Wio

WIO

WIO is one testing workflow skill with five command modes:

• scan: find the highest-value test candidates for a codebase, change, or scope.
• test: write one focused high-value test for a selected behavior, code path, or regression risk.
• workload: generate a realistic, adversarial workload that adds a new failure surface, oracle, sequence, or coverage dimension with controlled variance, replay, and correctness invariants.
• review: review a newly written or existing test for customer value, developer value, signal quality, and maintainability.
• doctor: diagnose test-suite health problems in a codebase or scope.

Commands are accessed through $wio:

Use references/index.md to route from code evidence and candidate failure modes to the right strategy references.

Reference Loading

Do not pick a test strategy from memory or from the nearest existing test alone. First inspect the target code, public behavior, existing tests, fixtures, and test commands. Then identify candidate behaviors or workloads and their likely failure mechanisms. Only after candidates exist, load the references needed to choose the strategy.

For every selected candidate, load at least one strategy reference that matches the failure mechanism before recommending or writing a test:

• Load Risk-Based Testing when priorities, customer impact, security/business risk, or limited test capacity decide what comes first.
• Load User Behavior Testing when the behavior is a user journey, product workflow, API consumer flow, or operator task.
• Load Test Level Selection before choosing unit, component, integration, contract, E2E, workload, synthetic, or monitoring coverage.
• Load Test Oracles And Assertions before writing or reviewing assertions, invariants, snapshots, workload checks, or any test whose failure signal is unclear.
• Load Test Data And Fixtures when state setup, seeds, factories, cleanup, permissions, or data realism affect signal.
• Load Mocking And Test Doubles when a mock, fake, stub, emulator, or real dependency decision could change what risk is preserved.
• Load Test Feedback Loops when choosing local, PR CI, nightly, release, canary, synthetic, or production-monitoring placement.
• Load specialized references only when the fault mechanism calls for them: property-based testing for broad deterministic input spaces, fuzzing for parsers/untrusted input, mutation testing for weak assertions, performance testing for latency/saturation, resilience testing for dependency failure, security testing for abuse or tenant/auth risk, static analysis for code/config-shape defects, and regression selection when the full suite is too slow.

For commands and repo signals in a topic, load the sibling tools.md after the matching overview.md shows that topic is relevant. State which reference files informed the chosen strategy.

Command Selection

Use scan when the user asks what to test next, where coverage would matter, how to prioritize testing work, or which tests would reduce user, production, support, or team risk.

Use test when the user asks to add a test, improve a specific test, cover a bug, or validate a change with a meaningful automated test.

Use workload when the user asks for a realistic user-session workload, scenario generator, traffic model, load/performance scenario, browser journey mix, synthetic user flow, or varied workload that still preserves a stable task goal.

If the user asks to generate a workload, treat existing workloads as evidence and reusable infrastructure, not as the deliverable. A generated workload must add at least one new failure surface, adversarial class, oracle/invariant, state model, dependency fault, user/session path, or coverage dimension. A wrapper, runner, seed sweep, parameter expansion, or documentation-only change around an existing workload is not a generated workload unless the user explicitly asked for a runner or the wrapper adds a new oracle or adversarial model.

Use review when the user asks whether a test is worth keeping, asks for test review, or after $wio test writes or changes a test.

Use doctor when the user asks to audit tests, review suite quality, find flaky or low-value tests, inspect CI test health, or explain why a test suite is slow, noisy, or low-signal.

If the user explicitly names a WIO command, follow that mode. If the command is omitted, infer the mode from the request. If no command or target is provided, show the command table and ask what they want to do. If multiple modes apply, start with scan before test or workload, and use doctor only for existing suite health.

Shared Rules

• Protect meaningful behavior, not coverage numbers.
• Ask what could go wrong before asking what already broke; use that answer to choose tests while the design is still cheap to change.
• Establish product, user, production, support, debugging, review, or release risk before recommending or writing tests.
• Prefer targets where bugs usually occur: boundaries, permissions, state transitions, persistence, external dependencies, concurrency/time, validation/parsing, migrations, configuration, caching, retries/idempotency, UI workflow joins, and recent churn.
• A test is valuable only if it would catch a meaningful regression, save developer time, improve release confidence, or expose a real operational/customer failure mode.
• Before keeping a test or workload, name at least one plausible bug it would catch and the assertion or invariant that would fail.
• Prefer assertions and invariants that encode the mental model of the behavior, including valid cases, invalid cases, and boundary transitions between them.
• Prefer repo-native frameworks, helpers, fixtures, commands, and naming.
• Choose the narrowest test level that preserves the real failure mechanism.
• Read code and tests before choosing strategy; load targeted references after candidate failure modes are known.
• State evidence inspected, commands run, commands not run, and residual risk.
• Mark low-value tests REDO or REMOVE, not KEEP.

