waggle-os/docs/decisions/2026-04-28-agent-fix-sprint-closure.md

---
decision_id: 2026-04-28-agent-fix-sprint-closure
date: 2026-04-28
phase: agent fix sprint — closure memo (single-source-of-truth)
verdict: harness fixes complete. Substrate-no-regression confirmed. Tier 2 GEPA work deferred to CC-2 Faza 1. Phase 5 NULL-baseline standby pending Faza 1 Checkpoint C + Memory Sync activation + PM-authored Phase 5 brief.
predecessors:
  - 2026-04-27-phase-2-gate-d3-rule-inspection.md
  - 2026-04-27-phase-3-acceptance-gate-results.md
  - 2026-04-28-phase-4-3-rescore-delta-report.md
  - 2026-04-28-phase-4-4-skills-audit-results.md
  - 2026-04-28-phase-4-5-tools-audit-results.md
branch_head: c9bda3d (Phase 4.7)
---

# Agent Fix Sprint — Closure Memo

## 1. TL;DR

Sprint scope: harness reliability + auditability fixes across four phases (1.x foundations → 2.x loop unification → 3.x long-task persistence → 4.x reporting + audits). Substrate v6 was preserved throughout — every commit was additive or refactor-equivalent, never substrate-modifying.

The pivotal mid-sprint event was the Phase 2 acceptance gate's **D3 disambiguation step**: the smoke run produced 90% trio-strict pass against a v6 baseline of 33.5%. Re-aggregation under v6's exact substring-match rule shrunk the drift from +56.5pp to +6.5pp — within statistical sample variance for N=20. The methodology gap (judge consensus vs substring match) was cleanly identified and resolved without re-running the smoke. This pattern recurs throughout the sprint: pre-execution rule clarification cheaper than post-execution re-run.

The pivotal late-sprint event was Phase 4.3's **strategic re-score finding**: of 36 judge rationales from the failed 2026-04-26 pilot, 5.6% were Tier 1 (Phase 1.1 normalize-fix-able) and 72.2% were Tier 2 (real semantic / synthesis content gaps). Hypothesis H4 (sovereign multiplier) registered 100% Tier 2 with zero ambiguity. This forced the strategic decision to authorize Tier 2 GEPA work pre-Phase-5 — Phase 1.1 normalize alone was empirically demonstrated insufficient to rescue the multiplier teza. CC-2 took over Tier 2 GEPA Faza 1 in a separate session.

Sprint cumulative cost: **$0.077 LLM** (Phase 4.3 LLM fallback only; all other phases $0). Sprint cumulative test growth: **+451 tests** added across 14 commits, ending at **2547/2547 packages/agent tests passing**. Tsc strict clean throughout. Zero substrate modifications. Zero regressions across the sprint.

Launch ETA recalibrated **6–9 → 8–11 weeks** to accommodate Tier 2 GEPA work as a serial dependency on Phase 5 NULL-baseline. Phase 5 NULL-baseline is on standby pending Faza 1 Checkpoint C + Memory Sync Marko-side activation + PM-authored Phase 5 brief.

## 2. Sprint timeline

Fourteen waggle-os commits, four phases, plus three analytical phases (4.3 / 4.4 / 4.5) that produced PM-side decision memos without waggle-os code changes:

| Phase | SHA | Component | Test delta | Cost |
|---|---|---|---|---|
| 1.1 | `4a557cc` | `output-normalize.ts` | +43 | $0 |
| 1.2 | `bc5b54f` | `prompt-shapes/` (claude / qwen-thinking / qwen-non-thinking / gpt / generic-simple + selector) | +65 | $0 |
| 1.3 | `12c7334` | `run-meta.ts` | +26 | $0 |
| 2.1 | `a599a07` | `retrieval-agent-loop.ts` (structured-action loop) | +25 | $0 |
| 2.2 | `5699677` | pilot wrapper refactor (consume `runSoloAgent` + `runRetrievalAgentLoop`) | net −84 lines | $0 |
| 2.3 | `61743df` | `benchmarks/harness/src/cells.ts` Option A refactor | (no new test files; existing pass) | $0 |
| 3.1 | `7163114` | `long-task/checkpoint.ts` | +42 | $0 |
| 3.2 | `a41271b` | `long-task/recovery.ts` | +52 | $0 |
| 3.3 | `01e32d9` | `long-task/context-manager.ts` | +48 | $0 |
| 3.4 | `8b8a940` | retrieval-agent-loop integration + `runRetrievalAgentLoopWithRecovery` | +31 | $0 |
| 4.1 | `4d0542f` | `long-task/failure-classify.ts` | +57 | $0 |
| 4.2 | `e906114` | `long-task/report.ts` (pilot reproduction at 40% pinned) | +35 | $0 |
| 4.6 | `be8f702` | `long-task/messages-compressor.ts` (closes Phase 3 gate finding) | +24 | $0 |
| 4.7 | `c9bda3d` | compression-engaged-end-to-end assertion | +3 | $0 |

