NWave nw-spike
Runs a timeboxed PROBE to validate one core assumption, then optionally PROMOTES the probe into a walking skeleton — the first e2e thin slice of the feature, committed and demo-able. Use after DISCUSS when the feature involves a new mechanism, performance requirement, or external integration.
git clone https://github.com/nWave-ai/nWave
T=$(mktemp -d) && git clone --depth=1 https://github.com/nWave-ai/nWave "$T" && mkdir -p ~/.claude/skills && cp -r "$T/nWave/skills/nw-spike" ~/.claude/skills/nwave-ai-nwave-nw-spike && rm -rf "$T"
nWave/skills/nw-spike/SKILL.mdNW-SPIKE: Probe → Walking Skeleton
Wave: SPIKE (between DISCUSS and DESIGN) | Agent: Attila (nw-software-crafter) | Command:
/nw-spike
Overview
Execute a two-phase wave that turns a risky assumption into visible, iterable value as fast as possible:
- PROBE — quick throwaway validation of one core assumption (30-60 min, code in
)/tmp/ - PROMOTION GATE (interactive) — ask the user whether to promote the probe
- WALKING SKELETON — refactor the probe into an end-to-end thin slice committed to the repository (1-3 h, code in
+ 1 acceptance test)src/
The PROBE answers "does the mechanism work?". The WALKING SKELETON answers "can a user see it working end-to-end?". You never throw away working validated code — you promote it and iterate.
When to use
The spike is needed when the feature introduces:
- A new mechanism never tried in this codebase
- A performance requirement that cannot be validated by reasoning alone
- An external integration with unknown behaviour
If none of the above apply, skip SPIKE and go to DESIGN.
Prior Wave Consultation
- DISCUSS artifacts: Read
(required)docs/feature/{feature-id}/discuss/
— scope and acceptance criteriauser-stories.md
— constraints and assumptions to testwave-decisions.md
- DIVERGE artifacts: Read
(if present)docs/feature/{feature-id}/diverge/recommendation.md
Interactive decision points (Phase 1 entry)
Decision 1: Probe scope
Question: What is the ONE assumption you need to validate? Examples:
- "Can we parse pytest output reliably in <5 seconds?"
- "Can the CEL library evaluate 100 expressions in <1 second?"
- "Can we write to
from a subprocess without corruption?".git/hooks/
Decision 2: Performance budget
Question: What is the timing constraint? (Enter "none" if mechanism validation only) Examples:
- "<5 seconds end-to-end"
- "<100ms per operation"
- "Handle 10K items without OOM"
Decision 3: End-to-end path preview
Question: If this probe works, what would the thinnest end-to-end slice look like? Capture the rough path:
user-facing entry → business logic → persistence/services → user-visible output. This is not a commitment — it's context for the promotion gate later.
Phase 1 — PROBE
Throwaway validation of the assumption.
Agent invocation
@nw-software-crafter
Execute PROBE for "{feature-description}".
Probe question: {Decision 1 answer} Performance budget: {Decision 2 answer} Target e2e path (for later): {Decision 3 answer}
Rules:
- Code goes in
. Never in/tmp/spike_{feature_id}/
.src/ - Max 1 hour. No tests, no types, no error handling, no abstractions.
- One file preferred. Two files maximum.
- Use
for timing.time.perf_counter() - Print results to stdout.
After probe completes:
- Write findings to
— binary verdict (WORKS / DOESN'T WORK), timing, edge cases, design implications.docs/feature/{feature-id}/spike/findings.md - Do not delete the probe code yet — wait for the promotion gate.
- Report verdict and ask the orchestrator to run the promotion gate.
Phase 2 — PROMOTION GATE (interactive)
Run this gate only after the probe completes and findings.md is written.
Present the user with three choices:
| Choice | When to pick | Outcome |
|---|---|---|
| PROMOTE | Probe verdict is WORKS and the mechanism is worth building on | Proceed to Phase 3 — walking skeleton |
| DISCARD | Probe verdict is WORKS but not worth pursuing (findings are enough) | Delete . Commit . Hand off to DESIGN. |
| PIVOT | Probe verdict is DOESN'T WORK or revealed a better approach | Delete probe code. Annotate with the pivot. Either loop back to DISCUSS or run a second probe. |
Default: if the probe verdict is WORKS and no reason to stop, recommend PROMOTE but let the user override.
Record the promotion decision in
docs/feature/{feature-id}/spike/wave-decisions.md as an explicit wave decision with rationale.
Phase 3 — WALKING SKELETON (only if PROMOTE)
Refactor the probe into the thinnest end-to-end slice that is committed, tested, and demo-able.
Definition of Done (walking skeleton)
- End-to-end path: the slice enters from a real user-facing entry point (CLI command, HTTP endpoint, UI action, hook) and exits at a real user-visible output (stdout, HTTP response, rendered screen, persisted file). Every layer in between is exercised — no layer is mocked unless that layer is an external paid service classified as costly in DISTILL's Walking Skeleton Strategy (then use the fake/contract test pattern).
- One acceptance test: a
tagged scenario in@walking_skeleton @driving_port
. The scenario MUST be green before hand-off.tests/{test-type-path}/{feature-id}/acceptance/walking-skeleton.feature - Production location: code lives under
, not insrc/{production-path}/
. Minimal module skeleton is fine — no premature abstractions, no features beyond the walking skeleton./tmp/ - Committed: the walking skeleton commit message is
.feat({feature-id}): walking skeleton — {one-line description} - Demo-able: running the single acceptance test (or the real entry-point command) produces visible output that matches the user story from DISCUSS.
