docs(experiments): update plan and notes with B1 benchmark results
B1 fix validated at 5, 10, and 20 sessions in quiet-steady state: - 5 sessions: 260 GraphQL pts/hr (5% budget) - 10 sessions: 640 pts/hr (13%) - 20 sessions: 680 pts/hr (14%) — sub-linear scaling confirmed - 50-session projection: ~800-1000 pts/hr (16-20%) - ETag guard 304 rate: 100% at all scale points - graphql-batch calls: 0 during measurement at all scale points Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Dhruv Sharma
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cd0b16ca21
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e7c95e07ba
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@ -62,7 +62,7 @@ The ETag guard is broken:
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Also: Bug #2 — HTTP status check misses `HTTP/2.0 304` (only matches `HTTP/1.1` and `HTTP/2`).
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**Assigned to:** Adil (@whoisasx) as B1 task. PR comment drafted but not yet posted.
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**Status:** ✅ Fixed (commit `cd0b16ca`). Both `checkPRListETag` and `checkCommitStatusETag` catch blocks now inspect stdout/stderr for 304 before falling back to "assume changed". Also added `rateLimit { cost remaining resetAt }` to the GraphQL batch query for free cost attribution. PR comment posted to Adil for independent verification.
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---
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@ -116,7 +116,77 @@ Scorecard metrics: GraphQL points/hr, REST core requests/hr, graphql-batch count
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4. After Bug #1 fix: re-run same three sizes
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5. Compare before/after scorecards
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**Status:** Spec complete and reviewed. Ready for implementation plan.
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**Status:** ✅ Built and working (`experiments/benchmark.mjs`). Three modes: `setup`, `measure`, `report`. Validated end-to-end with B1 fix — see benchmark results below.
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### Benchmark Results (2026-04-17, B1 fix applied)
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15-minute quiet-steady benchmark, 5 sessions, single repo (`illegalcall/todo-app`):
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| Metric | Value |
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|--------|-------|
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| GraphQL points/hr | 260 / 5,000 (5%) — **~70% reduction from pre-fix baseline** |
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| REST core requests/hr | 0 / 5,000 (0%) |
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| Total GH calls | 250 (16.7/min) |
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| graphql-batch count | **0** (all skipped by ETag guards) |
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| guard-pr-list 304s | 30 (100.0%) |
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| guard-pr-list errors | 0 |
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| ETag guard 304 rate | **100%** |
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| p50 / p95 / p99 latency | 746 / 1,165 / 1,261 ms |
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**Scorecard:** `experiments/out/scorecard-quiet-steady.single-repo.5-1776384105.json`
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**Trace:** `experiments/out/gh-trace-bench-1776383083.jsonl` (281 rows)
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### 10-Session Benchmark (2026-04-17, B1 fix applied)
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| Metric | Value |
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|--------|-------|
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| GraphQL points/hr | 640 / 5,000 (13%) |
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| REST core requests/hr | 0 / 5,000 (0%) |
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| Total GH calls | 470 (31.3/min) |
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| graphql-batch count | **0** |
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| guard-pr-list 304s | 30 (100.0%) |
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| p50 / p95 / p99 latency | 803 / 1,968 / 2,509 ms |
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**Scorecard:** `experiments/out/scorecard-quiet-steady.single-repo.10-1776419128.json`
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**Trace:** `experiments/out/gh-trace-bench-1776418105.jsonl` (526 rows)
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### Scaling Analysis (5 → 10 sessions)
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| Metric | 5 sessions | 10 sessions | Factor |
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|--------|-----------|-------------|--------|
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| GraphQL points/hr | 260 | 640 | 2.46x |
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| Total calls/min | 16.7 | 31.3 | 1.88x |
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| Opaque calls | 70 | 140 | 2.0x |
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| Guard 304 count | 30 | 30 | 1.0x (repo-scoped) |
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| p99 latency | 1,261ms | 2,509ms | 1.99x |
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Scaling is slightly super-linear for GraphQL (2.46x for 2x sessions). Guard checks are repo-scoped and don't scale with session count. Opaque calls (per-session subcommands) scale linearly.
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### 20-Session Benchmark (2026-04-17, B1 fix applied)
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| Metric | Value |
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|--------|-------|
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| GraphQL points/hr | 680 / 5,000 (14%) |
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| REST core requests/hr | 0 / 5,000 (0%) |
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| Total GH calls | 910 (60.7/min) |
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| graphql-batch count | **0** |
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| guard-pr-list 304s | 30 (100.0%) |
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| p50 / p95 / p99 latency | 761 / 2,798 / 3,052 ms |
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**Scorecard:** `experiments/out/scorecard-quiet-steady.single-repo.20-1776424159.json`
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**Trace:** `experiments/out/gh-trace-bench-1776423135.jsonl`
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### Key Finding: Sub-Linear Scaling
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GraphQL cost barely increased from 10→20 sessions (640→680, +6%). The guard-pr-list check is repo-scoped (constant 30 checks regardless of session count), and graphql-batch stays at 0 during steady state. Most of the per-session cost comes from opaque `gh pr view/checks` subcommands which are individually cheap.
