Incident Distiller

Incident Distiller

Converts incidents into structured learning units. V4: includes Failure Genome distillation with family classification and utility scoring.

When to Use

After any bug fix, deployment failure, or near-miss — when you need to create structured memory from the event.

Input

• Description of what happened
• Root cause analysis
• Fix applied
• Impact severity (1-10)
• Verification evidence

Output

Three files (+ index update):

1. .evolution/incidents/INC-YYYYMMDD-NNN.json
2. .evolution/experience_units/EU-YYYYMMDD-NNN.json
3. (If Impact ≥ 7) .evolution/failure_genomes/FG-NNNNNN.json
4. (If genome created) Update FAMILY_INDEX.json

Procedure

1. Create Incident Event

Validate against schemas/incident-event.schema.json:

{
  "incident_id": "INC-YYYYMMDD-NNN",
  "created_at": "ISO8601",
  "title": "Short title (5+ chars)",
  "type": "Regression | Gap | Process | Near-miss | Documentation Drift",
  "severity": 7,
  "category": "Preventive | Reactive | Structural | Paradigm Shift",
  "what_happened": "What broke and what the user/system experienced",
  "why_it_happened": "Root cause — WHY, not just WHAT",
  "fix_applied": "Exact change made to fix it",
  "pattern_extracted": "PAT-NNN: One sentence learning",
  "anti_pattern": "AP-NNN: What to never do again",
  "related_incidents": [],
  "verified": true,
  "evidence": "How verification was done"
}

2. Distil Experience Unit

Validate against schemas/experience-unit.schema.json:

{
  "eu_id": "EU-YYYYMMDD-NNN",
  "source_incident": "INC-YYYYMMDD-NNN",
  "pattern": "Reusable pattern name",
  "anti_pattern": "Anti-pattern name",
  "repair_operator": "Smallest reusable fix action",
  "applicability": ["tag1", "tag2", "tag3"],
  "impact": 7,
  "xp_awarded": 13
}

3. Distil Failure Genome (Impact ≥ 7)

Validate against schemas/failure-genome.schema.json.

3a. Context Fingerprint

Describe the environment, NOT the specific bug:

"context_fingerprint": {
  "stack_tags": ["python", "node", "supabase", "cloud-run", "gemini"],
  "surface_tags": ["deploy", "ui", "cli", "data-contract", "docs", "auth"],
  "environment_tags": ["windows-powershell", "linux", "gcp", "local"],
  "repo_maturity": "greenfield | legacy | hybrid | unknown"
}

Only include tags that are relevant. Don't tag everything.

3b. Failure Family Classification

Check existing families first: Read .evolution/failure_genomes/FAMILY_INDEX.json.

Matching rules — a genome belongs to an existing family if it overlaps on:

• Failure family (same class of problem)
• Violated invariant (same rule broken)
• At least 2 stack/surface tags
• Same repair operator neighborhood

Known families (seed from NVE journal):

Creating a new family: Use pattern {noun}-{noun}-{action}:

• stale-docs-after-change
• ephemeral-state-assumption
• import-omission-in-partial-fix

3c. Violated Invariant

The rule that should NEVER have been broken. Format: snake_case.

Good invariants:

• done_means_verified
• no_silent_fallbacks
• write_format_must_match_read_format
• external_state_must_be_persistent
• docs_follow_architecture

Bad invariants (too vague):

• ❌ code_should_work
• ❌ be_careful
• ❌ test_everything

3d. Repair Operator

The smallest reusable action. Format: verb-noun-phrase.

Good operators:

• strip-and-verify-all-env-vars-before-deploy
• add-resolvability-check-to-fidelity-gate
• compute-structural-composite-from-sub-metrics

Bad operators (too broad):

• ❌ fix-the-bug
• ❌ be-more-careful

3e. Verifier Evidence

"verifier_evidence": [
  {
    "kind": "test | command_output | screenshot | healthcheck | diff | replay_report | other",
    "ref": "path or command that produced proof",
    "summary": "one sentence describing what was verified"
  }
]

At least ONE evidence item is required for promoted genomes.

3f. Transferability Tags

Format: applies_to=<scope> and risk=<level>:

"transferability_tags": [
  "applies_to=cloud-run",
  "applies_to=env-var-management",
  "risk=high"
]

3g. Initial Utility Estimate

"utility": {
  "score": severity / 10,
  "reuse_count": 0,
  "prevention_count": 0,
  "negative_transfer_count": 0,
  "last_used_at": null
}

Utility score starts at severity / 10 and decays if not used:

• After 30 days without use: multiply by 0.9
• After 90 days without use: multiply by 0.7
• After reuse: multiply by 1.1 (cap at 1.0)
• After preventing a repeat: multiply by 1.2 (cap at 1.0)
• After negative transfer: multiply by 0.5

3h. Replay Status

Initially:

"replay": {
  "status": "not_run",
  "family_sample_size": 0,
  "holdout_sample_size": 0
}

After replay:

"replay": {
  "status": "passed | failed | partial",
  "family_sample_size": 5,
  "holdout_sample_size": 2,
  "pass_rate": 0.8,
  "notes": "4/5 family members would have been prevented"
}

4. Update Family Index

After creating a genome, update .evolution/failure_genomes/FAMILY_INDEX.json:

• Add genome ID to the family's genomes array
• Increment member_count
• Recalculate avg_utility
• If new family: add new entry

5. Update XP

6. Naming Convention

• Incidents: INC-YYYYMMDD-NNN (e.g., INC-20260318-001)
• Experience Units: EU-YYYYMMDD-NNN
• Failure Genomes: FG-NNNNNN (6-digit sequential, zero-padded)
• Next available genome ID: Check existing files to determine next number.