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spec-to-repo

Translate product specs (PRDs, user stories) into a ship-ready repo plan: ticket decomposition, branch strategy, and PR sequencing. Use when breaking a PRD into tickets or designing the branch/PR sequence.

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Works withJira

Run score Not tested

See how to install

Files included (7)

  • SKILL.md9.2 KB
  • references/branch-strategy-for-features.md6.4 KB
  • references/pr-discipline-and-conventions.md7.0 KB
  • references/spec-to-ticket-decomposition.md6.7 KB
  • scripts/branch_naming_validator.py5.0 KB
  • scripts/pr_scope_analyzer.py7.1 KB
  • scripts/prd_to_tickets_decomposer.py10.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Spec to Repo

A delivery-focused skill that bridges product spec to repository work. Where PRD-writing skills focus on what to build, this skill focuses on how to break it down for execution — the ticket decomposition, branch strategy, PR sequencing, and acceptance criteria that make a spec actually ship.

When to use this skill

  • Translating a PRD or feature brief into a sequence of tickets
  • Designing the branch + PR sequence for a multi-week feature
  • Auditing an existing ticket decomposition for risk (big tickets, hidden dependencies)
  • Defining definition-of-done that covers code, tests, docs, telemetry
  • Planning incremental shipping (feature flags, canaries, dark-launch)
  • Reviewing a decomposition before sprint planning to avoid mid-sprint surprises

Inputs the advisor expects

  • The PRD or spec document
  • Target ship window (1 sprint? 1 month? 1 quarter?)
  • Engineering team size + composition (FE, BE, ML, mobile)
  • Risk profile (greenfield vs production-impacting)
  • Feature-flag and rollout posture

Clarify First

Before generating the repo plan, settle the inputs below. When one is missing or vague and would change the result, ask about it; when it wouldn't, use a sensible default and say which one you used.

  • The PRD or spec: the user-facing capabilities to decompose (drives the epic→ticket tree).
  • Target ship window: one sprint, month, or quarter (drives ticket sizing and PR sequencing).
  • Team composition: FE, BE, ML, mobile (decides parallel paths and vertical-slice tickets).
  • Feature-flag and rollout posture: flagged/dark-launch vs direct ship (drives PR sequencing and definition-of-done).

Ask about the two or three inputs that matter most for this request, not the whole list. If the user wants a result straight away, produce it and state your assumptions at the top.

Workflows

Workflow 1 — Decompose a PRD into tickets

  1. Pull the PRD; identify the user-facing capabilities.
  2. Run prd_to_tickets_decomposer.py with the user stories + technical notes to surface a candidate ticket tree (epic → tickets → subtasks) with size estimates and dependencies.
  3. Manually review; tune for team-specific patterns.
python3 spec-to-repo/scripts/prd_to_tickets_decomposer.py \
  --input prd.json --format markdown

Workflow 2 — Validate the branch and PR plan

  1. Capture proposed branch + PR sequence.
  2. Run pr_scope_analyzer.py to flag oversized PRs, missing tests, missing telemetry, and risky merges.
  3. Adjust before opening PRs.
python3 spec-to-repo/scripts/pr_scope_analyzer.py \
  --input pr_plan.json --format markdown

Workflow 3 — Lint branch names against convention

  1. Capture branch list (e.g., git branch --list).
  2. Run branch_naming_validator.py to flag non-conformant names.
python3 spec-to-repo/scripts/branch_naming_validator.py \
  --input branches.txt --format markdown

Decision frameworks

Ticket sizing

SizeEffortDescription
XS< 0.5 dayTrivial; usually skip ticketing
S0.5–1 dayOne simple change
M1–3 daysSingle feature, well-scoped
L3–5 daysMulti-day work; should split if possible
XL> 5 daysAlways split — too big for confident estimate

A ticket that's L or XL almost always hides a missing decomposition. Push back on yourself.

The ticket tree

Epic — large product feature ("Notifications v2")
├── Story — user-facing capability ("As a user I can mute by channel")
│   ├── Ticket — one engineering work item (backend, frontend, infra)
│   │   └── Subtask — atomic step (optional)

Most orgs:

  • Epic ≈ PRD-sized scope
  • Story ≈ one user-facing slice
  • Ticket ≈ one PR (or pair of PRs: BE + FE)

The "vertical slice"

Best ticket: ships a small user-visible improvement end-to-end.

