feat(harness): cross-model behavior matrix (G) — harness + results

Tier 1 (clean-room first-turn harness, harness/scripts/model-matrix.mjs):
kickoff + resume chain in-turn on ALL available models — zai/glm-5.2,
deepseek/deepseek-v4-{pro,flash}, aritmolab/qwen3.6-35b-a3b, zai/glm-4.5-air.
The resume cold-start stall recurs on none (closes A's cross-model robustness).
aritmolab/gemma4-26b-a4b is a 404 at the endpoint (listed but not served) — an
availability gap classified as MODEL_ERROR, not a workflow issue.

Tier 2 (live, baseline zai/glm-5.2): F single-select auto-confirm verified
end-to-end — answering the first reviewer_select persisted a concept_clarified
decision (review_decisions.jsonl 0->1) with no follow-up confirmation gate.
Closes F's deferred live check.

No prompt hardening needed. Results in the G plan doc + memory. Throwaway psd
sessions used and deleted; real sessions untouched.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
2026-06-30 18:46:55 +02:00
co-authored by Claude Opus 4.8
parent e8cdd0037c
commit cbb8e184f1
3 changed files with 201 additions and 5 deletions
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@@ -122,12 +122,19 @@ all pushed to origin. A (Resume menu + stall diagnosis/hardening) DONE, uncommit
`tht session show`+`read SKILL.md` in-turn). The earlier narrate-and-stop predates the pi upgrade.
Defense-in-depth applied: `RIPRENDI_KICKOFF` hardened to force the in-turn tool call (gate test +
live regression 2/2). The cross-model angle (weaker/older models) lives in **G**.
- **G (last, separate):** cross-model behavior matrix (Qwen3.6 / GLM 5.2 / Deepseek V4 / others) —
also the home for **F's live check** and **A's cross-model resume robustness**.
- **G — DONE** (uncommitted): cross-model behavior matrix via a committed clean-room harness
(`harness/scripts/model-matrix.mjs`). **Tier 1** — kickoff + resume first-turn: all *available*
models chain in-turn (`zai/glm-5.2`, `deepseek/deepseek-v4-{pro,flash}`, `aritmolab/qwen3.6-35b-a3b`,
`zai/glm-4.5-air`); the resume stall recurs on none (closes A's cross-model robustness).
`aritmolab/gemma4-26b-a4b` = **404 unavailable** at the endpoint (listed but not served) — infra
gap, not a workflow issue. **Tier 2** — F single-select auto-confirm verified live on `glm-5.2`:
answering the first `reviewer_select` persisted a `concept_clarified` decision **0→1** with **no
follow-up gate** (closes F's deferred live check). Full results: the G plan doc + memory
`thothii-cross-model-matrix`. No prompt hardening needed.
**Status:** A-G core work done (D, E, B, C, F, A). **Remaining:** **G** (cross-model matrix,
incl. F's live single-select check + A's resume-on-weaker-models), plus a one-off manual Playwright
kebab→resume pass through the live UI (open item 2).
**Status:** **All UI-redesign + resume workstreams done — D, E, B, C, F, A, G.** D/E/B/C/F/A pushed;
**G uncommitted** (harness + docs + PROJECT_STATE). Remaining nice-to-haves: Tier-2 F/multiselect for
the non-baseline models (cheap re-run), and a one-off manual Playwright kebab→resume pass in the UI.
## Live verification + reviewer_select fix (2026-06-30, afternoon)
@@ -65,6 +65,35 @@ misbehaves, harden the **model-facing prompt** (kickoffs in `tht-gate.js`, disci
3. Prompt hardening PRs where a model diverges, each re-verified.
4. A short "supported models" note (which models drive the workflow reliably; which to avoid).
## Results (executed 2026-06-30)
Harness committed at `harness/scripts/model-matrix.mjs`. Throwaway sessions used + deleted; the two
real psd sessions were never driven.
