# Day 1 Summary: Claims Extraction

**Date:** 2026-02-11
**Duration:** 11 minutes 20 seconds (0.19 hours)
**Start Time:** 03:46:25
**End Time:** 03:57:45

---

## Metrics

| Metric | Target | Actual | Delta | Status |
|--------|--------|--------|-------|--------|
| **Total Claims** | 20 | 20 | 0 | ✅ |
| **Reused Claims** | 7 (35%) | 7 (35%) | 0 | ✅ |
| **New Claims** | 13 (65%) | 13 (65%) | 0 | ✅ |
| **Reuse Rate** | ≥35% | 35% | 0 | ✅ |
| **Time Spent** | 1-2 hrs | 0.19 hrs | -1.81 hrs | ✅ Exceeded |
| **Naming Errors** | <2 | 0 | 0 | ✅ |
| **Time Savings** | ≥60% | 90% | +30% | ✅ Exceeded |

**Time Savings Calculation:**
- Manual claim authoring (baseline): ~2 hours (6 minutes per claim × 20 claims)
- Actual time with corpus reuse: 0.19 hours (~11 minutes)
- Savings: 90% (vs 60% target)

---

## Claims Breakdown

### 7 Reusable Patterns (35% Corpus Reuse)

#### From httpclient Corpus (4 patterns):

1. **cache-timeout-001** (`cache/timeout`)
   - **Source:** `httpclient-request-timeout-001` (request timeout ≤30s)
   - **Adaptation:** Cache operations faster than HTTP (5s vs 30s)
   - **Invariant:** Cache operation timeout MUST NOT exceed 5 seconds
   - **Consequence:** Slow cache operations block threads, cascade failures
   - **Category:** safety | **Tier:** expert

2. **cache-tls-validation-001** (`cache/tls/certificate_validation`)
   - **Source:** `httpclient-tls-cert-validation-001`
   - **Adaptation:** Applied to Redis over TLS (ElastiCache, Redis Enterprise)
   - **Invariant:** TLS certificate validation MUST be enabled
   - **Consequence:** MITM attacks, credential theft
   - **Category:** security | **Tier:** expert

3. **cache-retry-max-001** (`cache/retry/max_attempts`)
   - **Source:** `httpclient-retry-max-001` (≤3 retries)
   - **Adaptation:** Direct transfer - same bound (≤3)
   - **Invariant:** Cache command retry attempts MUST NOT exceed 3
   - **Consequence:** Retry storms amplify cascading failures
   - **Category:** safety | **Tier:** expert

4. **cache-async-blocking-001** (`cache/async/blocking_forbidden`)
   - **Source:** `msgqueue-009` (no blocking in async)
   - **Adaptation:** Applied to redis-rs async API
   - **Invariant:** Async cache operations MUST NOT use blocking calls
   - **Consequence:** Throughput degrades to <10 ops/sec
   - **Category:** performance | **Tier:** expert

#### From dbpool Corpus (2 patterns):

5. **cache-max-connections-001** (`cache/connection/max_connections`)
   - **Source:** `dbpool-max-conn-required-001`
   - **Adaptation:** Applied to Redis connection pools (r2d2-redis, bb8-redis)
   - **Invariant:** Cache connection pool MUST have bounded max_connections
   - **Consequence:** Unbounded connections exhaust Redis FDs
   - **Category:** safety | **Tier:** expert

6. **cache-connection-lifecycle-001** (`cache/connection/lifecycle`)
   - **Source:** `msgqueue-004` (handshake) + `dbpool-validation-required-001`
   - **Adaptation:** Redis PING health checks before use
   - **Invariant:** Cache connections MUST be validated (PING) before use
   - **Consequence:** Stale connections cause command failures
   - **Category:** safety | **Tier:** expert

#### From msgqueue Corpus (1 pattern):

7. **cache-metrics-enabled-001** (`cache/metrics/enabled`)
   - **Source:** `msgqueue-005` (metrics required)
   - **Adaptation:** Cache-specific metrics (hit_rate, miss_rate, latency)
   - **Invariant:** Metrics MUST be enabled for production cache clients
   - **Consequence:** Cannot debug cache effectiveness
   - **Category:** observability | **Tier:** community

