97a9245d9e
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.
93 lines
3.8 KiB
Markdown
93 lines
3.8 KiB
Markdown
# EXAMPLE — mac-m1-8gb — qwen3.5:0.8b — 2026-05-12
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> **This is a synthetic example so contributors can see the shape of a
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> submission end-to-end. The numbers are plausible but not from a real run.
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> Don't cite this directory in analysis. Don't copy-paste these numbers.
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> Real submissions live alongside this folder under `submissions/<handle>/`.**
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**Run ID:** `00000000-0000-0000-0000-000000000000`
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**Submitter:** EXAMPLE (synthetic)
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**Hardware:** Apple MacBook Air M1, 8 GB unified, macOS 14.5
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**Runtime:** Ollama 0.5.13 (default settings; NUM_PARALLEL=1, KEEP_ALIVE=5m)
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**Models:** qwen3.5:0.8b
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**Phases run:** hello, 5q, 20q
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**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)
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## Headline numbers
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| Cell | Phase | n_calls | tok/s mean | tok/s p50 | duration p50 | format_ok rate |
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| mac-m1:ollama:qwen3.5:0.8b | hello | 1 | 22.7 | 22.7 | 1.8 s | n/a |
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| mac-m1:ollama:qwen3.5:0.8b | 5q | 5 | 21.4 | 22.3 | 4.2 s | 80% |
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| mac-m1:ollama:qwen3.5:0.8b | 20q | 20 | 17.0 | 20.9 | 9.6 s | 70% |
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## What I observed (qualitative)
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- **Hello-call cold-start was fast** — 1.8 s including initial model load.
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Ollama reports the 0.8B GGUF as ~600 MB; on Apple Silicon unified memory
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this loads in well under 2 s.
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- **5Q tasks were uniformly handled** — all five formats (bash, python,
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shell, four-numbered-steps, json) parsed correctly except one
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(Q3, "shell_lines" — model started with `1.` numbered list instead of
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raw shell command).
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- **20Q tasks bifurcated** — the simple ones (Q01-Q08) ran at full
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~20 tok/s with high format-correctness; the longer ones (Q09+ with
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multi-paragraph context) saw throughput drop to ~12-15 tok/s, with
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format_ok dropping to ~60%. p95 duration of 41 s was Q14 (the MyBoard
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triage prompt — long context, mixed format).
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- **No errors, no timeouts.** Cleanest run was on AC power; the laptop
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fan never spun up.
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## Methodology
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Followed the canonical Pavilion methodology with these deviations:
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- **NUM_PARALLEL=1** instead of canonical 3 — laptop, not server; one slot
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is enough for sequential per-model-block execution.
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- **KEEP_ALIVE=5m** instead of canonical 2400h — laptop, no need to pin.
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- **Phases `parallel_same`, `parallel_mixed`, `edge_append`, `edge_suite`
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skipped** — see top of file. Run not eligible for `flagship` grade,
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intended as `standard`.
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## Caveats
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- 8 GB unified RAM is below the comfort floor for parallel suites with this
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model; results above are NOT a refutation of the canonical parallel
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numbers — they're from a different shape of run.
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- macOS Spotlight indexing was disabled before the run started. If you
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rerun without disabling, expect ~5-10% additional variance from
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background I/O.
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- `format_ok` rate of 70% on 20Q is consistent with Sloba's flagship 20Q
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numbers for qwen3.5:0.8b on Pavilion (~74-78% in the v1 baseline) within
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measurement noise.
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## Reproducibility
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```
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ollama pull qwen3.5:0.8b
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ollama serve # in a separate terminal
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python3 harness/run_benchmark.py \
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--target-url http://127.0.0.1:11434 \
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--models qwen3.5:0.8b \
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--cell-id-prefix mac-m1:ollama \
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--phases hello,5q,20q \
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--submitter-handle alice \
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--device-tag mac-m1-8gb
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```
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Took ~16 minutes wall-clock on this hardware.
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## Privacy attestation
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I scanned `run.jsonl` for personal paths, API tokens, SSH keys, and
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home-directory leakage:
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```
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grep -nE "Bearer |sk-|api_key|/Users/|/home/|password|ssh-rsa|ssh-ed25519" \
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submissions/EXAMPLE/mac-m1-8gb/run-00000000-0000-0000-0000-000000000000/*
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```
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No matches outside the SSH-troubleshooting prompt in 5Q (Q3) which is
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intentional curriculum. Safe to ship.
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— EXAMPLE (synthetic; not a real contributor)
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