Three analytical phases produced memos in `D:\Projects\PM-Waggle-OS\decisions\` without waggle-os commits:

| Phase | Analytical artifact | Cost |
|---|---|---|
| 4.3 | re-score delta report (12-cell pilot through Phase 1.1 normalize + Phase 4.1 classifier subset + Qwen-as-classifier LLM fallback for ambiguous rationales) | $0.077 (27 LLM fallback calls of 30 max) |
| 4.4 | skills audit sweep (8 TS source files reviewed; 159 SKILL.md scanned with 6 narrative-bias regex patterns; 6 hand-sampled for cross-validation) | $0 |
| 4.5 | tools audit sweep (22 tool TS files; 312 tool descriptions scanned with 4 bias-pattern detectors; multi-step retrieval contract reviewed; pilot retrieval-engagement empirical signal extracted) | $0 |

The 14 commits split cleanly along the Option A discipline: **one commit per work item, halt + PM review per commit, no mid-flight scope expansion**. The three analytical phases broke this commit pattern only because their deliverable was a memo, not a code change — Branch HEAD remained at `c9bda3d` from Phase 4.7 onward.

## 3. Test coverage growth

The pre-Phase-1 packages/agent test count is documented in the Phase 3.1 commit message as **2255 prior to Phase 3.1**, which itself was the seventh waggle-os commit of the sprint. Reconstructing forward from there:

| Checkpoint | packages/agent test count | Cumulative delta from pre-Phase-3.1 |
|---|---|---|
| pre-Phase-3.1 (post 2.3) | 2255 | baseline |
| post-3.1 (`7163114`) | 2297 | +42 |
| post-3.2 (`a41271b`) | 2349 | +94 |
| post-3.3 (`01e32d9`) | 2397 | +142 |
| post-3.4 (`8b8a940`) | 2428 | +173 |
| post-4.1 (`4d0542f`) | 2485 | +230 |
| post-4.2 (`e906114`) | 2520 | +265 |
| post-4.6 (`be8f702`) | 2544 | +289 |
| post-4.7 (`c9bda3d`) | **2547** | **+292** |

For Phases 1.1 / 1.2 / 1.3 / 2.1 (pre-3.1), the per-phase deltas above sum to **+159 tests**. Combined with the +292 from Phase 3+ commits, the sprint added **+451 tests** in total over 14 commits. The Phase 2.2 / 2.3 commits produced refactor-equivalent net changes (no new test files but existing harness tests passed).

Repo-root vitest count, where measured: **5720 → 5689 → 5641 → 5589** (Phase 3.4 → 3.3 → 3.2 → 3.1 reverse-chronologically), each +/- the per-phase delta. Final repo-root state: **5720 passing + 1 skipped** (recorded at Phase 3.4 ratification).

Tsc strict clean was verified at every commit boundary across `packages/agent/tsconfig.json` and (where touching cells) `benchmarks/harness/tsconfig.json`.

## 4. Cost summary

The sprint produced 14 waggle-os commits and 3 analytical memos for a cumulative LLM spend of **$0.077**. The full breakdown:

| Phase | Cost USD | What was spent on |
|---|---|---|
| 1.1 / 1.2 / 1.3 | $0 | unit tests against mocked LLM; no real API |
| 2.1 / 2.2 / 2.3 | $0 | unit tests + pilot wrapper refactor; no new API |
| 3.1 / 3.2 / 3.3 / 3.4 | $0 | unit tests against mocked LlmCallFn; recovery + checkpoint logic deterministic |
| 4.1 / 4.2 / 4.6 / 4.7 | $0 | unit tests against mocked LLM (failure classifier LLM fallback exercised in tests via mock; report.ts pilot reproduction is pure data transformation) |
| 4.3 (analytical) | **$0.077** | 27 Qwen LLM fallback calls for ambiguous-rationale classification (24 of 36 rationales were rule-based-ambiguous and dispatched to LLM; 3 of those returned "AMBIGUOUS" verdicts the LLM also couldn't resolve) |
| 4.4 (analytical) | $0 | 159 SKILL.md regex scan + 6 hand-samples; pure local computation |
| 4.5 (analytical) | $0 | 312 tool description regex scan + multi-step contract review + pilot empirical extraction; pure local computation |

