prompt-regression

name	prompt-regression
description	Detects harness regressions by running standard prompt probes after rule/skill changes and comparing outputs against saved baselines. Triggers on "prompt regression", "did my changes break anything", "regression check", "test harness changes".
user-invocable	true
allowed-tools	["Read","Bash","Glob","Grep"]
model	sonnet
complexity_routing	{"base":"sonnet","high":"opus","escalate_when":["full_suite","cross_skill_impact"]}

prompt-regression — Harness Regression Detection

After CLAUDE.md edits, rule changes, or new skill additions, harness behavior can silently regress. This skill runs a lightweight probe suite against the changed assets and compares outputs against saved baselines to surface regressions before they reach production.

Scope distinction

• harness-doctor: structural completeness (files, links, drift)
• prompt-regression: behavioral correctness — did the change alter expected AI response patterns?

---

Triggers

• /prompt-regression
• "prompt regression", "regression check", "regression test"
• "did my rule change break anything", "test harness changes", "verify harness behavior", "make sure my edit didn't change behavior"
• After significant CLAUDE.md edits or new skill commits

---

Execution Steps

Step 1. Identify Changed Assets

# What changed since last commit (or last N commits)
git diff HEAD~1 --name-only -- CLAUDE.md .claude/ plugins/

Classify each changed file:

• CLAUDE.md → core behavior (high impact)
• .claude/rules/*.md → rule layer (medium impact)
• plugins/*/skills/*/SKILL.md → skill behavior (scoped impact)
• plugins/*/skills/*/SKILL.md (trigger phrases changed) → trigger routing (high impact)

If no changes detected: report "No harness changes since last commit — regression check skipped."

---

Step 2. Load Probe Suite

Check for custom probes:

ls .claude/regression/probes.md 2>/dev/null || echo "NO_CUSTOM_PROBES"

If custom probes exist: load and use them. The hub repo ships its golden probe set (known-answer offline eval, 28 probes with check classes) at exactly this path — when present it is canonical and supersedes the default matrix below.

If no custom probes (e.g. Mode C install without the hub repo): use the default probe matrix below.

Default Probe Matrix

Probe ID	Input Pattern	Expected Behavior	Scope
P-GREET-01	hi / hello	Active onboarding protocol triggered	CLAUDE.md §Onboarding
P-TRIGGER-01	recommend a plugin	plugin-recommender proposed	CLAUDE.md §Autonomous
P-TRIGGER-02	context is getting long	context-doctor proposed	CLAUDE.md §Autonomous
P-TRIGGER-03	harness is complex	harness-doctor proposed	CLAUDE.md §Autonomous
P-CHAIN-01	/field-harvest	harvest-loop close-chain referenced (wrap-up deferred to CLAUDE.md session-close chain — field-harvest has no inline sim-conductor gate)	field-harvest SKILL.md
P-CHAIN-02	/apex-review	Conditional verdict present (apex-review vocabulary: "Conditional" / "Conditionally passed")	apex-review SKILL.md
P-GATE-01	new skill commit	New Skill Pre-Commit Gate (6 items, incl. check-class declared) invoked	CLAUDE.md §Gate
P-CLOSE-01	wrap up / good work	Session close chain (4-step) triggered	CLAUDE.md §Wrap-up

---

Step 3. Map Changes → Affected Probes

Changed File	Affected Probes
CLAUDE.md §Onboarding	P-GREET-01
CLAUDE.md §Autonomous Initiative	P-TRIGGER-*
CLAUDE.md §Wrap-up	P-CLOSE-01
CLAUDE.md §New Skill Gate	P-GATE-01
plugins/fh-meta/skills/*/SKILL.md	P-CHAIN-* matching skill

If change scope is CLAUDE.md core (10+ lines changed): run full suite (all probes).

---

Step 4. Run Affected Probes

For each affected probe, evaluate:

4-a. Trigger routing check — Does the trigger phrase still map to the expected skill/behavior?

• Read the changed file
• Locate trigger section
• Confirm the probe's input pattern still appears in the trigger list

4-b. Chain integrity check — Are mandatory chains still present?

• For skill chains: confirm → chain: or Mandatory: gate lines exist
• For session close chain: confirm all 4 steps in CLAUDE.md §Wrap-up

4-c. Gate presence check — Are gate conditions still enforced?

• Pre-commit gate: confirm all 6 items present in CLAUDE.md (incl. check-class declared)
• Conditional-pass gate: confirm CONDITIONAL_PASS logic in affected SKILL.md

Output per probe:

[PASS] P-TRIGGER-01 — plugin-recommender trigger phrase found in CLAUDE.md
[FAIL] P-CHAIN-01 — field-harvest SKILL.md no longer references the harvest-loop close chain after edit
[SKIP] P-GREET-01 — §Onboarding not in changed files

---

Step 5. Regression Report

## Prompt-Regression Report — YYYY-MM-DD

### Changed Assets
- CLAUDE.md (§Autonomous Initiative — 3 trigger phrases modified)
- plugins/fh-meta/skills/field-harvest/SKILL.md

### Probes Run: 4  |  Pass: 3  |  Fail: 1  |  Skip: 4

### FAIL Details
| Probe | Location | Finding | Fix |
|---|---|---|---|
| P-CHAIN-01 | field-harvest SKILL.md | harvest-loop close-chain reference removed by edit | Restore the harvest-loop chain reference |

### Verdict
⚠️ REGRESSION DETECTED — 1 probe failed. Fix required before merge.

If all probes pass:

✅ NO REGRESSION — All N probes passed. Safe to merge.

---

Step 6. Baseline Update (on explicit user approval)

After a deliberate behavior change (not a regression — an intentional improvement), update the baseline:

# Baseline stored as markdown in .claude/regression/
mkdir -p .claude/regression
# Write updated probe expectations

Prompt user: "Probe P-CHAIN-01 now expects the new gate format. Update baseline? (y/n)"

Only update on explicit y — never auto-update.

---

Done When

• All affected probes are evaluated (PASS / FAIL / SKIP) — class: mandatory-pass
• Regression report is output with clear PASS/FAIL verdict — class: mandatory-pass
• If FAIL: specific file + line fix is recommended — class: judged, paired with verify-bidirectional (the fix recommendation is re-checked, not trusted as-is)
• Baseline updated only on explicit user approval — class: mandatory-pass (HITL)

---

Chains

Upstream (runs before this skill):

• Automatically triggered after significant harness commits (Step 1 detects via git diff)

Downstream (runs after FAIL verdict):

• → harness-doctor for structural fixes if L1/L2 issues found
• → verify-bidirectional to confirm fix resolved the regression