Loop Engineering v0.2 — Reproduction Challenge

[KanakMalpani]

Goal

First external reproduction of the Loop Engineering stack without maintainer help.

Steps (≤60 min)

Follow REPRODUCE.md:

1. Validate an LSS spec (python scripts/validate_loop_library.py)
2. Run python examples/reflection-loop/run.py
3. Emit LES JSON via les_calculator.py
4. (Optional) Compare to ALS-T2 baseline

Report format

Reply with title Reproduction report — [your handle] and include:

• Python version
• Validator output
• Reflection-loop snippet
• LES JSON
• Time to complete

Maintainer baseline: ALS-T2 structural LES 70.4, 5/5 mock runs.

Links: ECOSYSTEM_VERSIONS.md · LOOPNET.md · Good first issues

[KanakMalpani]

Reproduction report — maintainer dry-run

Verified REPRODUCE.md locally (~25 min).

Check	Result
validate_loop_library	OK: all 10
reflection-loop	Success: True, quality 0.84
LoopNet v0.2	545 records
loopbench LB-CR-1	success_at_k=1.0, LES 86.7
LoopGym replay	OK on v0.2 record

Structural LES (autonomous-debugger): 74.5. Full run: benchmarks/results/lb-cr-1-run.json.

Documents the path; not counted as external reproduction.

[KanakMalpani]

Reproduction report — independent replay (2026-06-24)

Completed REPRODUCE.md end-to-end (~2 min automated replay on maintainer machine).

Checklist

• Python 3.14.3
• Packages: pyyaml 6.0.3, jsonschema 4.25.1, loopgym 0.1.0, loopbench 0.1.0
• Validator: OK: 9 atomic + 5 composed specs valid
• Reflection loop: Success: True | Quality 0.84
• LES JSON (autonomous-debugger): composite 74.5
• LoopNet explore: 545 records loaded from HF
• LoopBench LB-CR-1 (seed 0): Success@k 1.0, LES 87.8

LES JSON (structural)

{
  "loop_name": "autonomous-debugger",
  "les": 74.5,
  "categories": {
    "effectiveness": 1.0,
    "speed": 0.55,
    "cost": 0.57,
    "robustness": 0.9,
    "scalability": 0.75,
    "safety": 0.67,
    "adaptability": 0.6,
    "autonomy": 0.77
  }
}

Artifacts in repo

• Report: docs/reproduction-reports/2026-06-24-independent-replay.md
• LES: docs/reproduction-reports/les-autonomous-debugger.json
• LoopBench run: docs/reproduction-reports/lb-cr-1-seed0.json

Regenerate: python scripts/run_reproduction_report.py

Non-maintainers: post your own report here to beat maintainer LB-CR-1 LES (86.7 baseline) → good-first #4.

[KanakMalpani]

Community call — external reproduction reports wanted

Maintainer dry-run is posted; we need your fork → validate → run → LES report to flip the adoption tracker green.

Pack: EXTERNAL_SUBMISSIONS.md §2
Guide: REPRODUCE.md (~60 min)

Post below with fork URL, validator output, and one benchmark or LoopGym replay snippet. Non-maintainer accounts only — thanks!

[KanakMalpani]

First external submitter checklist (Phase 2)

Goal: flip the adoption tracker green for non-maintainer contributions.

LoopBench row (fastest win)

1. pip install "loopbench>=0.1.1" loopgym
2. Follow BEAT_LB-CR-1.md (or RS-1 / MA-1)
3. PR your row to LoopBench leaderboard

Reproduction report (~60 min)

REPRODUCE.md → post below from a non-maintainer account.

Case study

TEMPLATE.md → PR → #7

Full pack: EXTERNAL_SUBMISSIONS.md

[KanakMalpani]

Phase 3 — BEAT all four LoopBench tasks

All four maintainer baselines now have one-command guides:

Task	Guide	Target LES
LB-CR-1	BEAT_LB-CR-1.md	86.7
LB-RS-1	BEAT_LB-RS-1.md	81.9
LB-MA-1	BEAT_LB-MA-1.md	86.5
LB-COMP-1	BEAT_LB-COMP-1.md	77.4

Composed loop: loopgym.make("loopbench/composed-swarm-v1") now ships in LoopGym.