The Phase 4.3 spend (under the $0.20 halt threshold and $0.30 hard cap PM-ratified) was the entire sprint's variable LLM cost. Every other phase produced its deliverable through deterministic transformations against existing data.

## 5. Tier 1 / Tier 2 categorization across analytical phases

The three analytical phases produced complementary categorizations against three different surfaces. Read together they form the empirical basis for the strategic recommendation that drove Faza 1 GEPA authorization.

### Phase 4.3 — judge rationale categorization (failure modes from 2026-04-26 pilot)

36 judge rationales from 12 cells × 3 judges, classified as Tier 1 (Phase 1.1 normalize fix-able) vs Tier 2 (real semantic gap requiring GEPA-level intervention) vs Ambiguous:

| Bucket | Count | Pct | Worst-case T1 ceiling (assume all ambiguous = T1) |
|---|---|---|---|
| T1 | 2 / 36 | 5.6% | — |
| T2 | 26 / 36 | 72.2% | — |
| Ambiguous | 8 / 36 | 22.2% | 27.8% |

Per-hypothesis breakdown:
- **H2** (Opus retrieval lift, B vs A): 11.1% T1 / 55.6% T2 / 33.3% AMB
- **H3** (Qwen solo reaches Opus quality, C vs A): 11.1% T1 / 66.7% T2 / 22.2% AMB
- **H4** (sovereign multiplier, D vs B): **0.0% T1 / 100.0% T2 / 0.0% AMB**

H4's 100% T2 with zero ambiguity is the strongest single signal across the sprint. It is the empirical anchor for the strategic recommendation that Phase 1.1 normalize alone is insufficient to rescue the multiplier teza, and the basis on which CC-2 GEPA Faza 1 was authorized for parallel execution.

A complementary signal from the same Phase 4.3 analysis: Phase 1.1 `benchmark-strict` normalize delta = **0% across all 12 candidate_responses**. The pilot's responses were already format-clean; there were no `<think>` tags / metadata copy / format wrappers for the normalize layer to strip. This is the strongest possible "Tier 1 negative" signal — the classifier didn't miss T1 cases; there were none to find.

### Phase 4.4 — skills audit (159 SKILL.md + 8 TS source files)

| Bucket | Count | Pct |
|---|---|---|
| Tier 0 (model-portable, no action) | 139 of 159 SKILL.md + all 8 TS source files | 87.4% of SKILL.md |
| Tier 1 (description / body rewrite would help) | 20 of 159 | 12.6% |
| Tier 2 (real coverage gap) | 0 candidates | 0% |

The 12.6% Tier 1 rate concentrates in **CoT-imperative phrasing** (12 of 20 cases), with smaller counts of philosophy-keyword (5), first-person plural narrative (3), and marketing-superlative / emoji / decorative emphasis (1 each).

A surface finding that emerged from this audit: **the 2026-04-26 pilot prompts contained NO skill content at all.** The agent's skill recommender was not engaged during the pilot orchestration. Whatever bias exists in skill content was empirically irrelevant to H3/H4 deltas.

The Tier 1 cleanup recommendation was DEFERRED to Sprint 12 cleanup backlog (see §6).

### Phase 4.5 — tools audit (22 tool TS source files + multi-step retrieval contract)

| Bucket | Count | Pct |
|---|---|---|
| Tier 0 (no action) | 309 of 312 descriptions + multi-step contract + all 22 tool files | 99.0% of descriptions |
| Tier 1 (description rewrite would help) | 3 of 312, all in skill-tools.ts | 1.0% |
| Tier 2 (real behavioral gap, GEPA-territory) | 1 — Qwen retrieval engagement gap | empirically anchored |

The Tier 2 finding from this phase is the most operationally-useful signal of the sprint: pilot data shows Qwen retrieval cells made **43% fewer tool calls than Opus retrieval cells across all three tasks** (Qwen 1.33 avg / Opus 2.33 avg). The multi-step retrieval contract is rendered identically across all 5 prompt shapes — same JSON action contract, same per-turn budget, same query guidance. Same surface, divergent behavior. This is by definition NOT a tool-description-format problem; it is a model-strategy / confidence-calibration problem that GEPA evolution should target.