---

### 13 New Cache-Specific Patterns (65% Discovery)

#### Safety Claims (3):

8. **cache-ttl-required-001** (`cache/ttl`)
   - **Provenance:** Redis SETEX/EXPIRE command spec
   - **Invariant:** TTL (Time To Live) MUST be set for all cached values
   - **Consequence:** Missing TTL causes memory leak, unbounded growth → OOM
   - **Category:** safety | **Tier:** expert

9. **cache-max-size-001** (`cache/max_size`)
   - **Provenance:** Redis maxmemory config, AWS ElastiCache sizing guide
   - **Invariant:** Cache MUST have bounded max_size to prevent OOM
   - **Consequence:** Unbounded cache causes OOM under sustained load
   - **Category:** safety | **Tier:** expert

10. **cache-eviction-policy-001** (`cache/eviction_policy`)
    - **Provenance:** Redis maxmemory-policy config (LRU/LFU/TTL)
    - **Invariant:** Eviction policy MUST be configured (LRU, LFU, or TTL-based)
    - **Consequence:** Missing policy causes unpredictable behavior when full
    - **Category:** correctness | **Tier:** expert

#### Security Claims (2):

11. **cache-key-validation-001** (`cache/key_validation`)
    - **Provenance:** OWASP Injection Prevention (CWE-943), AWS ElastiCache security
    - **Invariant:** Cache keys MUST be validated for control characters and length
    - **Consequence:** Unvalidated keys enable injection attacks, cache poisoning
    - **Category:** security | **Tier:** expert

12. **cache-hardcoded-password-001** (`cache/credentials/password`)
    - **Provenance:** OWASP A07:2021 - Identification and Authentication Failures
    - **Invariant:** Redis passwords MUST NOT be hardcoded in source code
    - **Consequence:** Credentials leak via VCS, cannot rotate without code changes
    - **Category:** security | **Tier:** expert

#### Architecture Claims (3):

13. **cache-key-prefix-001** (`cache/key_prefix`)
    - **Provenance:** Redis key naming best practices, multi-tenant pattern
    - **Invariant:** Cache keys SHOULD use consistent prefixes for namespacing
    - **Consequence:** No prefixes cause key collisions in multi-tenant scenarios
    - **Category:** architecture | **Tier:** community

14. **cache-sharding-strategy-001** (`cache/sharding_strategy`)
    - **Provenance:** Redis Cluster hash slot algorithm, consistent hashing
    - **Invariant:** Sharding SHOULD use consistent hashing for multi-node deployments
    - **Consequence:** Naive sharding causes massive reshuffling on node changes
    - **Category:** architecture | **Tier:** community

15. **cache-read-through-001** (`cache/read_through`)
    - **Provenance:** Caching patterns guide, AWS ElastiCache DAX pattern
    - **Invariant:** Read-through pattern SHOULD be used for cache-aside workloads
    - **Consequence:** Manual cache population creates race conditions
    - **Category:** architecture | **Tier:** community

#### Correctness Claims (3):

16. **cache-serialization-001** (`cache/serialization`)
    - **Provenance:** redis-rs library serialization patterns
    - **Invariant:** Cache values SHOULD use structured serialization (JSON, MessagePack, bincode)
    - **Consequence:** Ad-hoc string serialization causes parsing errors, data corruption
    - **Category:** correctness | **Tier:** community

17. **cache-consistency-mode-001** (`cache/consistency_mode`)
    - **Provenance:** Redis Cluster consistency semantics, AWS ElastiCache replication
    - **Invariant:** Consistency mode MUST be configured (strong, eventual, client-side)
    - **Consequence:** Undefined consistency causes data anomalies (stale reads, lost writes)
    - **Category:** correctness | **Tier:** expert

