From mck-scaffold
Use this skill when the user asks to "set up a new project", "start a new project", "scaffold a project", "pick a methodology", "choose an SDD framework", "configure Claude Code for this project", "what methodology should I use", or discusses agentic development methodology selection. Helps the user route to the right Spec-Driven Development approach based on Piskala's three-level rigor taxonomy and Wasowski's four decision contexts. Does NOT write files — conversational guidance only. For actual scaffolding, route to /mck-scaffold:init.
How this skill is triggered — by the user, by Claude, or both
Slash command
/mck-scaffold:methodology-pickerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Help the user pick the right Spec-Driven Development methodology for their project context. This is conversational guidance, not scaffolding. The user is making a decision; you are helping them frame it.
Help the user pick the right Spec-Driven Development methodology for their project context. This is conversational guidance, not scaffolding. The user is making a decision; you are helping them frame it.
The user mentions:
/mck-scaffold:init.| Level | Promise | Cost | When to pick it |
|---|---|---|---|
| L1 Spec-First | Flexibility | Low | ~80% of projects. Spec lives in the feature branch and becomes historical after merge. |
| L2 Spec-Anchored | Auditability + traceability | Medium-high | Regulated work. Spec lives the whole lifecycle; every change requires an addendum. |
| L3 Spec-as-Source | Guarantee by construction | Aspirational in 2026 | Watch / not-yet. Tessl (closed beta) and CSDD (academic). |
Higher rigor is not better. It is more expensive, and only pays off when the project genuinely needs the promise.
| Context | Profile | Default path |
|---|---|---|
| A | Solo / small team, greenfield | Spec-Kit lean ± Superpowers HARD-GATE |
| B | 10+ team, regulated, compliance | MUSUBI + CSDD security overlay |
| C | Brownfield / legacy | OpenSpec + Shotgun CLI |
| D | Security-critical (fintech, healthcare, embedded) | CSDD + MUSUBI + OWASP Skill |
Ask questions one at a time. Don't batch. Reference the question tree in interview/questions.md but adapt the wording conversationally.
The single most-discriminating question is: "Will an auditor ever ask about REQ-to-Test traceability for this code?" Answer determines L1 vs L2 cleanly.
Second-most-discriminating: "Greenfield or brownfield?" Brownfield routes to OpenSpec almost regardless of other answers — once you've identified brownfield, do not ask Q3 or Q4 (they're pruned by interview/questions.md; the routing table's brownfield-any rule short-circuits everything else).
Third (greenfield only): "Solo / small team / 10+?" Solo + greenfield + no audit → L1-lean or L1-superpowers. Team 10+ + audit → L2.
When recommending Superpowers: note the HN consensus that "I stripped it back to ~30%" — it's opinionated; that's a feature for serious work, friction for a 20-minute fix.
When recommending Spec-Kit: note the measured ~10x agent-time overhead on the first cycle (33.5 min vs 8 min baseline). Worth it on real product work, painful on throwaways.
When recommending MUSUBI: note that 28 GitHub stars vs Superpowers' 166k is not a sign of MUSUBI being bad — it's a sign that most teams don't need its rigor. If an auditor will ask, the 28 stars are irrelevant.
When the user's context suggests L3 might matter in 18+ months (security-critical financial/healthcare): mention Tessl and CSDD as "watch, not deploy" — don't oversell them. Tessl is closed beta; CSDD is a paper with one empirical study.
When the user agrees to install (any of "okay, do it" / "set this up" / "scaffold it" / "let's go"):
Capture the answer letters from the conversation. You've been having a guided discussion — now condense it into the canonical interview tuple. Map your conversational understanding to interview/questions.md letter options (a/b/c/d). If you're unsure of any letter, ask the user one clarifying question before proceeding.
Run scripts/route.py with the captured tuple (see commands/init.md step 3 for the JSON shape) to get the methodologies + profile deterministically. Do not interpret the routing table yourself.
Produce a ready-to-paste handoff. Output a single fenced block the user can paste verbatim:
/mck-scaffold:init --decision={"version":1,"methodologies":[...],"profile":"...","stack":"...","project_name":"...","rationale":"<one paragraph>","interview_answers":{"q1":"...","q2":"...","q3":"...","q4":"...","q5":"...","q6":"...","q7":"..."}}
Required fields in the JSON: version (always 1), methodologies (from route.py), profile (from route.py). Strongly recommended fields: stack (from Q5 — without this the installer cannot drop stack strictness files), rationale (one paragraph for the audit log), interview_answers (the captured letters, for reproducibility).
This is JSON-on-one-line; the JSON content must match schema/scaffold-decision.schema.json. When the user pastes that command, commands/init.md step 1a recognizes the --decision= arg and skips the interview — your conversation is the interview.
If the rationale paragraph would contain quote characters that break one-line JSON encoding, keep the rationale short for the handoff and write the longer version into docs/decisions/METHODOLOGY.md post-install. Don't fight JSON escaping.
Tell the user what just happened. One short paragraph: "I'd recommend X + Y at profile Z because . Paste the command above to install. The installer is deterministic — same input always produces the same output."
The picker remains read-only — it does not write files. The handoff is text the user explicitly pastes. The slash command does the write.
Phase 2 complete. Conceptual frame, conversational guidance flow, and routing references are all functional. The interview executor (/mck-scaffold:init) consumes the same interview/questions.md and interview/routing.md files this skill references — they are the single source of truth for both the conversational and the deterministic paths.
npx claudepluginhub mckruz/mck-scaffold --plugin mck-scaffoldProvides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.