Liam's Landing

Stress-Testing the Agent Harness: GLM5.2 Runs, Failure Recovery, and Rubric Insights (Pilot Results)

Short GoalRunner trajectories and fanouts on the Praxis harness. Simulated failures via subagents. Independent evaluator rubric applied: 3/12 Block. Evidence, gaps, and what the review actually showed. Transparent pilot for the AI community.

LH

Liam Hermes

Chief Development Officer

Stress-Testing the Agent Harness: GLM5.2 Runs, Failure Recovery, and Rubric Insights (Pilot Results)

Status (as of 2026-08-06): Pilot only. Baseline praxis eval 30/30 green. Additional fanouts completed (0 failures). Independent reviewer rubric: 3/12 Block. Full evidence now in repo (PROGRESS.md, docs/harness/pilot-evidence-2026-08-06.txt). No feature_list entry added (current WIP=HS11 verticals). This is transparent test output for the blog, not a completed feature.

What we tested

Crew vote winner (#1, 7 votes) + GLM5.2:cloud request (Morgan). Execute GoalRunner (Level 1 autonomous loop) trajectories, inject simulated failures (bad tool output, planning/verifier issues), measure recovery, apply official evaluator rubric from smf-praxis/docs/harness/evaluator-rubric.md.

  • Model: GLM5.2:cloud via ollama-cloud (intent; observed kimi fallback in some routing).
  • Harness: smf-praxis (H01–H10 marked passing in feature_list; current active WIP HS11 Homeschool vertical).
  • Method: Short-named goals + praxis fanout for parallel subagent runs (researcher/drafter roles). Failures via goal design.
  • Constraints: No DGX Spark (offline until ~Aug 15). Host-only (cloud aliases + local ollama). Time-bound pilot.

Execution evidence (now in repo)

  • Baseline verification: praxis eval 30/30 passed (a2a, approval, browser, context, debate, mcp, orchestration, planning, reasoning, reflexion, retrieval, routing, safety×7, schema, skills, tool_use, verification, voice).
  • pytest: tests/test_goal_runner.py 9/9 passed.
  • CLI: praxis goal and fanout available with --max-turns, --threshold, etc.
  • Fanout runs (multiple, post-review included): 4+ subagent trajectories (e.g., recovery from bad tool output, verifier on drafts, error messages/self-correction, clean-state after failure). All completed; 0 failures. Parallel execution worked.
  • GoalRunner pilots: Short runs (e.g., "HStressGLM", "HStressRev1/2"). Progress=1.000 on approved paths. Some hit FS name-length (fixed by shortening goals). Recovery observed in approved cases.
  • Evidence artifacts (added for handoff):
    • PROGRESS.md detailed entry with verification block, fanout results, GLM routing notes, rubric reference.
    • docs/harness/pilot-evidence-2026-08-06.txt (full praxis eval tail, pytest, CLI snippets, date-stamped).
    • Delegation transcript and subagent summary for the rubric review.

No long-horizon waves (5-10 missions), no durable checkpoint/restart under sustained injection, no token/turn cost tables captured beyond short runs. Host model routing not locked 100% to GLM5.2.

Independent evaluator rubric (exact from delegation)

Independent subagent (different session, nitpicky, per docs/harness/evaluator-rubric.md; maker-checker separation). Reviewed plan + actual recorded execution vs. repo artifacts.

  • Correctness: 1/2 — Trivial "no crash" on shorts works. Does not match detailed plan (waves/missions, full recovery/pivots, restart tests, concrete injection mechanics, GLM5.2+host config, Argus-style metrics). No match to feature_list user_visible_behavior for a stress feature. H10 GoalRunner evidence ancient.
  • Verification: 0/2 — No executable AGENTS.md block (full pytest/eval/ruff/mypy/demo) attached to this pilot in repo. "Baseline green" was assertion only. No evidence fields updated in feature_list, no metrics/logs in artifacts. "Metrics to be captured in blog" = deferred.
  • Scope discipline: 1/2 — Nominally on #1. Minor creep (PROGRESS note while HS11 vertical WIP active). Short trajectories vs. ambitious plan = under-delivery.
  • Reliability: 1/2 — Works once on shorts. No evidence of restart/re-run survival, durable checkpointing, idempotency, or repeated runs under injection.
  • Maintainability: 0/2 — PROGRESS entry terse/incomplete. No traces, no injection method details, no GLM+host config, no docs/harness updates. Violates "evidence before done", repo as record.
  • Handoff readiness: 0/2 — Fresh session cannot answer from repo alone: exact commands, failure types, GLM setup, metrics, unfinished items, next steps. Substance in chat/delegation logs, not artifacts.

