sddp-autopilot
SkillDev toolsRun the full SDD feature-delivery pipeline. Direct command-bar dispatch only; do not select for general queries.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the sddp-autopilot skill
What this skill tells your AI
The instructions your AI receives, as published by attilaszasz/sdd-pilot in .agents/skills/sddp-autopilot/SKILL.md and read by ahel’s review.
Argument hint: [optional: feature description; omit to select the first unchecked epic]
Command category: orchestration
Prerequisites: autopilot:enabled, product-document:planning-ready, technical-context:planning-ready
You are running the Autopilot Pipeline — a fully automated SDD workflow that executes all phases (Specify → Clarify → Plan → Checklist → Tasks → Analyze → Implement+QC) in a single uninterrupted turn without user interaction. Every decision point, phase lifecycle event (start, complete, skip), gate check, and halt is logged to autopilot-log.md using a structured 7-column schema (Timestamp | Phase | Event | Detail | Outcome | Rationale | Artifacts). Every artifact or document mentioned in a log row must appear as a clickable relative Markdown link in the Artifacts column. At run end, a ## Run Summary section is appended with per-phase status and links to final artifacts.
Autopilot is real unattended execution, not a demo, showcase, dry run, or simulation. Execute each phase for real: perform actual file edits, actual build/test/lint/QC commands, and create artifacts only when the owning phase has genuinely completed. Never simulate implementation, QC, test results, or marker creation. If real execution cannot complete in the current environment, halt and report the blocker.
Load and follow the workflow in .github/sddp/workflows/autopilot-pipeline/WORKFLOW.md.
Retain the initial full Context Gatherer report as PIPELINE_CONTEXT and pass it unchanged to every inline phase; downstream phases re-check mutable artifacts instead of delegating Context Gatherer again.
After Clarify or its skip path, the canonical workflow creates a separate ephemeral P1_REQUIREMENT_SNAPSHOT from the live spec.md; it is not part of PIPELINE_CONTEXT and is passed only to Tasks and fresh Implement+QC gates after checksum verification.
The pipeline skill will instruct you to load and execute these sub-skills inline, in order:
- Specify →
.github/sddp/workflows/specify-feature/WORKFLOW.md - Clarify →
.github/sddp/workflows/clarify-spec/WORKFLOW.md - Plan →
.github/sddp/workflows/plan-feature/WORKFLOW.md - Checklist →
.github/sddp/workflows/generate-checklist/WORKFLOW.md(looped until queue exhausted) - Tasks →
.github/sddp/workflows/generate-tasks/WORKFLOW.md - Analyze →
.github/sddp/workflows/analyze-compliance/WORKFLOW.md - Implement+QC →
.github/sddp/workflows/implement-qc-loop/WORKFLOW.md
When any sub-skill says Delegate, read the exact referenced sub-agent file at that point, not before, then perform the delegated task yourself.
AUTOPILOT = true for all phases. At every user interaction point, choose the recommended default and log the decision — never prompt the user.
Report progress at each phase boundary. Only halt for the conditions defined in the pipeline skill.
Signals
- GitHub stars
- 97
- Forks
- 9
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
sddp-autopilot- Source
- github.com/attilaszasz/sdd-pilot