  • Backend change + frontend change + tests + telemetry + docs in one ship
  • Better than: BE-only ticket waiting for FE-only ticket waiting for QA

When you can't slice vertically (e.g., backend is weeks before frontend):

  • Use feature flags to ship behind a switch
  • Dark-launch backend to validate before frontend
  • Communicate the lag explicitly

PR sequencing

For a multi-PR feature:

  1. PR 1 — Infrastructure / scaffolding (no behavior change)
  2. PR 2 — Backend changes (behind flag; no frontend uses it)
  3. PR 3 — Frontend changes (behind flag; tests pass with flag on/off)
  4. PR 4 — Telemetry + analytics events
  5. PR 5 — Documentation + runbook
  6. PR 6 — Flag enablement (small change; reviewable cleanly)

Each PR < 400 lines if possible. Reviewability collapses above 400.

Definition of done

Per ticket:

  • Code: written, reviewed, merged
  • Tests: unit + integration as appropriate
  • Telemetry: events fired (and verified)
  • Docs: README / runbook / API doc updated as needed
  • Accessibility: meets the project bar
  • Feature flag: configured (if applicable)
  • Rollout plan: defined for non-flagged ships

Per epic:

  • All tickets complete
  • Feature behind flag in production for 1+ week (if risky)
  • Flag enabled for X% (canary), then ramped
  • Telemetry shows expected behavior
  • Customer-facing comms drafted (if applicable)

Common engagements

"Help me decompose this PRD"

  1. List user-facing capabilities (1-line each).
  2. For each, list the backend, frontend, infra, telemetry, docs work.
  3. Estimate; flag anything > 3 days for further breakdown.
  4. Sequence: scaffolding first, behavior next, flag enablement last.
  5. Identify cross-team dependencies; engage before sprint start.

"Our team is shipping huge PRs"

  1. Audit the last 10 PRs: median size, P95 size.
  2. Identify the patterns: monolithic services + flag-less work + slow review.
  3. Pilot: feature flags + ticket-first decomposition + PR size SLA.
  4. Track: median PR size + lead time week-over-week.

"Help me plan the rollout"

  1. Define a successful launch criterion (e.g., < 0.5% error rate at 50%).
  2. Identify the kill switch (feature flag or quick-revert).
  3. Plan ramps: 1% → 5% → 25% → 50% → 100% with bake time.
  4. Define rollback criteria + comms plan.
  5. Coordinate with on-call + support.

Anti-patterns to avoid

  • Decomposition as wishful thinking. "3-day estimate" with no break-down is a 2-week-actual.
  • Sequential ticket tree (everyone waits). Plan parallel paths.
  • Hidden dependencies on other teams. Surface them in decomposition.
  • No feature flag. Shippable in chunks but every change goes to all users immediately.
  • PRs > 1000 lines. Reviewability dies; bugs hide.
  • DoD that's just "code merged." Forgets tests, docs, telemetry.
  • Ticket = a day of work. Sometimes tickets are 30 minutes; sometimes 3 days.

Scope & Limitations

In Scope:

  • Decomposing a PRD, described as user capabilities, technical notes and team, into an epic, story and ticket tree with prd_to_tickets_decomposer.py, flagging oversized tickets and cross-team dependencies
  • Checking a planned PR sequence with pr_scope_analyzer.py for oversized PRs, missing tests, telemetry or docs, risky merges and ordering problems
  • Linting branch names against a configurable pattern with branch_naming_validator.py
  • Guidance on ticket sizing, vertical slices, PR sequencing, definition of done and staged rollout

Out of Scope:

  • Writing the PRD itself (see project-management/execution/create-prd/)
  • Creating tickets in Jira or Linear (see project-management/jira-expert/ and project-management/linear-expert/)
  • Feature flag platform design (see engineering/feature-flags-architect/)
  • Reviewing actual code changes (see engineering/pr-review-expert/)

Important Caveats:

  • The decomposer does not parse PRD prose. It works from a JSON of capabilities, and effort comes from the estimated_days the user enters.
  • The PR analyzer reads a plan with estimated line counts, not real diffs. The branch validator checks a list of names and does not touch the git repository.
  • Size limits such as splitting tickets over 3 days or keeping PRs under 400 lines are rules of thumb. Teams should tune them to their own history.

References

  • references/spec-to-ticket-decomposition.md — patterns for breaking specs into tickets
  • references/branch-strategy-for-features.md — branching, feature flags, dark-launch
  • references/pr-discipline-and-conventions.md — PR size, review, definition-of-done

Related skills

  • product-team/agile-product-owner — sprint planning, prioritization
  • engineering/feature-flags-architect — flag strategy
  • engineering/observability-designer — SLO / telemetry
  • c-level-advisor/vpe-advisor — broader delivery context
  • project-management/ skills — ticket / sprint management tooling

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