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You’ll run the first three spec-kit commands — /speckit.specify, /speckit.clarify, and /speckit.plan — to plan a realistic Production Accounting dashboard. You will end with a spec.md that captures your intent, a Clarifications section that resolves every ambiguity, and a plan.md your agent can act on. The last two commands, /speckit.tasks and /speckit.implement, are not covered. See Spec-driven development for the full flow. The spec you write in this walkthrough drives toward a finished app like the one below — a KPI bar and a Balance Reconciliation Tree with quality badges, running as a Flows app in development mode:
Production Accounting dashboard showing a KPI bar with Gross Production, Net Export, Imbalance, and Closure percent, above a Balance Reconciliation Tree of flow components with volume, source tag, and Verified, Estimated, or Manual quality badges.

The Production Accounting dashboard this walkthrough plans toward: a KPI bar and a quality-flagged Balance Reconciliation Tree.

Prerequisites

You need a Flows custom app with spec-kit enabled. If you don’t have one yet:
  1. Follow Getting started with Flows custom apps to create your app.
  2. When prompted Enable spec-driven development, choose Yes, then choose Yes again when prompted to enable spec-kit.
Once your app is open in Cursor or Claude Code, the spec-kit slash commands are available in .cursor/commands/ and .claude/commands/.

Step 1: Specify your feature

Start with a short description of the app, then let spec-kit expand it into a structured spec.
1

Run /speckit.specify with a one-liner description

Give spec-kit a short description of what you want to build. You don’t need to fill in every detail — the template will prompt you for the rest:
The command creates specs/001-production-accounting/spec.md pre-populated with the spec-kit template.
Keep the one-liner focused on the surface and the key behavior. You will fill in edge cases and constraints during /speckit.clarify.
2

Review and complete spec.md

Open specs/001-production-accounting/spec.md. The template has generated User Stories, acceptance scenarios, and placeholder Functional Requirements from your description. An example of the populated output (trimmed):
Fill in any sections the template left as placeholders, especially Data Models & CDF Integration and Success Criteria.
Complete these sections before running /speckit.plan. The plan command depends on them to generate an accurate implementation plan.

Step 2: Clarify ambiguities

Resolve the open questions in the spec before you plan, so the implementation rests on explicit decisions.
1

Run /speckit.clarify

The command reads your spec and runs an internal coverage scan across categories: functional scope, data model, integration, and edge cases. It then surfaces up to five questions that would block planning if left unanswered.
2

Answer each question

For each question, your agent presents a recommendation and an options table. The following example is from the Production Accounting spec:
Reply with the option letter or accept the recommendation. Your agent writes the answer directly back into the spec.md Clarifications section:
3

Review the clarification-complete report

When all questions are resolved, your agent outputs a summary:
At this point, spec.md is complete and ready for planning. Commit it before moving on so the decisions are in git history.

Step 3: Generate the implementation plan

Turn the clarified spec into a concrete, reviewable plan your agent can act on.
1

Run /speckit.plan

The command reads the clarified spec and generates specs/001-production-accounting/plan.md. For the Production Accounting dashboard, the output included the following sections (trimmed):
The plan also includes a Constitution Check — a table verifying that the proposed implementation satisfies each rule in AGENTS.md, such as using @cognite/aura/components before raw HTML, following the ViewModel pattern, and writing tests for every hook and component that contains logic.
2

Review and commit plan.md

Review plan.md with your team before starting implementation. If anything looks off, update spec.md and re-run /speckit.plan. Commit both files together.
You don’t have to use /speckit.plan to generate this file. You can write plan.md yourself or produce it through your agent’s in-session plan mode — as long as the steps are numbered and ordered clearly enough for /speckit.tasks to split into a task list.

Troubleshooting

The slash commands ship only when you enable spec-kit during apps create. Confirm that .cursor/commands/ and .claude/commands/ contain speckit.* files. If they’re missing, you created the app without spec-kit — there is no retrofit command, so re-scaffold the app and choose Yes at the spec-kit prompt, or manually copy the spec-kit files into your app. See Spec-driven development.
The command asks only about ambiguities it finds, up to five. If your spec.md is already specific, it may ask fewer questions or none. Review the coverage report it prints. If a category you care about is marked resolved but you disagree, add detail to spec.md and run /speckit.clarify again.
The plan is only as good as the clarified spec. Update spec.md — especially the Functional Requirements and the Data Models & CDF Integration section — then re-run /speckit.plan. Running the command again regenerates the plan from the current spec.

What’s next

You’ve run specify, clarify, and plan on a real feature and committed a spec.md and plan.md to your repository. Your agent now has the context it needs to implement the Production Accounting dashboard. The next two spec-kit commands decompose the plan into executable tasks and run them in order:
  • /speckit.tasks — writes an ordered tasks.md where each task maps back to a functional requirement.
  • /speckit.implement — runs the tasks in sequence, stopping at each one to confirm before continuing.
See Spec-driven development for how these commands work and how they fit into the full flow.
Last modified on June 10, 2026