scout returns HOLD: resolve each gap, then re-score.
  3. If Scout returns GO: proceed to Phase 2.
Scout checklist:
- [ ] Score ≥ 70 (GO verdict)
- [ ] Context mode selected (DEV / REVIEW / RESEARCH)
- [ ] No unresolved gaps

Phase 2 — Plan

  1. Run the implementation-planner skill (or /plan command).
  2. Review the plan for risky modules — invoke risky-module-review if flagged.
  3. Check replay-learnings for relevant past patterns before accepting the plan.
Plan checklist:
- [ ] Plan produced with ordered steps
- [ ] Risky modules flagged and reviewed
- [ ] Past learnings consulted
- [ ] Max 10 steps (split if more)

Phase 3 — Implement

  1. Execute plan steps one at a time.
  2. After each file change, Reviewer agent validates before writing.
  3. Run pytest -x after each logical group of changes.
  4. Run deslop skill before final commit to remove AI code slop.
  5. Run smart-commit to gate and commit.
Implement checklist:
- [ ] Reviewer passed each file change
- [ ] pytest -x green after each step
- [ ] docs/changelog.md updated
- [ ] deslop run before commit
- [ ] smart-commit used for final commit

Phase 4 — Wrap Up

  1. Run council-review if changes are > 50 lines or touch risky modules.
  2. Run wrap-up skill to close the session.
  3. Run learn-rule to persist any corrections from this session.
  4. Run session-handoff to write resume docs for the next session.

Model Selection Guide

Use the right Claude model for the task type:

Task Model
Quick fixes, typos, config changes Haiku 4.5
New features, standard implementations Sonnet 4.6 (adaptive thinking)
Refactors, structural changes Opus 4.6 (adaptive thinking)
Architecture decisions, ADR writing Opus 4.6 (1M context)
Hard bugs, deep debugging Opus 4.6 (1M context)

Acceptance Checks

  • Scout scored ≥ 70 before implementation started
  • Plan was produced and reviewed
  • All tests pass
  • Changelog updated
  • Commit made with smart-commit
  • Session closed with wrap-up