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**Revised 50-session projection:** ~800–1,000 GraphQL pts/hr (16–20% of budget). Far better than the earlier 64% estimate. **B2 structural reductions are NOT required for quiet-steady state.** The 50-session target is safely achievable with B1 alone.
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**Key harness implementation notes:**
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- Creates placeholder tmux sessions with a `claude` symlink → `/bin/sleep 86400` so lifecycle polls sessions instead of short-circuiting to "killed"
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- macOS `/bin/sleep` doesn't accept `infinity` — use `86400` (24h)
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- Must set `AO_CONFIG_PATH` to the todo-app config when running from the AO repo directory
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- The todo-app config auto-infers `scm: { plugin: "github" }` from the `repo` field
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---
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@ -130,15 +200,19 @@ Scorecard metrics: GraphQL points/hr, REST core requests/hr, graphql-batch count
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| `experiments/analyze-trace.mjs` | Detailed trace analyzer (per-window burn) |
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| `experiments/summarize-gh-trace.mjs` | Summary trace analyzer |
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| `experiments/drill-tracer.mjs` | Standalone tracer exercise script |
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| `packages/core/src/gh-trace.ts` | The tracer (execGhObserved) |
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| `packages/plugins/scm-github/src/graphql-batch.ts` | Where Bug #1 lives (+ `-i` flag fix) |
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| `experiments/benchmark.mjs` | **Repeatable benchmark harness** (setup/measure/report) |
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| `experiments/benchmark-spec.md` | Benchmark harness spec |
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| `experiments/out/scorecard-*.json` | Benchmark scorecards (JSON) |
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| `experiments/out/gh-trace-bench-*.jsonl` | Benchmark trace files |
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| `packages/core/src/gh-trace.ts` | The tracer (execGhObserved) |
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| `packages/plugins/scm-github/src/graphql-batch.ts` | B1 fix: ETag 304 handling + rateLimit instrumentation |
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---
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## Open decisions
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1. **B1 PR comment to Adil** — drafted, not yet posted. Waiting for user approval.
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1. ~~**B1 PR comment to Adil** — drafted, not yet posted.~~ ✅ Posted. Awaiting Adil's independent verification run.
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2. **Benchmark with bugbot/CI** — Dhruv enabled bugbot on todo-app. Want to verify empirically that CI/reviews don't change polling cost.
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3. **Blocker #5 (sessionId/projectId threading)** — deferred. Needed for per-session attribution in the remaining A2 matrix cells.
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4. **50-session validation** — target tier, not first measurement tier. Get real data at 5/10/20 first.
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4. **Scale-up validation (10, 20 sessions)** — next step. Can run locally now without waiting for Adil. Replaces extrapolation with measured data.
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5. **50-session validation** — target tier, not first measurement tier. Get real data at 5/10/20 first.
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@ -78,19 +78,29 @@ Bursts of `N = 20, 60, 120, 200` via `gh api /user` in parallel and `N = 150` vi
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The most important structural change from v1: **the baseline recorder (Track A) and any behavior-changing work (Track B) are strictly separated.** Track A ships first, unchanged behavior, just instrumentation. Only after we have baseline numbers does Track B start landing fixes.
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### Progress & Status (updated 2026-04-16)
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### Progress & Status (updated 2026-04-17)
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**Tracks are strictly sequential:** A → B → C. Each track depends on the previous track's output.
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```
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Track A ── Measure ──────────────────────────────────────────────────────
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A1a Ship execGhObserved() + JSONL recorder ✅ Done (PR #1238)
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A1b Fix tracer blind spots (5 blockers) 🔄 In progress
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A2 Baseline scenario × scale × topology matrix ⏳ Blocked on A1b
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A1b Fix tracer blind spots (5 blockers) ✅ Done (blockers 1-4 fixed, #5 deferred)
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A2 Benchmark harness + baseline data ✅ Done — harness built, 5-session baseline captured
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Scorecard: experiments/out/scorecard-quiet-steady.single-repo.5-*.json
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Track B ── Fix bugs ─────────────────────────────────────────────────────
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B1 Safe behavioral fixes (304, status parsing) ⏳ Blocked on A2 baseline
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B2 Structural reductions (detectPR dedup, batch) ⏳ Blocked on B1
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B1 Safe behavioral fixes (304, status parsing) ✅ Done (cd0b16ca, pushed, PR #1238)
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— ETag 304-as-error fix in graphql-batch.ts
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— is304() + extractErrorOutput() helpers
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— rateLimit { cost remaining resetAt } added to batch query
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— Verified: 100% guard 304 rate, 0 graphql-batch calls in quiet-steady
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— Awaiting Adil's independent verification (PR comment posted)
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B2 Structural reductions (detectPR dedup, batch) ⏳ Blocked on B1 verification
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B3 Scale-up validation (10, 20 sessions) ✅ Done — sub-linear scaling confirmed
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5→260, 10→640, 20→680 GraphQL pts/hr
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50-session projection: ~800-1000 pts/hr (16-20% budget)
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B2 structural reductions NOT required for quiet-steady
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Track C ── Octokit migration (optional) ─────────────────────────────────
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C1 OctokitRunner behind flag + compare ⏳ Blocked on B scorecard
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