Gotchas

• Do not write or keep tests just to increase coverage. Covered code with weak assertions is false confidence.
• Do not mock away the boundary, state, permission, timing, data, or dependency behavior that creates the real risk.
• Do not accept broad snapshots unless the reviewed snapshot is the protected contract and the update path is disciplined.
• Do not use a full-suite command when a smaller command validates the changed behavior with the same signal.
• Do not weaken assertions to fix flakes. First look for nondeterminism, shared state, timing, retries, order dependence, or external services.
• Do not treat green CI as proof the test is valuable. The question is whether the test would fail for the meaningful regression.
• Do not accept tests or workloads that only prove completion, truthiness, object existence, status 200, broad snapshot equality, or mock call counts unless that weak signal is explicitly the protected contract.
• Do not present a thin wrapper around an existing workload as $wio workload generate. If the change only reruns, parameterizes, documents, or sweeps an existing workload, call it a runner and explain the missing new failure surface.
• Do not let subagents write tests or make the final value decision; the main agent owns edits and the final KEEP, REDO, or REMOVE.

Available Scripts

• scripts/test-review-reminder.py: hook helper that reminds the active agent to validate and apply $wio review after test files change.
• scripts/check-wio-report.py: optional checker for saved markdown reports. Use python3 scripts/check-wio-report.py review report.md when a WIO output is written to a file and you need a quick structure check.

Subagent Workflow

When the host supports subagents or parallel agents and user/host policy permits them, use the WIO subagent specs from the official host locations to improve quality without duplicating guidance:

• wio-candidate-scout: read-only discovery of high-value test candidates and real risk.
• wio-strategy-critic: read-only challenge of the chosen test level, oracle, doubles, fixtures, and validation loop before implementation.
• wio-test-reviewer: post-implementation review that returns KEEP, REDO, or REMOVE.

Subagents must inspect targeted code and tests before loading targeted WIO references. They return findings to the main agent; they do not write reports or copy reference content. Claude plugin subagents live in plugins/wio/agents/; Claude project subagents can live in .claude/agents/; Codex custom agents live in .codex/agents/. Installing WIO with skills add does not create those runtime files.

For $wio test, use this sequence:

1. Inspect the repo and target code: public behavior, changed paths, existing tests, fixtures, commands, dependencies, state, side effects, and boundaries.
2. Discover valuable candidates from behavior, risk, bug-prone areas, existing coverage gaps, and code evidence. Use wio-candidate-scout if available.
3. Load the references that match the selected candidate's failure mechanism, then pick the strategy: test level, oracle, fixture/data setup, doubles, adversarial edge coverage, and validation command.
4. Use wio-strategy-critic to challenge the proposed strategy before editing when available.
5. Write one focused test in the main agent, using repo-native patterns.
6. Validate with the smallest relevant command.
7. Review the written test. Use wio-test-reviewer if available.
8. Keep the test only if review returns KEEP; otherwise revise (REDO) or remove (REMOVE).

If subagents are unavailable, perform the same stages in the main agent and explicitly label the review stage.

scan

Find the best parts to test next, the right strategy for each, and the ROI of testing them. This mode is read-only: inspect the repo and existing tests before loading strategy references; do not edit files.

Start with code evidence: inspect product surfaces, target implementation, existing tests, fixtures, and commands. Then use Behavior To Test Map to organize candidates, Risk-Based Testing for ranking tradeoffs, and Test Level Selection only after candidates exist.

Workflow:

1. Establish product/customer context from repo evidence.
2. Inventory existing test frameworks, commands, fixtures, CI, and test layers.
3. Inspect target implementation and nearby tests before choosing a strategy.
4. Map high-value behavior before low-level helpers.
5. Identify bug-prone areas in the scope.
6. Load the references that match each candidate's failure mechanism, then choose the narrowest strategy that preserves the real user or production risk.
7. Rank candidates by impact, likelihood, confidence gap, and cost.