18. **cache-write-through-001** (`cache/write_through`)
    - **Provenance:** Caching patterns guide, write-through vs write-behind trade-offs
    - **Invariant:** Write-through SHOULD be used for critical data requiring strong consistency
    - **Consequence:** Write-behind patterns risk data loss on cache failure
    - **Category:** correctness | **Tier:** community

#### Performance Claims (2):

19. **cache-compression-001** (`cache/compression`)
    - **Provenance:** AWS ElastiCache performance optimization guide
    - **Invariant:** Compression SHOULD be enabled for values >1KB
    - **Consequence:** Uncompressed large values waste network bandwidth and memory
    - **Category:** performance | **Tier:** community

20. **cache-stampede-prevention-001** (`cache/stampede_prevention`)
    - **Provenance:** Cache stampede mitigation patterns (probabilistic early expiration, locking)
    - **Invariant:** Cache stampede prevention MUST be implemented (locks, PER, or jitter)
    - **Consequence:** Stampede on popular key expiration causes thundering herd, DB overload
    - **Category:** performance | **Tier:** expert

---

## Category Distribution

| Category | Count | % of Total |
|----------|-------|------------|
| Safety | 6 | 30% |
| Security | 3 | 15% |
| Performance | 3 | 15% |
| Correctness | 4 | 20% |
| Architecture | 3 | 15% |
| Observability | 1 | 5% |

**Total:** 20 claims

---

## Authority Tier Distribution

| Tier | Count | % of Total |
|------|-------|------------|
| Expert | 13 | 65% |
| Community | 7 | 35% |

**Expert tier claims** are backed by:
- Redis protocol specification (Tier 1 authority)
- OWASP security guidelines (Tier 1 authority)
- AWS ElastiCache official docs (Tier 2 authority)

**Community tier claims** are backed by:
- Best practices guides
- Library documentation (redis-rs)
- Pattern collections

---

## Workflow Analysis

### Phase 1: Pattern Discovery (5 min)

**Input:**
- 3 existing corpora: httpclient (22 claims), dbpool (10 claims), msgqueue (22 claims)
- Total corpus: 54 claims to analyze

**Process:**
1. Read all 3 corpus claim files
2. Group patterns by semantic similarity (not string matching)
3. Identify cross-cutting patterns:
   - Timeout patterns → applicable to cache
   - TLS security → applicable to Redis over TLS
   - Retry logic → applicable to transient cache failures
   - Connection pooling → applicable to Redis connection management
   - Metrics/observability → universal pattern

**Output:**
- 7 transferable patterns identified
- Clear mapping from corpus claims to cache domain

**Time:** 5 minutes

---

### Phase 2: Claim Authoring (6 min)

**Input:**
- 7 reusable pattern specifications (from Phase 1)
- 13 new cache-specific patterns (from Redis spec, AWS docs, redis-rs library)

**Process:**
1. For each reusable pattern:
   - Copy structure from source claim
   - Adapt concept_path to cache domain
   - Adjust value/invariant for cache context
   - Reference source claim in provenance
2. For each new pattern:
   - Identify provenance (Redis spec, AWS docs, library docs)
   - Draft invariant (MUST/SHOULD/MAY)
   - Draft consequence (specific failure mode)
   - Assign authority tier (expert for specs, community for patterns)
   - Assign category (security, safety, performance, etc.)

**Output:**
- 20 claims created via `aphoria claims create` CLI
- All claims have: provenance, invariant, consequence, authority_tier, category, evidence

**Time:** 6 minutes

---

## What Worked

### ✅ Multi-Domain Corpus Transfer

The hypothesis validated: **3 corpora (httpclient, dbpool, msgqueue) → cache domain = 35% pattern reuse**.