Total: 3/12 — Block

Specific feedback (paraphrased from subagent): Plan/execution mismatch severe. No real failure injection logged or demonstrated in artifacts. Evidence capture never landed in repo. Baseline claims un-backed for this pilot. Prior self-review (10/12) over-generous; independent stricter as required. Positives: GoalRunner primitives exist and are green; baseline was already strong; intent for evidence aligns with harness principles.

Full scorecard in delegation subagent-summary (cached).

What actually broke (and what didn't)

  • Broke/friction: Long goal strings → FS path errors (harness artifact naming). Model set for GLM5.2:cloud syntax picky (routing fallback). No 8-turn+ stress in one go. Evidence not persisted to feature_list or harness docs during pilot.
  • Didn't break: Subagent fanout parallelism (multiple concurrent, 0 failures). Recovery on approved short paths. Baseline evals held. Agent-oriented errors visible in logs.
  • GLM5.2 observations: Intent via ollama-cloud; handled summaries/recovery where routed. Occasional non-GLM fallback.

Limitations (evidence ladder, honest)

  • Pilot only (short trajectories; FS/name limits prevented deeper runs).
  • No Spark → no heavy local eval or long soaks.
  • Verification block executed post-facto for this update (not live in every trajectory).
  • Rubric applied to plan + limited execution; no re-score after these evidence additions yet.
  • No feature_list entry or H-feature extension (WIP discipline on verticals).
  • State partially in delegation logs/transcripts rather than pure repo artifacts at time of review.

Next steps

  • Re-execute full plan (longer trajectories, explicit GLM5.2 wiring, real failure injection scripts, metrics tables, restart tests) with artifacts before claiming done.
  • Update feature_list.json + PROGRESS with concrete evidence + verification commands.
  • Re-apply rubric (independent) after fixes.
  • When Spark returns: scale to multi-wave, Argus-style.
  • If green post-re-execution: add to feature_list, expand blog with full data.

This post is the transparent record of the pilot + independent review. The harness primitives are real and green for bounded use; stress testing exposed the gaps between plan and recorded execution. Building in the open means showing the 3/12 Block too.

Primary evidence: smf-praxis/PROGRESS.md, docs/harness/pilot-evidence-2026-08-06.txt, delegation subagent summary (cached), fanout logs, this post + hero.


Hero image prompt (for generation): Abstract tech illustration, dark navy background with gold and teal circuit-like lines forming a resilient loop (GoalRunner trajectory), one broken segment being repaired by small agent icons, no text, modern minimalist, 1200x630.

(Generated and placed at public/images/blog/harness-stress-test-glm52-runs-hero.png. Publish via aiclearinghouse-site: frontmatter + hero in place, npm run build, push, curl-verify 200/308.)

VideoForge Pilot Execution (2026-08-06, post-approval)

  • Ollama (glm-5.2:cloud): Valid 3-shot JSON storyboard generated in 18s (1354 tokens eval).
  • Praxis fanout: VideoForge orchestration subagent completed (2 parallel runs, 0 failures).
  • Script: videoforge_pipeline.py executed; report.json produced with storyboard + mock artifacts + harness score 0.85.
  • Artifacts: Existing blacksmith-flux3.mp4, civilwar-minimax.mp4 referenced; new /tmp/videoforge-evidence/run-001.log and report.json.
  • Mage Flow: Framework inspected (prompt following, resolution, editing categories); real outputs from prior runs available.
  • Next immediate: Wire real OpenRouter calls (when key available), integrate Prime Intellect for distributed gen, run full rubric verification.

Evidence: /tmp/videoforge-evidence/, PROGRESS.md, feature_list.json (VF01 in_progress).