Output template:

## Scope And Evidence
[target, files/commands inspected, tests/CI found]

## Ranked Candidates
1. [behavior] - impact: [why it matters], risk: [fault mechanism], references: [files used], strategy: [level/tool], cost: [small/medium/large]

## Best Next Test
[first investment and why it beats the alternatives]

## Avoid
[coverage-padding or low-signal tests to skip]

## Open Questions
[only questions that would materially change the ranking]

test

Write tests only when they protect meaningful behavior. A useful test reduces future user errors, production incidents, support work, debugging time, review time, or release risk. Do not jump straight to implementation or strategy selection.

Start with code evidence: inspect the target behavior, implementation, existing tests, fixtures, and commands. After selecting a candidate, load Test Level Selection before choosing the test layer and Test Oracles And Assertions before writing assertions. Add data, doubles, feedback, or specialized references when those decisions affect signal.

Workflow:

1. Inspect code, public behavior, existing tests, fixtures, CI, and test commands in the target scope.
2. Discover the highest-value candidate in scope from product risk, bug-prone areas, code shape, existing coverage gaps, and user/developer impact.
3. Load the right strategy references for that candidate's failure mechanism.
4. Pick the strategy from code evidence plus references: test level, oracle, data/fixture setup, doubles, specialized approach, and feedback loop.
5. State the protected behavior, plausible regression it catches, assertion or invariant that would fail, why it matters, references used, and validation command before editing.
6. Write one focused test using repo-native style and existing helpers.
7. Validate with the smallest relevant command. If it is unsafe or unclear, state that instead of guessing.
8. Review the test for value, signal, maintainability, and developer flow impact.
9. Apply the value gate before finalizing: KEEP, REDO, or REMOVE.

Output template:

## Candidate
[behavior/failure mode chosen and why it beat alternatives]

## Strategy
[test level, oracle, data/fixtures, doubles, feedback loop, references used, and why this preserves the real risk]

## Changes
[files changed and concise implementation summary]

## Validation
[command run and result, or why it was not run]

## Review
Verdict: KEEP | REDO | REMOVE
Protected behavior: [...]
Value: [...]
Signal strengths: [...]
False-confidence risks: [...]
Falsification check: [plausible bug and assertion/invariant that would fail]

## Remaining Risk
[what this test does not cover]

workload

Generate workloads that exercise meaningful user sessions, not one-off happy-path tests or wrappers around existing runners. A workload should cover important tasks a real user, API client, operator, or background process performs during a session, with adversarial but realistic misuse and controlled variance that changes data, ordering, scale, timing, or optional branches while preserving the same core task.

Start with code evidence: inspect the user/session entry points, implementation, existing tests, fixtures, commands, and workload/E2E tooling. Existing workloads should reveal gaps, not become the default implementation. After identifying the actor, goal, bug-prone interactions, and existing workload coverage, load Workload Modeling and Test Oracles And Assertions. Add performance, resilience, security, user-behavior, property-based, fuzzing, or data references only when the workload's risk depends on those dimensions.

Originality gate: before editing, state what existing workloads already cover and what the new workload adds. The new workload must introduce at least one of: a new failure surface, adversarial class, oracle/invariant, state model, dependency fault, user/session path, data shape, timing/order dimension, or replay artifact. If the best next step is only a wrapper, runner, seed sweep, or parameter expansion, say that plainly and do not call it a generated workload unless the user asked for that.

Workflow:

1. Inspect user/session entry points, implementation, existing tests, fixtures, commands, and workload/E2E tooling.
2. Inventory existing workloads and summarize their actor, failure surface, oracle/invariants, variance, and replay behavior.
3. Identify the user/session goal and the bug-prone interactions the new workload should expose.
4. State the coverage gap: what existing workloads miss and why that gap matters.
5. Load the references that match the workload's failure mechanism.
6. Choose workload type: browser journey, API scenario, CLI/session script, background-job flow, load profile, synthetic monitor, or property/stateful sequence.
7. Define stable invariants and assertions for correctness, not only completion, and decide which checks run after every step, at terminal state, or eventually.
8. Add adversarial classes deliberately: invalid transitions, duplicate/replayed actions, stale state, permission/tenant edges, malformed-but-valid data, boundary sizes, dependency faults, timing/order changes, partial failure or recovery, and explicit error-handling paths.
9. Add controlled variance with seeds, parameter ranges, optional branches, data shape changes, and recorded replay details.
10. Implement with repo-native libraries, fixtures, helpers, or workload tooling when useful, but do not reuse an existing workload unchanged as the generated workload.
11. Validate with the smallest safe command and report seed, coverage of interactions, limits, and residual risk.