This finding was forwarded to CC-2 via Amendment 2 (`D:\Projects\PM-Waggle-OS\briefs\2026-04-28-cc4-faza1-amendment-2.md`) where it was incorporated as an explicit Faza 1 fitness function component (retrieval_engagement_bonus on Qwen-targeted shapes) and an Acceptance §5 Qwen-shape-specific sub-criterion.

The 3 Tier 1 cases in skill-tools.ts overlap with Phase 4.4's domain and are bundled into the Sprint 12 cleanup backlog rather than counted separately.

## 6. Sprint 12 cleanup backlog handoff

The accumulated Tier 1 work across Phases 4.4 + 4.5 forms a coherent Sprint 12 cleanup backlog: **23 items**, all narrative-bias-style description / body rewrites, none requiring substrate modification or test infrastructure changes.

| Source | Count | Item type |
|---|---|---|
| Phase 4.4 SKILL.md files | 20 | narrative-bias rewrites (12 CoT-imperative + 5 philosophy-keyword + 1 first-person plural + 1 marketing-superlative + 1 emoji-decoration; some files trigger multiple patterns) |
| Phase 4.5 skill-tools.ts borderline cases | 3 | minor narrative-voice cleanup ("you might need" / "you can provide" / "Step-by-step…" param description) |
| **Total** | **23** | |

Effort estimate: **40–60 hours of focused work**. Each rewrite is ~2–3 hours including: read existing description / body, rewrite to imperative-direct format, verify trigger keywords still match, no semantic loss test against the skill recommender's keyword scoring. Generator template (`skill-creator.ts`) is already model-portable, so newly-generated skills will not accumulate new bias — this backlog applies only to the legacy corpus.

This backlog goes into the next sprint brief, not the current sprint. It is explicitly not a Phase 5 NULL-baseline blocker.

## 7. Cross-references

All decision memos cited by absolute path for downstream auditability:

- `D:\Projects\PM-Waggle-OS\decisions\2026-04-27-phase-2-gate-d3-rule-inspection.md` — Phase 2 D3 disambiguation; resolved the substring-match vs judge-consensus methodology gap; substrate-no-regression confirmation
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-27-phase-3-acceptance-gate-results.md` — Phase 3 long-task acceptance gate; H6 INCONCLUSIVE accepted as PASS-with-caveat; surfaced the messages-array compression gap that Phase 4.6 closed
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-27-phase-3-acceptance-gate-pre-run-halt.md` — pre-run scope halt for Phase 3 acceptance gate; cost analysis against super-linear context growth
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-27-phase-2-acceptance-gate-PASS.md` — Phase 2 gate PASS doc with σ-aware band derivation
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-28-phase-4-3-pre-run-halt.md` — Phase 4.3 pre-run halt; surfaced the synthesis-Likert vs factoid schema mismatch that prompted the Option D + LLM fallback methodology shift
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-28-phase-4-3-rescore-delta-report.md` — Phase 4.3 strategic finding; H4 100% T2 verdict; Tier 2 GEPA work authorization basis
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-28-phase-4-4-skills-audit-results.md` — Phase 4.4 skills audit; 12.6% Tier 1 / 0% Tier 2; skill-engagement gap as new finding (deferred)
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-28-phase-4-5-tools-audit-results.md` — Phase 4.5 tools audit; 99.0% Tier 0 / 1.0% Tier 1 / Qwen retrieval-engagement Tier 2 → CC-2 Amendment 2
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-27-memory-sync-repair-CLOSED.md` — Memory Sync Repair closure (PM-authored, referenced for Phase 5 standby predicates)
- `D:\Projects\PM-Waggle-OS\decisions\2026-04-28-gepa-faza1-launch.md` — CC-2 GEPA Faza 1 LOCK doc (PM-authored, references Amendment 2 fitness function update)

The 14 waggle-os commits referenced by 8-char SHA prefix: `4a557cc` `bc5b54f` `12c7334` `a599a07` `5699677` `61743df` `7163114` `a41271b` `01e32d9` `8b8a940` `4d0542f` `e906114` `be8f702` `c9bda3d`. Branch HEAD at sprint closure: `c9bda3d` (Phase 4.7).

