Code Review After Completing Complex Software Development Tasks

Run a structured review over the changes in scope. Two modes:

• Reviewing work you just completed, or told to fix - review, then apply and verify the fixes.
• Asked only to review - stop at clear, actionable feedback and let the user decide what to act on. Don't start editing.

Workflow

1. Search the repo for every file documenting how code should be written. CODING_STANDARDS.md and CONTRIBUTING.md must be on the list when present. Pass the list to the sub-agents.
2. Spawn parallel sub-agents to critically review the changes, splitting the work by review axis (below) or by area of the codebase.
3. Compile their findings into a concise numbered list, each tagged critical/medium/low.
4. Verify every finding against the actual code before reporting or acting on it. Sub-agents report false positives, and acting on a phantom issue makes the code worse.

Applying Fixes

Fix mode only. If you were asked only to review, stop at step 4 and report your findings.

1. Fix the confirmed issues.
2. Re-run the project's lint/test/build pipeline.
3. Read each fix to confirm it resolves its finding and didn't break the original task or introduce a new problem. A green pipeline proves mechanical correctness only.
4. Stop after this single verification pass; don't recurse into a fresh full review.

If a finding is especially complex or keeps recurring, use the systematic-debugging skill to get to the root cause.

Review Axes

Direct sub-agents to evaluate the changes across these dimensions. The questions below are illustrative, not a fixed checklist. Apply the ones that fit and raise the concerns that actually matter for this codebase's language, domain, and conventions:

• Correctness - Does it do what the task required? Are edge cases (null, empty, boundary) and error paths handled, not just the happy path? Do the tests actually exercise the new behaviour?
• Readability - Are names and control flow clear to someone who didn't write this? Could it be simpler or shorter? Is each abstraction earning its complexity?
• Architecture - Does it follow existing patterns and module boundaries, or introduce a new one without justification? Is there duplication that should be shared? A new dependency the existing stack already covers?
• Security - Is untrusted input validated at boundaries? Any secrets in code or logs? Any injection (SQL, shell, path), missing authorisation checks, or external data used unsafely in logic or output?
• Performance - What's costly for this kind of code: algorithmic complexity, repeated work or allocations in hot paths, N+1 queries, unbounded fetches, missing pagination, synchronous behaviour or blocking work on the critical path?

Create checklists or TODOs for yourself (or the sub-agents) to ensure your coverage is thorough.

Smell baseline

On top of whatever the repo documents, the Readability and Architecture axes always carry this fixed set of Fowler code smells (Refactoring, ch.3). It applies even when a repo documents no standards of its own. Two rules bind it:

• The repo overrides. A documented repo standard always wins; where it endorses something the baseline would flag, suppress the smell.
• Always a judgement call. Each smell is a labelled heuristic ("possible Feature Envy"), never a hard violation. Skip anything tooling already enforces.

Pass this list to the sub-agents verbatim - they have no other access to it. Each smell reads what it is → how to fix; match it against the diff and name the smell in the finding.

• Mysterious Name - a function, variable, or type whose name doesn't reveal what it does or holds. → rename it; if no clear name comes, the design's murky.
• Duplicated Code - the same logic shape appears in more than one hunk or file in the change. → extract the shared shape, call it from both.
• Feature Envy - a method that reaches into another object's data more than its own. → move the method onto the data it envies.
• Data Clumps - the same few fields or params keep travelling together (a type wanting to be born). → bundle them into one type, pass that.
• Primitive Obsession - a primitive or string standing in for a domain concept that deserves its own type. → give the concept its own small type.
• Repeated Switches - the same switch/if-cascade on the same type recurs across the change. → replace with polymorphism, or one map both sites share.
• Shotgun Surgery - one logical change forces scattered edits across many files in the diff. → gather what changes together into one module.
• Divergent Change - one file or module is edited for several unrelated reasons. → split so each module changes for one reason.
• Speculative Generality - abstraction, parameters, or hooks added for needs the task doesn't have. → delete it; inline back until a real need shows.
• Message Chains - long a.b().c().d() navigation the caller shouldn't depend on. → hide the walk behind one method on the first object.
• Middle Man - a class or function that mostly just delegates onward. → cut it, call the real target direct.
• Refused Bequest - a subclass or implementer that ignores or overrides most of what it inherits. → drop the inheritance, use composition.

Calibration

• The bar is "does this improve the codebase," not "is this how I would have written it." Don't invent problems just to have something to report, and don't rewrite working code over style preference.
• Don't soften or rubber-stamp real problems either. State them plainly and quantify the impact where you can ("this N+1 adds ~50ms per row" beats "this might be slow").
• Passing tests are necessary, not sufficient. They don't catch architecture, security, or readability problems, so review those regardless.

Dead Code

Refactors leave orphans. After changing code, list anything now unused (replaced functions, components, constants) and ask before removing it, rather than deleting silently or leaving it to rot.

Sub-Agent Guidelines

Where appropriate use sub-agents to parallelise your work and reduce context bloat in the main conversation.

• Tell sub-agents to keep output concise, actionable, and focused on your changes, not minor style nitpicks.
• Give them only the context they can't infer from the code itself.
• Scope each agent to clear boundaries so they don't overlap or review unrelated code.

Reporting

The fixes, or the findings are the deliverable, so open with the (concise) outcome, not preamble or a description of your process.

• Review-only: the findings ordered by severity, each as file:line, the problem, and a concrete fix. If nothing substantive turned up, say so in a line.
• Fix mode: what you fixed, then what you didn't and why. List deferred or out-of-scope findings one line each so the user can decide, and note the pipeline result.

State real issues plainly and drop the hedging ("might want to consider", "could potentially"); tag anything optional as low and move on. Batch style nitpicks into a single note rather than scattering them. Don't close with a summary that restates the list. A short report flagging the few things that count beats a long one padded with the obvious.