astra-jev-harness cuts Astra input 27% on one two-file fixture

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Louis posted Oranquelui/astra-jev-harness, MIT, version 0.5.0. On a completed coding run dated September 24, two files and six checks, Astra input tokens fall from 19,198 to 14,011, and the checks stay 6/6. An older three-task note cut files from 28 to 4 while Astra input fell 1.2%. The dollar column is the maintainer's formula, one trial per arm, not a Codex invoice. We did not rerun it.

Oranquelui/astra-jev-harness is a Python harness Louis posted on September 26. The LICENSE file is MIT, copyright 2026 Oranquelui. Version 0.5.0. It wants Python 3.10 or newer and names no third-party packages at runtime. The benchmark notes pin Codex CLI 0.153.2, gpt-6-astra, and jev-1.13.0. The September 26 post quotes his September 24 note about files. We did not rerun the arms. Each arm in the file is one trial, and the dollar column is his formula, not a bill from Codex.

The older number is a run dated September 22, three synthetic tasks. Files go from 28 to 4, which is 85.7%. Characters in the harness prompt go from 4,309 to 2,581, which is 40.1%. Astra input tokens go from 42,714 to 42,199, which is 1.2%. Output tokens stay at 175. Elapsed time goes from 18.51 seconds to 21.53 seconds. Jev’s side of that run is 4,094 input tokens and 1.62 seconds of API time. Both arms pass 22 of 22 checks. The file-count drop and the token drop are different sizes.

The completed coding run is dated September 24, source commit 9eb422976c42d66dba4f92596a43b2e89a6897c8, on a build he marks as v0.3.0. The fixture is two files: a 75-byte main.py, and 27,278 bytes of gardening prose. Six checks are held out. main.py is pinned, so the model is not being asked to remember the file. On the Extra High setting, Astra input tokens go from 19,198 to 14,011, a 27.0% cut. Output goes from 193 to 126. Jev is called twice, 6,784 input tokens and 76 output tokens. Elapsed time goes from 12.778 seconds to 11.851 seconds. His API-equivalent price goes from $0.201630 to $0.146694928. The formula in the note is (14011 × 10 + 126 × 50 + 6784 × 0.042) / 1e6. Rates he recorded that day: Astra input $10 per million tokens, cache read $1, cache write $12.50, output $50. Jev input $0.042 per million, output $0. All four Astra calls in the run report zero cache tokens. Checks stay at 6/6.

Medium, which the note says is still the distributed CLI default, cuts input from 19,204 to 14,013, also 27.0%. The dollar figure goes from $0.195190 to $0.143564928. Elapsed time goes from 9.074 seconds to 12.217 seconds.

A selection-only pair, v0.2.0 against a v0.3.0 candidate, keeps 75 bytes where the older build kept 27,353. That is a 99.73% cut in retained bytes. Jev input on that pair rises from 392 tokens to 6,784, and the estimated Jev price rises from $0.000016464 to $0.000284928. Astra’s price for that pair is not in the file. Auto mode uses a threshold of 12,000 source bytes and makes no Jev call on the 75-byte file.

Version 0.5.0 adds a progress-log smoke. Stdout falls from 19,885 bytes to 7,601, which is 61.8%, with 5 of 5 required facts still present. Jev is two calls, 7,172 and 195 tokens. The note says this smoke is not a measurement of Astra tokens or of task time. A later context-only pass retains all 4 files it was given. Replaying a batch against a per-file pass moves 34,852 bytes to 34,634, which is 0.63%, and 15 files to 14, with no new API calls. The README says the full offline suite is 141 tests. The benchmarks note says 119 after a follow-up, and 114 at the selection stage. A Claude Code 2.1.281 check on September 24 uses --mode local, makes zero Jev calls, and is not a savings run.

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Oranquelui/astra-jev-harness, version 0.5.0. LICENSE is MIT, Copyright (c) 2026 Oranquelui. Python 3.10 or newer, no third-party runtime dependencies. The notes name Codex CLI 0.153.2, gpt-6-astra, and jev-1.13.0.

The September 26 post quotes a September 24 post. Historical run, 2026-09-22, three synthetic tasks: files 28 to 4 (85.7%), harness prompt characters 4,309 to 2,581 (40.1%), Astra input tokens 42,714 to 42,199 (1.2%), output 175 and 175, elapsed 18.51 s to 21.53 s (+16.3%), Jev input 4,094 tokens, Jev API 1.62 s, checks 22/22 on both arms.

Completed coding run, 2026-09-24, source commit 9eb422976c42d66dba4f92596a43b2e89a6897c8, based on v0.3.0. The fixture is a 75-byte main.py plus 27,278 bytes of gardening prose. Six held-out checks.

main.py is pinned, so the task is not a recall test. Extra High: Astra input 19,198 to 14,011 (-27.0%), output 193 to 126, Jev 2 calls and 6,784 / 76 tokens, elapsed 12.778 s to 11.851 s (-7.3%), API-equivalent USD 0.201630 to 0.146694928 (-27.2%), checks 6/6.

The note's formula is (14011 times 10 plus 126 times 50 plus 6784 times 0.042) divided by 1e6. Rates recorded 2026-09-24: Astra input $10 per million, cache read $1, cache write $12.50, output $50. Jev input $0.042 per million, output $0.

All four Astra calls in that run report zero cache tokens. Medium: input 19,204 to 14,013 (-27.0%), USD 0.195190 to 0.143564928 (-26.4%), elapsed 9.074 s to 12.217 s (+34.6%). The distributed CLI default remains medium.

Selection-only, v0.2.0 against a v0.3.0 candidate: retained bytes 27,353 to 75 (-99.73%), Jev input 392 to 6,784 tokens, estimated Jev USD 0.000016464 to 0.000284928. Astra cost for that pair was not measured. Auto mode uses a 12,000-byte threshold and makes zero Jev calls on the 75-byte file.

v0.5.0 progress-log smoke: stdout 19,885 to 7,601 bytes (61.8%), 5 of 5 required facts, Jev 2 calls and 7,172 / 195 tokens. The note says that smoke is not an Astra token measurement. A later context-only pass keeps 4 of 4 files.

A batch replay against a per-file replay is 34,852 to 34,634 bytes (0.63%) and 15 to 14 files, with no new API calls. The README says 141 offline tests. The benchmarks note says 119 after a follow-up, and 114 at the selection stage.

A 2026-09-24 Claude Code 2.1.281 check uses --mode local, zero Jev calls, and is not a savings bench. Each arm is one trial. We did not rerun it.

Compare

jev-gateway asks which tool a coding agent should call, and the README there has no token table like this one. CLM-8B's speed claim is about scoring a fixed action list, not about shrinking a Codex prompt. The 27% figure is Astra input tokens on one two-file fixture.

The 28-to-4 file count is the September 22 run, where Astra input fell 1.2%.

Terms

-27.0%
Astra input tokens on the September 24 Extra High run, 19,198 to 14,011, six checks still passing. Medium is 19,204 to 14,013. The September 22 three-task run cut files from 28 to 4 and cut Astra input 1.2%.
0.146694928
API-equivalent dollars for the harness arm on Extra High. The note computes (14011 times 10 plus 126 times 50 plus 6784 times 0.042) divided by 1e6. The uninstrumented arm is 0.201630. This is not a Codex invoice.
12,000
Auto mode's source-byte threshold. The 75-byte main.py makes zero Jev calls. The 27,278-byte gardening file is what the selection pass is for.

Sources

  1. Louis, the harness
  2. Louis, 28 files to 4
  3. Oranquelui/astra-jev-harness