Dec 14, 2025·6 min
Claude Code task scoping: from vague requests to commits
Learn Claude Code task scoping to turn messy feature requests into clear acceptance criteria, a minimal UI/API plan, and a few small commits.
Learn Claude Code task scoping to turn messy feature requests into clear acceptance criteria, a minimal UI/API plan, and a few small commits.
A vague request sounds harmless: “Add a better search,” “Make onboarding smoother,” “Users need notifications.” In real teams it often arrives as a one-line chat message, a screenshot with arrows, or a half-remembered customer call. Everyone agrees, but everyone pictures something different.
The cost shows up later. When scope is unclear, people build on guesses. The first demo turns into another round of clarification: “That’s not what I meant.” Work gets redone, and the change quietly grows. Design tweaks trigger code changes, which trigger more testing. Reviews slow down because a fuzzy change is hard to verify. If nobody can define what “correct” looks like, reviewers end up debating behavior instead of checking quality.
You can usually spot a vague task early:
A well-scoped task gives the team a finish line: clear acceptance criteria, a minimal UI and API plan, and explicit boundaries around what’s not included. That’s the difference between “improve search” and a small change that’s easy to build and review.
One practical habit: separate “definition of done” from “nice-to-have.” “Done” is a short list of checks you can run (for example: “Search returns results by title, shows ‘No results’ when empty, and keeps the query in the URL”). “Nice-to-have” is everything that can wait (synonyms, ranking tweaks, highlighting, analytics). Labeling those up front prevents accidental scope growth.
Vague requests often start as proposed fixes: “Add a button,” “Switch to a new flow,” “Use a different model.” Pause and translate the suggestion into an outcome first.
A simple format helps: “As a [user], I want to [do something], so I can [reach a goal].” Keep it plain. If you can’t say it in one breath, it’s still too fuzzy.
Next, describe what changes for the user when it’s done. Focus on visible behavior, not implementation details. For example: “After I submit the form, I see a confirmation and can find the new record in the list.” That creates a clear finish line and makes it harder for “just one more tweak” to sneak in.
Also write down what stays the same. Non-goals protect your scope. If the request is “improve onboarding,” a non-goal might be “no dashboard redesign” or “no pricing-tier logic changes.”
Finally, pick one primary path to support first: the single end-to-end slice that proves the feature works.
Example: instead of “add snapshots everywhere,” write: “As a project owner, I can restore the latest snapshot of my app, so I can undo a bad change.” Non-goals: “no bulk restore, no UI redesign.”
A vague request is rarely missing effort. It’s missing decisions.
Start with constraints that quietly change scope. Deadlines matter, but so do access rules and compliance needs. If you’re building on a platform with tiers and roles, decide early who gets the feature and under what plan.
Then ask for one concrete example. A screenshot, a competitor behavior, or a prior ticket reveals what “better” actually means. If the requester has none, ask them to replay the last time they felt the pain: what screen were they on, what did they click, what did they expect?
Edge cases are where scope explodes, so name the big ones early: empty data, validation errors, slow or failed network calls, and what “undo” really means.
Finally, decide how you’ll verify success. Without a testable outcome, the task turns into opinions.
These five questions usually remove most of the ambiguity:
Example: “Add custom domains for clients” gets clearer once you decide which tier it belongs to, who can set it up, whether hosting location matters for compliance, what error shows for invalid DNS, and what “done” means (domain verified, HTTPS active, and a safe rollback plan).
Messy requests mix goals, guesses, and half-remembered edge cases. The job is to turn that into statements anyone can test without reading your mind. The same criteria should guide design, coding, review, and QA.
A simple pattern keeps it clear. You can use Given/When/Then, or short bullets that mean the same thing.
Write each criterion as a single test someone could run:
Now apply it. Suppose the note says: “Make snapshots easier. I want to roll back if the last change breaks things.” Turn it into testable statements:
If QA can run these checks and reviewers can verify them in the UI and logs, you’re ready to plan the UI and API work and split it into small commits.
A minimal UI plan is a promise: the smallest visible change that proves the feature works.
Start by naming which screens will change and what a person will notice in 10 seconds. If the request says “make it easier” or “clean it up,” translate that into one concrete change you can point to.
Write it as a small map, not a redesign. For example: “Orders page: add a filter bar above the table,” or “Settings: add a new toggle under Notifications.” If you can’t name the screen and the exact element that changes, the scope is still unclear.
Most UI changes need a few predictable states. Spell out only the ones that apply:
UI copy is part of scope. Capture labels and messages that must be approved: button text, field labels, helper text, and error messages. If wording is still open, mark it as placeholder copy and note who will confirm it.
Keep a small “not now” note for anything that isn’t required to use the feature (responsive polish, advanced sorting, animations, new icons).
A scoped task needs a small, clear contract between UI, backend, and data. The goal isn’t to design the entire system. It’s to define the smallest set of requests and fields that prove the feature works.
Start by listing the data you need and where it comes from: existing fields you can read, new fields you must store, and values you can compute. If you can’t name a source for each field, you don’t have a plan yet.
