crowdsourced runner
Sloba's chat directive 2026-05-06: "this project is preparation for
going public ... ship the harness along so others can join in."
The repo's original purpose (Ben's catalogue + 21 reference run
ledgers, shipped 2026-05-05) stays intact. This commit ADDS a second
purpose: a portable harness + agent runbook so a friend's coding agent
can clone, read CLAUDE.md, run the same suite on the friend's hardware,
and submit results back as a PR.
What landed:
CLAUDE.md + AGENTS.md (byte-identical, ~520 lines)
Full agent runbook: hardware probe, runtime + model selection,
canonical knob reference (Sloba's Pavilion methodology values),
hardware-adaptation decision rules, run-instructions, output-schema
templates for hardware.json + metadata.json + run.md, PR submission
flow (fork → branch → push → PR; nothing auto-merges), privacy
guardrails, methodology lineage. Per Sloba's Q3 directive: the
runbook explicitly tells the friend's agent to ADAPT to hardware
reality and document deviations rather than blindly run defaults.
CONTRIBUTING.md (~110 lines)
Human-readable companion for the friend (not the agent). What you
need, how it works, what we ask, what maintainers commit to,
license, code-of-conduct short version.
harness/
├── README.md Technical readme for the harness folder
├── run_benchmark.py ~520 LOC runner. Stdlib-only. Adapted from
│ WeeyugaWeb/scripts/benchmarks/run_pavilion_weeyuga.py
│ v3 with the cluster-internal IP defaults
│ (10.8.0.x) replaced by 127.0.0.1:11434, the
│ cluster /v1/cluster/* endpoints removed, the
│ canonical-suite paths under ~/Documents/MyServers
│ replaced by harness/suites/ paths, the git-sha
│ enforcement on WeeyugaWeb dropped, and the
│ output written under submissions/<handle>/<tag>/
│ instead of docs/BENCHMARKS/runs/. Supports all
│ six suite phases via --phases, plus 'all'.
├── prompts.py Verbatim copy of the canonical 3 frozen prompts
│ (P-EASY/P-MEDIUM/P-HARD) from
│ WeeyugaWeb/scripts/benchmarks/prompts.py.
├── requirements.txt Empty by intent (stdlib-only); placeholder for
│ pip-tools / agent auto-install patterns.
├── .gitignore __pycache__/ etc.
└── suites/ Six bundled JSON suites copied verbatim from
Sloba's MyServers/instances/vps-81-17-99-14/telemetry/:
small_model_eval_questions.json, python_task_suite_questions.json,
parallel_qwen_same_model_20q_suite.json,
parallel_qwen_mixed_model_20q_suite.json,
python_context_edge_append_questions.json,
python_context_edge_suite_only.json.
submissions/
README.md Folder convention + naming + reviewability rules
EXAMPLE/mac-m1-8gb/run-00000000-...-000000000000/
Synthetic-but-shape-complete contribution template:
manifest.json, hardware.json, run.jsonl (5 example lines),
metadata.json, run.md (with privacy attestation, methodology
deviations, reproducibility command). Marked as synthetic at
the top so future analysis doesn't accidentally cite it.
LICENSE-MIT
MIT for harness/*.py and future helper code. Existing LICENSE
(CC-BY-4.0) covers data files.
README.md (modified)
Updated to reflect dual purpose. Layout diagram updated.
Maintainer credits: Ben for catalogue/methodology + Bane for harness.
Contributor quick-start added. Status table extended.
Privacy posture:
- All 6 suite JSON files privacy-scanned for cluster IPs / hostnames /
paths / tokens. Two prompts contain project names ("MyBoard" auth
debugging in 20Q-Q14, generic SSH troubleshooting in 5Q-Q03);
flagged in chat for Sloba's review. Otherwise clean.
- run_benchmark.py default target_url is 127.0.0.1:11434 (no internal
IPs leaked).
- manifest.json captures host_hostname_short via socket.gethostname()
.split('.')[0] — agent should review before PR if hostname is
sensitive.
- CLAUDE.md §8 spells out the privacy-grep before push.
Verification:
- py_compile run_benchmark.py: OK
- --help renders cleanly
- All 6 suite JSON files: valid
- All 4 example JSON files: valid
- Example run.jsonl (5 lines): valid
This commit lands on branch feature/runner-and-agent-instructions.