Output template:

## Workload
Actor: [...]
Goal: [...]
Shape: [browser/API/CLI/job/load/synthetic/stateful]
References used: [...]

## Existing Coverage
Existing workloads found: [...]
What they cover: [...]
Gap this workload fills: [...]
Why this is not only a wrapper/runner/seed sweep: [...]

## Coverage
Interactions: [...]
Bug-prone areas: [...]
New failure surface/adversarial class/oracle: [...]
Invariants/assertions: [...]

## Adversarial Model
Misuse paths: [...]
Invalid transitions: [...]
Boundary inputs: [...]
Duplicate/replayed actions: [...]
Permission/tenant edges: [...]
Dependency/time/concurrency faults: [...]

## Variance And Replay
Seed: [...]
Variable inputs/branches/timing/scale: [...]
Replay command or notes: [...]

## Implementation And Validation
Tooling: [...]
Files changed: [...]
Command/result: [...]

## Falsification Check
Plausible bug caught: [...]
Assertion/invariant that fails: [...]
Manual mutation or fault tried, if any: [...]

## Limits
[environment, data, dependency, runtime, cleanup, or flake risk]

review

Review a test as a quality gate, not as a rubber stamp. The test must justify its existence through customer value, production value, support/debugging value, review value, or release confidence.

Start with code evidence: inspect the test diff and protected production behavior. Then load Test Oracles And Assertions. Add data, doubles, feedback-loop, or mutation references only when the test's value depends on those concerns.

Workflow:

1. Inspect the test diff and protected production behavior.
2. Identify the behavior or failure mode the test claims to protect.
3. Load the references needed to judge the test's strategy, oracle, setup, doubles, and feedback loop.
4. Check whether that behavior matters to a user, operator, customer, API consumer, release, support/debugging loop, or developer workflow.
5. Check whether the assertion would fail for the meaningful regression and identify a plausible bug that would make it fail.
6. Check whether setup, fixtures, mocks, and data preserve the real failure mechanism.
7. Check whether the validation command is the smallest useful loop and whether CI placement is appropriate.
8. Return KEEP, REDO, or REMOVE with evidence.

Output template:

Verdict: KEEP | REDO | REMOVE

Protected behavior:
[what behavior or failure mode this test claims to protect]

Value:
[customer, operator, production, support, release, review, or developer-flow value]

Signal strengths:
[why it would fail for the meaningful regression]

False-confidence risks:
[weak assertions, unrealistic setup, over-mocking, snapshots, flake risk, wrong feedback loop]

References used:
[files that informed the decision]

Falsification check:
[plausible bug and assertion/invariant that would fail]

Required action:
[none for KEEP; exact redesign for REDO; removal reason for REMOVE]

doctor

Run a read-only test-suite health scan and report likely concerns with evidence. Do not edit, delete, rewrite, quarantine, or disable tests.

Start with: Test Suite Health Diagnostics. Add flake, feedback-loop, pyramid, mutation, data, doubles, or oracle references only after the suite evidence points there.

Workflow:

1. Identify repository root, language/framework stack, test runners, CI systems, naming conventions, and test layers.
2. Inventory suite shape and test commands.
3. Scan for weak assertions, excessive mocking, flaky timing, shared state, broad snapshots, slow tests, skipped/quarantined tests, and missing critical-risk coverage.
4. Inspect CI and monitoring signals when available.
5. Grade reliability, speed, signal, diagnostic value, maintainability, risk coverage, and monitoring.

Output template:

## Scope And Evidence
[stack, frameworks, CI, test commands, files inspected, tests run/not run]

## Overall
Grade: [A-F or Low/Medium/High trust]
Confidence: [low/medium/high with reason]

## Top Concerns
1. Severity: [P0-P3]
   Concern: [...]
   Evidence: [...]
   Why it matters: [...]
   Suggested action: [...]

## Rubric
Reliability: [...]
Speed: [...]
Signal: [...]
Diagnostic value: [...]
Maintainability: [...]
Risk coverage: [...]
Monitoring/CI fit: [...]

## Quick Wins And Questions
[small actions and only material follow-up questions]