- Back-propagation: if building the skeleton reveals a contradiction with DISCUSS or DESIGN, write the contradiction to
and stop — do not hand off to DISTILL until resolved.docs/feature/{feature-id}/spike/upstream-issues.md
Agent invocation (Phase 3)
@nw-software-crafter
Promote probe for "{feature-description}" into a walking skeleton.
Source probe:
/tmp/spike_{feature_id}/
Target driving adapter: {from Decision 3, refined with user}
Target acceptance test path: tests/{test-type-path}/{feature-id}/acceptance/walking-skeleton.feature
Rules:
- Max 3 hours. Stop and escalate if over budget.
- One acceptance test only. No unit tests unless they are strictly required to make the acceptance test pass.
- No premature abstractions. The skeleton should be obviously incomplete — only the single path from the user story works. Error paths, edge cases, and other scenarios are DISTILL's job.
- Use the real driving adapter, the real domain code, the real driven adapter. In-memory doubles only for costly external services.
- Delete
after promotion./tmp/spike_{feature_id}/
Walking skeleton commit checklist
- 1 acceptance test @walking_skeleton green
- Real user-facing entry point exercised (not a service function call)
- Real driven adapters for local resources (filesystem, git, subprocess, SQLite)
- Code in
, notsrc//tmp/ - Committed with conventional commit message
- Probe directory deleted
- Findings.md includes the "promoted on {date}" note
Progress tracking
The invoked agent MUST create a task list from its workflow phases at the start of execution using TaskCreate. Each phase becomes a task with the gate condition as completion criterion. Phase 1, Phase 2, and Phase 3 are separate task groups — Phase 3 tasks are only created if the promotion gate says PROMOTE.
Success criteria
Phase 1 (always)
- Exactly one assumption tested (not two, not zero)
- Probe code lives in
, never in/tmp/src/ - Completed within 1 hour (or escalated with "BIGGER THAN EXPECTED")
-
written with binary verdict, timing, and edge casesfindings.md
Phase 2 (always)
- Promotion gate decision captured in
wave-decisions.md - One of: PROMOTE / DISCARD / PIVOT selected by user
Phase 3 (only if PROMOTE)
- Walking skeleton acceptance test green
- E2E path exercised through all non-costly layers
- Skeleton code in
, committedsrc/ - Probe directory deleted
- No upstream contradictions left unresolved
Next wave
Handoff to: nw-solution-architect (DESIGN) — DESIGN reads findings.md and the walking skeleton (if promoted) before starting. The skeleton is a fait accompli — DESIGN designs the rest of the feature around it, not in place of it.
DISTILL (next wave after DESIGN) reads the walking skeleton as a prior artifact and adds additional scenarios and integration tests on top of it — it does not write the walking skeleton from scratch.
Wave decisions summary
Before completing SPIKE, produce
docs/feature/{feature-id}/spike/wave-decisions.md:
# SPIKE Decisions -- {feature-id} ## Assumption Tested - {the one question} ## Probe Verdict - {WORKS / DOESN'T WORK}: {one-line summary} ## Promotion Decision - {PROMOTE / DISCARD / PIVOT}: {rationale} ## Walking Skeleton (only if PROMOTE) - Driving adapter: {entry point} - Acceptance test: {path to .feature file} - Commit: {commit sha of walking skeleton} - Demo command: {how to run the skeleton} ## Design Implications - {what DESIGN must account for based on probe results and skeleton learnings} ## Constraints Discovered - {any new constraints from edge cases}
Examples
Example 1: Performance probe → promoted skeleton
/nw-spike "wave-matrix -- derive feature status from pytest + filesystem"
Probe question: "Can we collect pytest markers + parse filesystem state in <5 seconds?" Agent writes 50-line script in
/tmp/spike_wave_matrix/. Result: 44 seconds (budget blown), but discovers pytest --collect-only --cache-only completes in 200 ms.
Gate: user picks PROMOTE with the cache-only approach.
Phase 3: agent refactors the probe into src/des/cli/wave_matrix.py with a wave-matrix CLI command; one acceptance test exercises subprocess.run(["wave-matrix", "--feature", "alpha"]) end-to-end and asserts the markdown output contains a row for alpha.
DESIGN now designs the rest (multi-feature aggregation, cell navigation, refresh strategy) around the already-working skeleton.
Example 2: Integration probe → discard
/nw-spike "cel-policy-engine -- evaluate access control expressions"
Probe question: "Can cel-python evaluate 100 policy expressions in <1 second?" Agent installs cel-python, writes evaluation loop, measures 23 ms for 100 expressions. Verdict: WORKS. Edge case: nested map access syntax differs from Go CEL. Gate: user picks DISCARD — the findings are enough, the real access-control feature is large enough to deserve its own design wave. Phase 3 skipped. Findings committed. DESIGN reads findings.md.
Example 3: Mechanism probe → pivot
/nw-spike "git-hook-wiring -- install hooks via subprocess"
Probe question: "Can we write to
.git/hooks/ from a Python subprocess without file corruption?"
Agent tries concurrent access, discovers that the real risk is not corruption but the existing user hook being silently overwritten.
Gate: user picks PIVOT — the real question is "how do we install alongside existing user hooks?". Findings annotated with the pivot, new probe scheduled.
Expected outputs
docs/feature/{feature-id}/spike/ findings.md # always wave-decisions.md # always (with promotion decision) upstream-issues.md # only if skeleton revealed prior-wave contradictions src/{production-path}/ # only if PROMOTE {module}.py # minimal walking skeleton tests/{test-type-path}/{feature-id}/acceptance/ walking-skeleton.feature # only if PROMOTE — 1 scenario, @walking_skeleton @driving_port steps/ # only if PROMOTE