One-pager: ADOPTION.md

Post your row / repro / case study below (non-maintainer accounts only).

Posted 2026-06-24 UTC via adoption_wave3.py

[KanakMalpani]

Phase 4 — LB-COMP-1 on real composed env

LoopBench LB-COMP-1 now runs via loopbench/composed-swarm-v1 (not MA-1 proxy).

Task	Guide	Target LES
LB-CR-1	BEAT_LB-CR-1.md	86.7
LB-RS-1	BEAT_LB-RS-1.md	81.9
LB-MA-1	BEAT_LB-MA-1.md	86.5
LB-COMP-1	BEAT_LB-COMP-1.md	80.3

pip install "loopbench>=0.1.1" "loopgym>=0.1.1"
loopbench run --task LB-COMP-1 --spec loop-library/compositions/scenario-swarm-rehearsal.yaml --seeds 0,1,2,3,4 -o results.json

One-pager: ADOPTION.md

Non-maintainer accounts only for tracker credit.

Posted 2026-06-24 UTC via adoption_wave4.py

[KanakMalpani]

Reproduction v3 — PyPI install names

Use le-loopforge and le-loopctl on PyPI (CLI commands remain loopforge / loopctl).

Do not pip install loopforge or pip install loopctl — those are unrelated packages. See https://github.com/KanakMalpani/Loop-Engineering/blob/main/contributions/PYPI_NAMING.md

Required artifacts:

1. LoopForge command output (loopforge new, fork, or intent)
2. loopctl validate pass
3. Loop Trace 1.0 JSON
4. Observed LES composite (loopctl observed trace.json --json)
5. Optional LoopBench results.json

Reference dry-run: https://github.com/KanakMalpani/Loop-Engineering/tree/main/docs/submission-dry-run

Recommended install:

pip install "le-loopforge>=0.2.0" "le-loopctl>=0.1.0" "loopgym>=0.1.2" loopbench

[KanakMalpani]

Adoption wave 11 — repo owners: submit the first external LoopBench row

We're inviting maintainers of code-repair and agent-loop repos to map their loop to LSS and open a PR on LoopBench.

Outreach sent (2026-06-25):

• OpenAutoCoder/Agentless — repair loop ↔ LB-CR-1
• paul-gauthier/aider — edit-test loop ↔ LB-CR-1
• All-Hands-AI/OpenHands — autonomous dev loop
• LangGraph + CrewAI RFC threads — LoopBench invite added

Your turn (~30 min, no API keys):

1. LOOP_PLAYGROUND.md
2. BEAT_LB-CR-1.md
3. PR → leaderboard/entries.json
4. Comment here with your row link

First non-maintainer submission flips the adoption tracker green.

Posted 2026-06-25 UTC via adoption_wave11.py

[KanakMalpani]

Beat maintainer LB-CR-1 LES (86.7) — trace-native challenge

Target: beat maintainer dry-run observed LES 86.7 on LB-CR-1 with a trace-native reproduction (no API keys on SimEnv v0.1).

pip install "le-loop-stack[bench]>=0.1.0"
loopctl pipeline \
  --intent "Fix failing tests from CI" \
  -o mapped.yaml \
  --run-loopgym \
  --trace trace.json \
  --json
loopbench run --task LB-CR-1 --spec mapped.yaml --seeds 0,1,2,3,4 -o results.json

• Golden Path v3: https://github.com/KanakMalpani/Loop-Engineering/blob/main/contributions/GOLDEN_PATH.md
• Trace template: https://github.com/KanakMalpani/Loop-Engineering/blob/main/docs/reproduction-reports/TEMPLATE-trace-native.md
• Report template: paste trace link + loopbench validate output

Wave 13 outreach: Reflexion · DSPy · SmolAgents (plus wave 11/12 Agentless/Aider/OpenHands).

First non-maintainer comment with a filled trace report flips the adoption tracker green.

Posted 2026-06-28 UTC via adoption_wave13.py