**Tier 1 — kickoff + resume first-turn (medium thinking), all *available* models CHAINED in-turn:**
| model | new (→`read` SKILL) | resume (→`tht session show`+`read`) |
|---|---|---|
| `zai/glm-5.2` | ✅ 10.9s | ✅ 14.5s |
| `deepseek/deepseek-v4-pro` | ✅ 8.9s | ✅ 7.8s |
| `deepseek/deepseek-v4-flash` | ✅ 5.9s | ✅ 6.4s |
| `aritmolab/qwen3.6-35b-a3b` | ✅ 6.5s | ✅ 7.0s |
| `zai/glm-4.5-air` | ✅ 18.3s | ✅ 11.3s |
| `aritmolab/gemma4-26b-a4b` | ⚠️ `MODEL_ERROR` — 404 "model does not exist" at the endpoint (in the registry but not served); not a workflow issue |
→ The kickoff contract is model-agnostic across the available fleet; the **resume cold-start stall
does not recur on any model** (closes A's cross-model robustness). No prompt hardening needed.
**Tier 2 — F single-select auto-confirm, live on baseline `zai/glm-5.2`:** F1 reached the first
`reviewer_select` ("cosa significa 'fibrillazione atriale'?") at ~321s; answering a concrete option
drove `review_decisions.jsonl` **0 → 1** (a full `concept_clarified` decision persisted directly)
with **no follow-up confirmation gate**. → **F's auto-confirm contract verified end-to-end.**
**Supported-models note:** GLM 5.2 (baseline), Deepseek V4 (pro + flash), Qwen3.6 35B, and the
lighter GLM-4.5-air all drive the workflow reliably. `gemma4-26b-a4b` is listed but **not served**
by the AritmoLab endpoint (404) — exclude until the endpoint provides it. Tier-2 per-model F/
multiselect behavior beyond the baseline remains a cheap future add (re-run with each model).
## Risks / notes
- **psd is the active workspace (real client data).** Use throwaway sessions + delete after (the A2
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// model-matrix.mjs — workstream G Tier 1: clean-room cross-model behavior matrix.
//
// Drives `pi --mode rpc` exactly as the backend does (set_model -> set_thinking_level ->
// prompt) for each (model x scenario) and classifies the FIRST turn. Decisive signal: a
// `toolcall_start`/`tool_execution_start` means the model chained into work in-turn; its
// absence + quiescence = the narrate-and-stop stall.
//
// Scenarios (first-turn only, cheap ~15-30s each):
// new -> prompt `/nuova-domanda "kickoff"` (THT_SESSION set => PROVIDED kickoff; first
// tool should be `read` of SKILL.md)
// resume -> prompt `/riprendi-sessione <id>` (first tools should be `tht session show` +
// `read SKILL.md` in-turn) — workstream A robustness across models.
//
// Usage:
// node harness/scripts/model-matrix.mjs <sessionId> [provider/model,...] [thinking] [outDir]
// Defaults: the named primaries + one weak/local model; thinking=medium.
//
// NOTE: spawns real models against the configured workspace. Use a THROWAWAY session and
// delete it afterwards (psd is real client data). Kills each child after the first decisive
// signal, so mutation is minimal (reads only; no gate is answered).
import { spawn } from "node:child_process";
import fs from "node:fs";
import path from "node:path";
import { fileURLToPath } from "node:url";
const harnessDir = path.resolve(path.dirname(fileURLToPath(import.meta.url)), "..");
const sessionId = process.argv[2];
if (!sessionId) {
console.error("usage: node model-matrix.mjs <sessionId> [provider/model,...] [thinking] [outDir]");
process.exit(2);
}
const models = (process.argv[3] ??