## 8. Open items at sprint closure

Four open items carry forward from the agent fix sprint into the broader launch sequence. None of them block the sprint closure itself; they are scope items handed to either CC-2 or the next sprint brief or the PM-side activation queue.

1. **Memory Sync Marko-side activation** — 4 gh commands deferred non-blocking during the sprint. PM has flagged these for activation before Phase 5 fresh runs to ensure parity-check + sync-mind workflows are protecting substrate during Phase 5 LLM work. Out of CC-1 scope.

2. **Phase 5 brief authoring** — gated on three predicates per the Phase 4 kickoff brief: (a) CC-2 GEPA Faza 1 Checkpoint A NULL-baseline reproduction, (b) Memory Sync Marko-side activation, (c) PM-authored Phase 5 brief incorporating Phase 4.3 / 4.4 / 4.5 findings + Faza 1 outcome. ETA: 4–5 days from sprint closure.

3. **GEPA Faza 1 in progress** — CC-2 owns this in a separate session on `prompt-shapes/gepa-evolved/` subdirectory. Memory Sync parity-check workflow active to prevent accidental collision. Out of CC-1 scope; CC-1 will not modify `mind/` or `prompt-shapes/` until Faza 1 completes.

4. **Sprint 12 cleanup backlog** — 23 items consolidated above (§6). Goes into next sprint brief, not current sprint. Out of current scope.

## 9. Lessons learned — patterns for future sprint authoring

Four patterns emerged across the sprint that are worth abstracting for future sprint brief authors and execution sessions.

### Pattern 1: pre-execution rule clarification beats post-execution re-run

The Phase 2 acceptance gate D3 step (`2026-04-27-phase-2-gate-d3-rule-inspection.md`) demonstrated this most clearly. The smoke run produced a 90% trio-strict pass against a v6 baseline of 33.5% — a +56.5pp drift that initially read as a substrate regression. Re-aggregation under v6's exact substring-match rule (the `scoreAccuracy` function in `benchmarks/harness/src/metrics.ts`) shrunk the drift to +6.5pp, well within statistical sample variance for N=20.

The cost of identifying the rule mismatch through a memo + re-aggregation was zero LLM dollars and roughly an hour of analytical time. The cost of re-running the smoke with corrected methodology would have been a fresh ~$0.20 in API spend plus a second wall-clock cycle of waiting for results. The lesson: when an empirical result diverges sharply from baseline expectations, FIRST check whether the methodology rules differ between the run and the baseline. Only re-run if rule alignment confirms the divergence is real.

This generalizes to a sprint-authoring guideline: **rules should be locked at gate authoring time, not gate execution time.** The Phase 2 gate brief did not pre-specify the exact accuracy rule; that gap is what allowed the +56.5pp drift to surface as a methodology artifact rather than a substrate regression. Future gate briefs should cite the rule's source-of-truth file path and line number explicitly.

### Pattern 2: pre-Phase-5 mechanistic categorization is net-positive

Phase 4.3 (`2026-04-28-phase-4-3-rescore-delta-report.md`) was a $0.077 / ~2-hour analytical exercise that produced one definitive empirical signal: H4 = 100% Tier 2. Without that signal, Phase 5 NULL-baseline could have run as the primary remediation pathway, expecting Phase 1.1 normalize to materially close the multiplier gap. The empirical result demonstrated this expectation was unfounded (Phase 1.1 normalize delta = 0% across all 12 cells). Phase 5 NULL-baseline would have produced a NULL result on the multiplier teza and consumed real LLM spend doing so.

The lesson: when an upstream phase's failure mode is ambiguous between two diagnostic categories (here: Tier 1 presentation vs Tier 2 semantic), invest in mechanistic categorization BEFORE re-running. The pre-rerun categorization is typically 1–2 orders of magnitude cheaper than the rerun itself, and a clean categorization can redirect the strategic plan more effectively than the rerun would.

This generalizes to: **failure modes should be classified before they are remediated.** If a sprint plan calls for a re-run pre-Phase-N to validate a fix, consider whether a categorization phase pre-rerun would be cheaper and more strategically useful.