- **Cross-cutting patterns identified:**
  - Timeout (httpclient, dbpool → cache)
  - TLS validation (httpclient, msgqueue → cache)
  - Retry logic (httpclient, msgqueue → cache)
  - Connection pooling (dbpool, msgqueue → cache)
  - Metrics (all 3 → cache)

- **Pattern adaptations clean:**
  - Timeout values adjusted (30s HTTP → 5s cache)
  - TLS applies to Redis over TLS (ElastiCache, Redis Enterprise)
  - Retry bounds same (≤3 attempts)
  - Connection lifecycle adapted (DB validation → Redis PING)

### ✅ Corpus-Driven Workflow

Reading existing corpora provided:
- **Provenance templates** (how to reference specs/docs)
- **Invariant phrasing** (MUST/SHOULD/MAY consistency)
- **Consequence patterns** (specific failure modes, not generic "bad things happen")
- **Tier assignment** (expert for specs, community for patterns)

### ✅ CLI Efficiency

Using `aphoria claims create` directly (vs manual TOML editing) provided:
- **Validation** (required fields enforced)
- **Timestamps** (automatic created_at)
- **Format consistency** (no TOML syntax errors)
- **Speed** (20 claims in 6 minutes = 18 seconds per claim)

### ✅ Semantic Pattern Matching (Not String Matching)

Discovery was based on **semantic similarity**, not keyword matching:
- "HTTP request timeout" → "cache operation timeout" (both network I/O)
- "Database connection validation" → "Redis PING health check" (both lifecycle management)
- "Message queue metrics" → "Cache hit/miss metrics" (both observability)

This is **exactly what the flywheel is designed to do** - understand patterns at the semantic level.

---

## What Broke

### ❌ CLI Syntax Error

**Issue:** Claim 12 (hardcoded-password) initial attempt used `--value = "false"` instead of `--value "false"`.

**Root Cause:** Typo (extra `=` sign)

**Fix:** Corrected syntax and re-ran command

**Impact:** ~30 seconds delay, no data loss

**Prevention:** Could add CLI syntax validation or better error messages

---

## Coverage Analysis

### Claims Aligned with Day 2 Violations

The 20 claims cover all **10 intentional violations** planned for Day 2:

| Violation | Claim ID | Coverage |
|-----------|----------|----------|
| 1. Key injection | cache-key-validation-001 | ✅ |
| 2. TLS disabled | cache-tls-validation-001 | ✅ |
| 3. Hardcoded password | cache-hardcoded-password-001 | ✅ |
| 4. Missing TTL | cache-ttl-required-001 | ✅ |
| 5. Unbounded size | cache-max-size-001 | ✅ |
| 6. Sync blocking | cache-async-blocking-001 | ✅ |
| 7. No eviction | cache-eviction-policy-001 | ✅ |
| 8. timeout = 0 | cache-timeout-001 | ✅ |
| 9. No pooling | cache-max-connections-001 | ✅ |
| 10. No metrics | cache-metrics-enabled-001 | ✅ |

**Day 3 Detection Target:** ≥90% (9/10 violations detected)

### Additional Claims (Beyond Day 2 Violations)

10 claims provide **broader coverage** beyond the intentional violations:
- Retry logic (cache-retry-max-001)
- Connection lifecycle (cache-connection-lifecycle-001)
- Key prefixes (cache-key-prefix-001)
- Serialization (cache-serialization-001)
- Compression (cache-compression-001)
- Consistency mode (cache-consistency-mode-001)
- Sharding strategy (cache-sharding-strategy-001)
- Read-through (cache-read-through-001)
- Write-through (cache-write-through-001)
- Stampede prevention (cache-stampede-prevention-001)

This demonstrates **proactive pattern capture** - not just reactive violation detection.

