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The implementation-plan skill produces the document that sits between your architecture and your first commit: the ordered build sequence. It takes your existing system architecture, technical specification, and project plan and sequences them into dependency-driven phases, each with an explicit Definition of Ready, Definition of Done, and a concrete verification step that proves the phase is complete rather than merely written. This is an always-core skill because most implementation failures are ordering failures — building UI before the API contract is stable, building features before the auth foundation exists, integrating a payment provider before the data model that records its results is finalised. The output is precise enough for a human team or an AI coding agent to execute phase by phase without stopping to ask what comes next.
Type: Workflow  ·  Estimated time: 2–4 hours  ·  Methodology: Dependency-driven phasing, vertical slices, three-point estimation  ·  Output file: 14-implementation-plan.md  ·  Inclusion: Always-core — every project

Best for

Sequencing a new project build

Turn architecture and requirements into an ordered build roadmap once the design phase is complete.

AI coding agent handoff

Produce a self-contained plan an AI agent can execute phase by phase without implicit context or ambiguous entry points.

Foundation vs. feature sequencing

Make explicit which foundational work — auth, data model, CI/CD — must exist before any feature work starts.

Phase gate definition

Define binary done criteria so partially-built features cannot be integrated prematurely.

What it produces

The skill outputs 14-implementation-plan.md, the final planning artefact before implementation begins:
  • Foundation layer table — components that must exist before feature work (data model, auth, CI/CD) and the specific reason each is foundational
  • Resource allocation matrix — skills, team members, phases they’re involved in, availability percentage, and bottleneck risks
  • Phased build sequence — one phase block per phase, each containing: what gets built, estimated duration, dependencies, Definition of Ready, Definition of Done, verification steps, code review approach, and rollback procedure
  • Dependency map and graph — Mermaid DAG showing every dependency edge and which workstreams can run in parallel
  • Integration checkpoints — explicit points where parallel workstreams must converge and be tested together before proceeding
  • High-uncertainty items and fallbacks — primary approach and fallback for every item with low-confidence estimates
  • Technical debt register — every shortcut taken during the build, with owner and target resolution date
  • Completion criteria — the observable, testable conditions that mean the full implementation is done and ready for the deployment-plan skill
  • Post-implementation handoff — codebase, documentation, runbook, known issues, and credentials handoff table

How to invoke it

Reference existing documents in your invocation: implementation-plan marketplace platform — architecture doc exists (Next.js / Node / Postgres / Stripe Connect) and the technical spec is complete. The skill reads those documents before asking any questions, which reduces the interview to at most 2–3 targeted clarifications.

Example scenarios

Key concepts

Foundation before features

Certain components block almost everything else and must be built first — regardless of what feels most important to stakeholders. The skill identifies these explicitly in a Foundation Layer table:
  • Data model / core schema — nearly everything reads or writes through it; build it first so every subsequent layer has a stable base
  • Authentication and authorisation — most features require a user context; building features before auth means retroactively adding auth to every endpoint
  • CI/CD and environment setup — nothing can be verified or deployed without it; a green CI pipeline on day one saves days of integration pain later
  • Core API scaffolding — shared error handling, middleware, request/response conventions that every feature endpoint inherits
Sequencing feature work before the foundation layer is the most common cause of implementation rework. The skill will always place foundation components in Phase 0, regardless of stakeholder pressure to start with a visible feature.

Dependency-driven phases, not calendar phases

A phase boundary must represent a real technical dependency — “Phase 2 cannot start until the data model in Phase 1 is migrated and integration-tested” — not an arbitrary time slice. If two workstreams have no technical dependency on each other, they belong in the same phase for parallel execution. The skill produces a Mermaid dependency graph alongside the phase descriptions so the ordering rationale is always visible:

Definition of Ready and Definition of Done

Every phase has two explicit criteria:
  • Definition of Ready — what must be true before work on this phase can begin (e.g., “API contract for Phase 2 is frozen, reviewed, and documented”)
  • Definition of Done — what must be true before moving to the next phase (e.g., “all Phase 1 endpoints pass integration tests against a seeded database”)
Vague phase boundaries — “mostly done,” “code is written” — are the most common cause of premature integration and cascading bugs. The skill enforces that every DoD criterion is binary and verifiable.

Vertical slices over horizontal layers

The skill prefers implementing a thin, fully-working slice through all system layers — one complete user flow: UI → API → DB → response — over building an entire layer (all of the database, then all of the API, then all of the UI) before anything is testable end-to-end. Vertical slices surface integration problems early, when they’re cheap to fix.

Effort estimation methodology

For each phase the skill applies one of three estimation approaches, tagged with a confidence level: Every estimate is tagged with a confidence level (High / Medium / Low). Low-confidence items require a spike or PoC before the phase starts.

Designed for agent execution

Because an AI coding agent may execute the plan directly, each phase is written as a self-contained unit with no implicit context:
  1. What already exists at the start of this phase
  2. What to build — specific components, not vague goals
  3. What “done” looks like — binary, verifiable, not subjective
  4. What to verify before reporting the phase complete

Technical debt tracking

The plan includes a running debt register. Every shortcut is tracked with:
  • What — the shortcut taken
  • Why — the pressure that forced it
  • Owner — who is responsible for resolving it
  • Target resolution — the phase by which it must be addressed
  • Cost of leaving unresolved — what breaks if the debt is never paid
A debt that is not documented does not exist as far as future engineers are concerned — until it surfaces as a production incident.

Interview process

The skill reads all prior .engineering-docs/ documents to pre-load known context (tech stack, scope, timeline, team). It then asks a maximum of 2–3 targeted questions via tool calls, not inline chat:

Output structure

Phase block format

Every phase in Section 4 uses this consistent template:

Handoff

Reads from: Feeds into:

Quality gate

Before marking the document final, the agent verifies five gates:
1

Every phase has DoR, DoD, and a concrete verification step

Not just a deliverables list. The verification step must be something an engineer or agent can execute and get a binary pass/fail result from.
2

Build order is driven by technical dependency

The sequencing rationale is always “B depends on A”, never “A looks more exciting” or “stakeholders want A first”. The dependency graph makes this explicit and auditable.
3

Foundation layer is Phase 0 and blocks all feature phases

Data model, auth, and CI/CD are always Phase 0. No feature phase has a “Depends on” that precedes them.
4

Independent workstreams are grouped for parallel execution

Two workstreams with no dependency on each other belong in the same phase. Splitting independent work into sequential phases adds schedule risk without reducing technical risk.
5

Integration checkpoints exist wherever parallel workstreams converge

Every place in the dependency graph where two or more parallel streams must merge has a named integration checkpoint with a verification step.