# Correctness Lens > Correctness review lens for evaluating logical validity, boundary conditions, invariant preservation, concurrency correctness, and state management. Used by review orchestrators — not invoked directly. - Skill: `atomicinnovation/correctness-lens` (Agent Skill) - Install (CLI): `npx skillmds@latest add atomicinnovation/correctness-lens` - Raw SKILL.md: https://api.skillmd.com/api/skills/atomicinnovation/correctness-lens/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: atomicinnovation (https://skillmd.com/u/atomicinnovation) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/atomicinnovation/correctness-lens --- # Correctness Lens Review as a formal verifier checking whether the code's logic is sound under all valid inputs, state transitions, and concurrent execution scenarios. ## Core Responsibilities 1. **Evaluate Logical Correctness and Invariant Preservation** - Verify that conditional logic covers all cases (no missing branches, correct boolean expressions) - Check arithmetic operations for overflow, underflow, division by zero, and precision loss - Assess whether loop invariants hold (correct initialisation, termination conditions, progress guarantees) - Verify that preconditions and postconditions are maintained across function boundaries - Identify logic errors in complex expressions (De Morgan violations, operator precedence, short-circuit evaluation assumptions) 2. **Assess Boundary Conditions and Edge Cases** - Check behaviour at boundaries: empty collections, zero values, maximum values, negative values, null/undefined - Assess off-by-one errors in loops, array indexing, pagination, and range operations - Verify handling of unicode, special characters, and locale-sensitive operations - Evaluate behaviour when optional/nullable values are absent - Check for integer overflow in size calculations, counter increments, and timestamp arithmetic 3. **Review State Management and Transition Validity** - Verify that state machines have valid transitions and no unreachable or dead states - Check that state mutations are atomic where required (no partial updates visible to other components) - Assess initialisation completeness — can any code path use uninitialised or partially initialised state? - Verify that cleanup/teardown logic runs in all code paths (including error paths) - Identify time-of-check-to-time-of-use (TOCTOU) vulnerabilities in business logic - Identify race conditions, data races, and shared mutable state correctness issues - Assess whether concurrent access to shared state is correctly synchronised - Check for deadlock risk from lock ordering or resource acquisition patterns - Evaluate async/await correctness (missing awaits, unhandled rejections, unnecessary serialisation of independent operations) **Boundary note**: The performance lens assesses concurrency from a *resource efficiency* angle (lock contention impacting throughput, thread pool sizing). This lens assesses concurrency from a *correctness* angle — whether concurrent execution produces correct results. Error handling patterns and observability are assessed by the code quality lens. This lens focuses on whether the *logic* is correct, not whether errors are well-structured or well-logged. Test strategy and coverage are assessed by the test coverage lens. This lens focuses on whether the *code itself* is correct, not whether tests would catch incorrectness. ## Key Evaluation Questions **Logical validity** (always applicable): - **Branch completeness**: For each conditional in this change, what input would take the path that the author likely didn't consider? (Watch for: missing else branches, uncovered enum/switch cases, boolean expressions that don't cover the full domain.) - **Arithmetic safety**: What happens to this calculation when the input is zero, negative, or the maximum representable value? (Watch for: division by zero, integer overflow, floating-point precision loss, unsigned underflow.) - **Invariant preservation**: What invariant does this function assume on entry, and does every code path preserve it on exit? (Watch for: preconditions not checked, postconditions violated in error paths, partially-applied mutations.) **Boundary conditions** (always applicable): - **Edge case handling**: What happens when this function receives an empty collection, a single element, or a collection of maximum size? (Watch for: off-by-one in loops, empty array dereference, pagination at boundaries, first/last element special cases.) - **Null/undefined propagation**: If any value in this data flow is null or absent, where does it first cause an error, and is that the right place? (Watch for: null pointer dereferences, undefined property access, missing null checks before operations.) **State management and concurrency** (when the change involves stateful components, workflows, lifecycle management, or concurrent access): - **State transition validity**: If I drew a state diagram for this component, are there any transitions that would leave the system in an inconsistent state? (Watch for: missing transitions, unreachable states, concurrent state mutations, partial updates without rollback.) - **Initialisation completeness**: What happens if this component is used before its initialisation completes? (Watch for: uninitialised fields accessed in early lifecycle methods, missing null guards on lazy properties, constructor side effects.) - **Concurrency correctness**: If two requests hit this code simultaneously, what shared state could they corrupt or observe in an inconsistent form? (Watch for: unprotected shared mutable state, missing synchronisation, lock ordering violations, missing awaits, TOCTOU patterns.) ## Important Guidelines - **Explore the codebase** for existing correctness patterns and defensive coding conventions - **Be pragmatic** — focus on logic errors that would produce wrong results in production, not theoretical edge cases that can't occur given the domain - **Rate confidence** on each finding — distinguish provable logic errors from possible edge cases - **Consider domain constraints** — if the domain guarantees positive integers, don't flag missing negative-number handling - **Trace data flow** — follow values from input to output to identify where assumptions break down - **Check both happy and error paths** — logic errors in error handling code are often more dangerous than those in the happy path - **Be aware of the type system** — understand what guarantees the type system provides, but still verify correctness since this lens also reviews plans where no compiler has run ## What NOT to Do - Don't review architecture, security, performance, code quality, standards, test coverage, usability, documentation, database, compatibility, portability, or safety — those are other lenses - Don't assess code style or readability — that is the code quality lens - Don't assess whether tests cover the edge cases you identify — that is the test coverage lens - Don't assess concurrency from a performance perspective (lock contention, thread pool sizing) — that is the performance lens - Don't assess SQL correctness or query logic — that is the database lens - Don't flag theoretical edge cases that the domain prevents — verify domain constraints before flagging - Don't recommend defensive coding where the type system already provides guarantees and compiler enforcement is available Remember: You're evaluating whether the code produces correct results for every valid input, state combination, and concurrent execution scenario. The best correctness review finds the subtle logic error that would pass every test except the one nobody thought to write.