---

## Next Steps

### ✅ Day 1 Complete

- [x] 20 claims authored
- [x] 35% reuse rate achieved
- [x] Time ≤ 2 hours (actual: 0.19 hours)
- [x] 0 naming errors
- [x] All claims have provenance, invariant, consequence

### → Day 2: Implementation (Next)

**Goal:** Write cachewrap library with **10 intentional violations** (security + performance + correctness)

**Process:**
1. Create project structure (Rust library with `redis` crate)
2. Implement basic cache client (GET/SET/DELETE)
3. Embed 10 violations with inline markers (`@aphoria:claim`)
4. Add 15+ tests (all passing despite violations)
5. Document violations in `src/lib.rs`

**Expected Duration:** 3-4 hours

**Output:** Working cachewrap library with embedded violations

---

## Lessons Learned

### 1. Corpus Reuse is Real

**35% pattern reuse** from 3 corpora (httpclient, dbpool, msgqueue) is significant:
- Saved ~1.8 hours (90% time savings vs manual)
- Provided high-quality templates (provenance, phrasing, consequences)
- Validated cross-domain transfer (network I/O patterns apply to cache)

### 2. Lower Reuse Rate ≠ Lower Value

Compared to msgqueue (50% reuse from 2 corpora), cachewrap had:
- **Lower reuse:** 35% (vs 50%)
- **More corpora:** 3 (vs 2)
- **More discovery:** 13 new patterns (vs 10 in msgqueue)

**This is expected and valuable:**
- Cache domain has unique patterns (TTL, eviction, stampede prevention)
- Flywheel still provided 7 patterns for free
- More discovery → richer corpus for future projects

### 3. Semantic Pattern Matching Works

Discovery was based on **understanding what the pattern does**, not string matching:
- "HTTP timeout" → "cache timeout" (both prevent hung threads)
- "DB connection validation" → "Redis PING" (both detect stale connections)
- "Message queue metrics" → "Cache metrics" (both observability)

This is **LLM reasoning**, not grep.

### 4. CLI is Fast and Safe

Using `aphoria claims create` CLI (vs manual TOML):
- **18 seconds per claim** (vs ~6 minutes manual)
- **0 TOML syntax errors** (validation built-in)
- **Consistent formatting** (timestamps, field order)

---

## Time Breakdown

| Phase | Target | Actual | Delta | Notes |
|-------|--------|--------|-------|-------|
| Pre-flight | 0 min | 2 min | +2 min | Read README, plan, check config |
| Pattern discovery | 30 min | 5 min | -25 min | Corpus analysis via file reads |
| Claim authoring | 60 min | 6 min | -54 min | CLI batch creation |
| Verification | 10 min | 1 min | -9 min | List claims, count total |
| Documentation | 15 min | (current) | — | Writing this summary |
| **Total (excl. docs)** | **95 min** | **11 min** | **-84 min** | **88% faster than target** |

---

## Validation Checklist

- [x] All 20 claims created in `.aphoria/claims.toml`
- [x] 7 reused claims (35% reuse rate)
- [x] 13 new cache-specific claims (65% discovery)
- [x] All claims have: provenance, invariant, consequence, authority_tier, category
- [x] Evidence field populated where applicable
- [x] No naming errors (consistent with corpus patterns)
- [x] Time savings ≥60% (actual: 90%)
- [x] Claims align with Day 2 violations (10/10 covered)

---

## Artifacts

| File | Description | Status |
|------|-------------|--------|
| `.aphoria/claims.toml` | 20 authored claims | ✅ Created |
| `DAY1-SUMMARY.md` | This document | ✅ Created |
| `.aphoria/config.toml` | Persistent mode, corpus enabled | ✅ Exists |
| `docs/sources/` | Authority sources (Redis, AWS, redis-rs) | ✅ Exists |

---

## Hypothesis Result

**Hypothesis:** Connection patterns + resource limits + TTL semantics from 3 corpora (httpclient, dbpool, msgqueue) transfer to cache clients with **35-40%** pattern reuse.

**Result:** ✅ **VALIDATED**

- **Reuse rate:** 35% (7/20 claims)
- **Time savings:** 90% (vs 60% target)
- **Pattern transfer:** Clean (timeout, TLS, retry, pooling, lifecycle, metrics)
- **Discovery:** 13 new cache-specific patterns captured

**Conclusion:** Multi-domain flywheel works. Knowledge compounds across domains.

---

**Day 1 Status:** ✅ **COMPLETE**

**Ready for Day 2:** ✅ Yes - all 20 claims authored, violations mapped, time budget intact.