### Pattern 3: cross-stream signal cascade enables real-time empirical-signal integration

Phase 4.5 produced an empirical mechanistic signal (Qwen retrieval engagement gap, −43% vs Opus across all three tasks) that fed directly into CC-2's Amendment 2 BEFORE the Faza 1 scaffold was built. The signal was anchored to actual pilot data (retrieval_calls per cell), not theoretical bias detection.

Because the audit was done as parallel work during a halt-and-PM checkpoint pre Phase 5, the signal arrived at CC-2 in time to be incorporated into Faza 1's fitness function (retrieval_engagement_bonus on Qwen-targeted shapes) and Acceptance §5 sub-criterion. Had Phase 4.5 been executed serially after Faza 1 had already begun scaffolding, the signal would have either delayed Faza 1 or arrived too late to be incorporated cleanly.

The lesson: when parallel work streams produce mechanistic signals about each other's inputs, the halt-and-PM checkpoint discipline creates the synchronization point at which signals can be integrated cleanly. Without halt-and-PM checkpoints, parallel streams either drift out of synchronization or require expensive replanning.

This generalizes to: **halt-and-PM checkpoints are not just for go/no-go decisions; they are also the integration points for cross-stream empirical signals.**

### Pattern 4: halt-and-PM checkpoint discipline ROI

The sprint exercised halt-and-PM checkpoints multiple times where they produced false-positive averts that would otherwise have consumed real LLM spend or cycle time:

- **Phase 2 D3 gate** — caught the methodology gap via memo, no re-run needed
- **Phase 3 acceptance gate pre-run halt** — identified the cost-vs-scope mismatch before any API call (saved ~$45 of unbudgeted Opus spend)
- **Phase 4.3 verdict pre-Phase-5** — categorization phase produced strategic redirect that prevented Phase 5 from running as the primary remediation pathway when Tier 2 GEPA was actually required
- **Phase 4.5 → Faza 1 fitness fork** — empirical signal integrated into CC-2 Amendment 2 pre-scaffold

The ROI of each checkpoint was positive: the pause cost (a memo + a PM ratification round) was small relative to the cost it averted. Even without averting an explicit cost, several checkpoints produced strategic redirection (Phase 4.3, Phase 4.5) that improved the trajectory of subsequent phases.

The lesson: **halt-and-PM checkpoint discipline is a positive-EV practice across a wide range of conditions**, not only when surprises are present. It is worth treating as a default sprint pattern rather than an escalation mechanism.

### Pattern 5: single-commit-per-work-item under Option A discipline scales

The sprint produced 14 commits across roughly two calendar days of focused execution, each commit corresponding to exactly one work item from the sprint plan. Per-commit verification (tsc strict + full vitest run + repo-root vitest where touching cells) was performed before every commit. The Option A discipline — one commit per work item, halt + PM review per commit, no mid-flight scope expansion — held throughout without exception.

This commit cadence had three concrete benefits visible in retrospect: (1) every commit had a clean test delta attributable to that one work item, simplifying the Phase 4.7 + Phase 4.6 ordering decision when Phase 3 acceptance gate findings forced Phase 4.6 ahead of 4.3 in the recommended order; (2) per-commit halt-and-PM rounds caught two pre-coding triggers (Phase 3.2 backoff/jitter conflict, Phase 3.3 hive-mind/Sync-Repair coupling) that would have required rework if surfaced post-commit; (3) the PM-side ratification messages serve as durable per-commit context for the closure memo without requiring chat-history reconstruction.

The lesson: **single-commit-per-work-item is not friction in a multi-phase sprint, it is leverage.** Larger commits would have made the Phase 4.7 ordering reshuffle harder to execute cleanly and would have required reconstructing per-phase test deltas from `git log --stat`. Smaller commits would have fragmented the test verification overhead. The work-item-sized commit boundary is approximately the right unit.

## Closure

Sprint cumulative deliverables: 14 waggle-os commits, 3 analytical memos, +451 tests, 2547/2547 passing, tsc strict clean, $0.077 LLM, zero substrate modifications, zero regressions. Substrate-no-regression confirmed via Phase 2 D3 disambiguation. Tier 2 GEPA work deferred to CC-2 Faza 1 (separate session). Phase 5 NULL-baseline on standby pending Faza 1 Checkpoint C + Memory Sync Marko-side activation + PM-authored Phase 5 brief.

CC-1 sprint scope is complete. Standing by per Phase 4 kickoff brief halt-and-PM checkpoint protocol.

---

**End of agent fix sprint closure memo.**