"zai/glm-5.2,deepseek/deepseek-v4-pro,aritmolab/qwen3.6-35b-a3b,aritmolab/gemma4-26b-a4b")
.split(",").map((s) => s.trim()).filter(Boolean);
const thinking = process.argv[4] ?? "medium";
const outDir = process.argv[5] ?? "/tmp/model-matrix";
fs.mkdirSync(outDir, { recursive: true });
const scenarios = ["new", "resume"];
const DEADLINE = 90000; // hard cap per cell
const QUIESCENCE = 14000; // turn ended idle if this long with no new events and no toolcall
const sleep = (n) => new Promise((r) => setTimeout(r, n));
function runCell(provider, modelId, scenario, rawOut) {
return new Promise((resolve) => {
const env = {
...process.env,
THT_SESSION: sessionId,
THT_AUTHOR: "matrix@local",
PATH: `${harnessDir}/.venv/bin:${process.env.PATH ?? ""}`,
};
const child = spawn("pi", ["--mode", "rpc"], { cwd: harnessDir, env });
const raw = fs.createWriteStream(rawOut);
child.stderr.resume();
const t0 = Date.now();
const ms = () => Date.now() - t0;
const counts = {};
let firstTool = null;
let assistantText = "";
let modelError = null; // a 404/endpoint error is "model unavailable", not a behavioral stall
let lastEventAtMs = 0;
let promptAtMs = Infinity;
let buf = "";
child.stdout.on("data", (d) => {
raw.write(d);
buf += d.toString();
let i;
while ((i = buf.indexOf("\n")) >= 0) {
const line = buf.slice(0, i);
buf = buf.slice(i + 1);
if (!line.trim()) continue;
lastEventAtMs = ms();
let e;
try { e = JSON.parse(line); } catch { continue; }
const type = e.type ?? "?";
counts[type] = (counts[type] || 0) + 1;
if ((type === "toolcall_start" || type === "tool_execution_start") && !firstTool) {
firstTool = {
atMs: ms(),
name: e.toolName ?? e.name ?? e.tool?.name ?? e.input?.command ?? "?",
};
}
if (type === "message_update") {
const delta = e.assistantMessageEvent?.delta;
if (typeof delta === "string") assistantText += delta;
}
if (!modelError) {
const m = e.message;
if (m && (m.errorMessage || m.stopReason === "error")) {
modelError = m.errorMessage || "stopReason=error";
}
}
}
});
function send(obj) { try { child.stdin.write(JSON.stringify(obj) + "\n"); } catch {} }
function finish(verdict) {
clearInterval(timer);
try { child.kill("SIGKILL"); } catch {}
resolve({
provider, modelId, scenario,
verdict: modelError ? "MODEL_ERROR" : verdict,
firstToolAtMs: firstTool?.atMs ?? null,
firstToolName: firstTool?.name ?? null,
error: modelError,
events: counts,
textTail: assistantText.slice(-240).replace(/\s+/g, " ").trim(),
});
}
(async () => {
await sleep(700);
send({ type: "set_model", provider, modelId });
await sleep(1800);
send({ type: "set_thinking_level", level: thinking });
await sleep(1000);
const message = scenario === "resume"
? `/riprendi-sessione ${sessionId}`
: `/nuova-domanda "kickoff"`;
send({ type: "prompt", message });
promptAtMs = ms();
})();
const timer = setInterval(() => {
if (modelError) return finish("MODEL_ERROR");
if (firstTool) return finish("CHAINED");
const sawTurn = lastEventAtMs > promptAtMs && (counts.agent_start || counts.turn_start || counts.message_start);
const quiet = ms() - lastEventAtMs > QUIESCENCE;
if (sawTurn && quiet) return finish("STALLED");
if (ms() > DEADLINE) return finish(sawTurn ? "STALLED" : "NO_TURN");
}, 1000);
child.on("exit", () => { if (!firstTool) finish("CHILD_EXIT"); });
});
}
const results = [];
for (const m of models) {
const [provider, modelId] = m.split("/");
for (const scenario of scenarios) {
const tag = `${provider}_${modelId}_${scenario}`.replace(/[^a-z0-9_.-]/gi, "-");
const r = await runCell(provider, modelId, scenario, path.join(outDir, `${tag}.jsonl`));
results.push(r);
console.error(`done ${m} ${scenario}: ${r.verdict} (${r.firstToolName ?? "-"} @ ${r.firstToolAtMs ?? "-"}ms)`);
}
}
// Markdown summary table + raw JSON for the record.
const rows = results.map((r) =>
`| ${r.provider}/${r.modelId} | ${r.scenario} | ${r.verdict} | ${r.firstToolName ?? "-"} | ${r.firstToolAtMs ?? "-"} | ${r.error ?? ""} |`,
);
console.log("\n| model | scenario | verdict | first tool | t(ms) | error |");
console.log("|---|---|---|---|---|---|");
console.log(rows.join("\n"));
console.log("\nJSON " + JSON.stringify(results));