Keep the API surface small. For many features, one read and one write is enough:
GET /items/{id} returns the state needed to render the screenPOST /items/{id}/update accepts only what the user can change and returns the updated stateWrite inputs and outputs as plain objects, not paragraphs. Include required vs optional fields, and what happens on common errors (not found, validation failed).
Do a quick auth pass before touching the database. Decide who can read and who can write, and state the rule in one sentence (for example: “any signed-in user can read, only admins can write”). Skipping this often leads to rework.
Finally, decide what must be stored and what can be computed. A simple rule: store facts, compute views.
Claude Code works best when you give it a clear target and a tight box. Start by pasting the messy request and any constraints (deadline, users affected, data rules). Then ask for a scoped output that includes:
After it replies, read it like a reviewer. If you see phrases like “improve performance” or “make it cleaner,” ask for measurable wording.
Request: “Add a way to pause a subscription.”
A scoped version might say: “User can pause for 1 to 3 months; next billing date updates; admin can see pause status,” and out of scope: “No proration changes.”
From there, the commit plan becomes practical: one commit for DB and API shape, one for UI controls, one for validation and error states, one for end-to-end tests.
Big changes hide bugs. Small commits make reviews faster, make rollbacks safer, and help you notice when you drift away from the acceptance criteria.
A useful rule: each commit should unlock one new behavior, and include a quick way to prove it works.
A common sequence looks like this:
Keep each commit focused. Avoid “while I was here” refactors. Keep the app working end to end, even if the UI is basic. Don’t bundle migrations, behavior, and UI into one commit unless you have a strong reason.
A stakeholder says: “Can we add Export reports?” It hides a lot of choices: which report, which format, who can export, and how delivery works.
Ask only the questions that change the design:
Assume the answers are: “Sales Summary report, CSV only, manager role, direct download, last 90 days max.” Now the v1 acceptance criteria becomes concrete: managers can click Export on the Sales Summary page; the CSV matches the on-screen table columns; the export respects current filters; exporting more than 90 days shows a clear error; the download completes within 30 seconds for up to 50k rows.
Minimal UI plan: one Export button near table actions, a loading state while generating, and an error message that tells the user how to fix the issue (like “Choose 90 days or less”).
Minimal API plan: one endpoint that takes filters and returns a generated CSV as a file response, reusing the same query as the table while enforcing the 90-day rule server-side.
Then ship it in a few tight commits: first the endpoint for a fixed happy path, then UI wiring, then validation and user-facing errors, then tests and documentation.
Requests like “add team roles” often hide rules about inviting, editing, and what happens to existing users. If you catch yourself guessing, write the assumption down and turn it into a question or an explicit rule.
Teams lose days when one task includes both “make it work” and “make it pretty.” Keep the first task focused on behavior and data. Put styling, animations, and spacing into a follow-up task unless they’re required to use the feature.
Edge cases matter, but not all of them need to be solved immediately. Handle the few that can break trust (double submits, conflicting edits) and defer the rest with clear notes.
If you don’t write them down, you’ll miss them. Include at least one unhappy path and at least one permission rule in your acceptance criteria.
Avoid “fast” or “intuitive” unless you attach a number or a concrete check. Replace them with something you can prove in review.
Pin the task down so a teammate can review and test without mind-reading:
Example: “Add saved searches” becomes “Users can save a filter and reapply it later,” with non-goals like “no sharing” and “no sorting changes.”
Once you have a scoped task, protect it. Before coding, do a quick sanity review with the people who asked for the change:
Then store the criteria where the work happens: in the ticket, in the PR description, and anywhere your team actually looks.
If you’re building in Koder.ai (koder.ai), it helps to lock the plan first and then generate code from it. Planning Mode is a good fit for that workflow, and snapshots and rollback can keep experiments safe when you need to try an approach and back it out.
When new ideas pop up mid-build, keep scope stable: write them into a follow-up list, pause to re-scope if they change the acceptance criteria, and keep commits tied to one criterion at a time.
Start by writing the outcome in one sentence (what the user can do when it’s done), then add 3–7 acceptance criteria that a tester can verify.
If you can’t describe the “correct” behavior without debating it, the task is still vague.
Use this quick format:
Then add one concrete example of the expected behavior. If you can’t give an example, replay the last time the problem happened and write what the user clicked and expected to see.
Write a short “Definition of done” list first (the checks that must pass), then a separate “Nice-to-have” list.
Default rule: if it’s not needed to prove the feature works end-to-end, it goes into nice-to-have.
Ask the few questions that change scope:
These force the missing decisions into the open.
Treat edge cases as scope items, not surprises. For v1, cover the ones that break trust:
Anything else can be explicitly deferred as out-of-scope notes.
Use testable statements anyone can run without guessing:
Include at least one failure case and one permission rule. If a criterion can’t be tested, rewrite it until it can.
Name the exact screens and the one visible change per screen.
Also list the required UI states:
Keep copy (button text, errors) in scope too, even if it’s placeholder text.
Keep the contract small: usually one read and one write is enough for v1.
Define:
Store facts; compute views when possible.
Ask for a boxed deliverable:
Then re-prompt any vague wording like “make it cleaner” into measurable behavior.
Default sequence:
Rule of thumb: one commit = one new user-visible behavior + a quick way to prove it works. Avoid bundling “while I’m here” refactors into the feature commits.