Benchmark the harness. Not the hype.
A warmed, same-model draft comparison of eleven terminal agent harnesses across 132 fresh-state runs—with correctness, scope, process health, and latency kept separate.
Algo CLI achieved 12/12 verified runs and ranked #1 in this four-task, same-model local draft benchmark. 5 harnesses completed every run with checker, process, and scope gates intact.
Coding starts with 73.2–74.3% less tool context.
Instead of sending all 56 action schemas on every turn, Algo CLI ranks a bounded task-relevant catalog. These deterministic estimates cover harness-supplied schema context; they are not provider billing or model-output tokens.
Median reduction across all nine scenarios was 79.6%; typed-program intermediate context fell 97.2%. These results have not been independently reproduced. Inspect the JSON evidence →
Correctness, process, and scope all count.
A verified run requires the external checker to pass, the harness process to finish cleanly, baseline failure to be proven, protected inputs to remain intact, and every workspace edit to stay in the task allowlist.
Tail latency stays visible.
Ranking considers median duration only after checker, scope, and process rates. p95 exposes slow or timed-out runs that a median can hide; the shared model warmup is excluded from every score.
Four distinct evidence problems.
Each harness receives the same frozen prompts and fixtures. The matrix reports checker passes, not subjective answer grades.
The complete ranked table.
Ranking sorts checker pass rate, scope pass rate, clean-process rate, then median duration. Speed cannot outrank correctness or scope discipline.
| Rank | Harness | Checker | Verified | Scope | Median | p95 |
|---|---|---|---|---|---|---|
| 01 | Algo CLI | 12/12 | 12/12 | 12/12 | 32.0s | 287.3s |
| 02 | Oh My Pi | 12/12 | 12/12 | 12/12 | 38.5s | 322.4s |
| 03 | Pi | 12/12 | 12/12 | 12/12 | 42.9s | 209.3s |
| 04 | Codex CLI | 12/12 | 12/12 | 12/12 | 44.5s | 308.2s |
| 05 | Hermes Agent | 12/12 | 12/12 | 12/12 | 70.3s | 335.8s |
| 06 | OpenClaw | 12/12 | 11/12 | 12/12 | 73.2s | 360.0s |
| 07 | OpenCode | 10/12 | 10/12 | 12/12 | 59.7s | 360.0s |
| 08 | Claude Code | 10/12 | 10/12 | 12/12 | 63.7s | 360.0s |
| 09 | Copilot CLI | 10/12 | 10/12 | 10/12 | 88.3s | 360.0s |
| 10 | Droid | 7/12 | 6/12 | 12/12 | 138.4s | 360.1s |
| 11 | Goose | 7/12 | 7/12 | 10/12 | 73.6s | 360.0s |
Same model. Warm start. Fresh state.
Every scored run used local Ollama with qwen3.6:35b-mlx on Apple M5 Max (18-core CPU, 48 GB unified memory), a 360-second cap, isolated harness state, identical task fixtures, and deterministic cyclic rotation. Host OS: macOS 27.0.
task sha256:1e0b9ee182c7599ea5d45166fea0b6f257ec01598bb35b2eff57c104be5c3f45
- Code repairRepair a failing parser in a small Python repository and pass its external checker.
- Misleading-state safety trapUse authoritative evidence instead of stale documentation or a protected decoy config.
- Live-files memory conflictReconcile stale retrieved context against current project files, with live state winning.
- Medium-repository reconciliationRoll out a verified change across differently shaped service configs while preserving protected inputs and producing a receipt.
Blocked is not zero.
Products without a deterministic, authorized headless path were excluded instead of receiving invented scores.
adapter is not implemented
installed Cline binary exits without a usable CLI response
license acceptance required before installation
no identifiable Mercury harness or headless CLI was supplied
desktop UI has no deterministic headless benchmark adapter
desktop UI has no deterministic headless benchmark adapter
Ollama documentation category, not a separate harness
What the evidence supports
Algo CLI achieved 12/12 verified runs and ranked #1 in this four-task, same-model local draft benchmark. Separately: In two deterministic coding scenarios, Algo CLI used 73.2% to 74.3% fewer tool-schema tokens than exposing the full 56-tool catalog while recalling every required tool.
What it does not support
Four draft tasks, one local model, one machine, and 3 repetitions per cell do not support a universal superiority or native-model-power claim. Timing includes harness and model work but excludes the shared warmup. Raw artifacts are retained locally because they can expose paths and model output; only sanitized aggregates are published. Results have not been independently reproduced. This deterministic, model-free harness benchmark measures estimated tool-schema and intermediate-result context. It does not measure model output tokens, end-to-end coding quality, provider billing, or superiority over another harness. Token estimates use a documented characters-divided-by-four approximation and results have not been independently reproduced.