NOT pushed to main; staying on the feature branch until Sloba reviews
on Gitea and merges. Bus dispatch to Ben + Sam announcing the
architectural pivot lives in the WeeyugaWeb coordination repo.
3.8 KiB
EXAMPLE — mac-m1-8gb — qwen3.5:0.8b — 2026-05-12
This is a synthetic example so contributors can see the shape of a submission end-to-end. The numbers are plausible but not from a real run. Don't cite this directory in analysis. Don't copy-paste these numbers. Real submissions live alongside this folder under
submissions/<handle>/.
Run ID: 00000000-0000-0000-0000-000000000000
Submitter: EXAMPLE (synthetic)
Hardware: Apple MacBook Air M1, 8 GB unified, macOS 14.5
Runtime: Ollama 0.5.13 (default settings; NUM_PARALLEL=1, KEEP_ALIVE=5m)
Models: qwen3.5:0.8b
Phases run: hello, 5q, 20q
Phases skipped: parallel_same, parallel_mixed, edge_append, edge_suite — RAM constraint, parallel suites need ≥2 warm copies of the model and 8 GB unified didn't fit; edge suites time-budget skipped (would have been ~30 min more)
Headline numbers
| Cell | Phase | n_calls | tok/s mean | tok/s p50 | duration p50 | format_ok rate |
|---|---|---|---|---|---|---|
| mac-m1:ollama:qwen3.5:0.8b | hello | 1 | 22.7 | 22.7 | 1.8 s | n/a |
| mac-m1:ollama:qwen3.5:0.8b | 5q | 5 | 21.4 | 22.3 | 4.2 s | 80% |
| mac-m1:ollama:qwen3.5:0.8b | 20q | 20 | 17.0 | 20.9 | 9.6 s | 70% |
What I observed (qualitative)
- Hello-call cold-start was fast — 1.8 s including initial model load. Ollama reports the 0.8B GGUF as ~600 MB; on Apple Silicon unified memory this loads in well under 2 s.
- 5Q tasks were uniformly handled — all five formats (bash, python,
shell, four-numbered-steps, json) parsed correctly except one
(Q3, "shell_lines" — model started with
1.numbered list instead of raw shell command). - 20Q tasks bifurcated — the simple ones (Q01-Q08) ran at full ~20 tok/s with high format-correctness; the longer ones (Q09+ with multi-paragraph context) saw throughput drop to ~12-15 tok/s, with format_ok dropping to ~60%. p95 duration of 41 s was Q14 (the MyBoard triage prompt — long context, mixed format).
- No errors, no timeouts. Cleanest run was on AC power; the laptop fan never spun up.
Methodology
Followed the canonical Pavilion methodology with these deviations:
- NUM_PARALLEL=1 instead of canonical 3 — laptop, not server; one slot is enough for sequential per-model-block execution.
- KEEP_ALIVE=5m instead of canonical 2400h — laptop, no need to pin.
- Phases
parallel_same,parallel_mixed,edge_append,edge_suiteskipped — see top of file. Run not eligible forflagshipgrade, intended asstandard.
Caveats
- 8 GB unified RAM is below the comfort floor for parallel suites with this model; results above are NOT a refutation of the canonical parallel numbers — they're from a different shape of run.
- macOS Spotlight indexing was disabled before the run started. If you rerun without disabling, expect ~5-10% additional variance from background I/O.
format_okrate of 70% on 20Q is consistent with Sloba's flagship 20Q numbers for qwen3.5:0.8b on Pavilion (~74-78% in the v1 baseline) within measurement noise.
Reproducibility
ollama pull qwen3.5:0.8b
ollama serve # in a separate terminal
python3 harness/run_benchmark.py \
--target-url http://127.0.0.1:11434 \
--models qwen3.5:0.8b \
--cell-id-prefix mac-m1:ollama \
--phases hello,5q,20q \
--submitter-handle alice \
--device-tag mac-m1-8gb
Took ~16 minutes wall-clock on this hardware.
Privacy attestation
I scanned run.jsonl for personal paths, API tokens, SSH keys, and
home-directory leakage:
grep -nE "Bearer |sk-|api_key|/Users/|/home/|password|ssh-rsa|ssh-ed25519" \
submissions/EXAMPLE/mac-m1-8gb/run-00000000-0000-0000-0000-000000000000/*
No matches outside the SSH-troubleshooting prompt in 5Q (Q3) which is intentional curriculum. Safe to ship.
— EXAMPLE (synthetic; not a real contributor)