SyncValsverifier → artifact → classifier → verdict
SyncVals · Trajectory

deepcad-canonical-equivalence

claude-code claude-opus-4-8 0.44 partial GOOD_FAILURE ↑ View task
Solved from the instruction alone, tests/ and solution/ were withheld from the agent's workspace and restored only for grading.
Reward = tests/test.sh exit code (0 → resolved); the classification below is post-hoc and cannot change it.
Classification , post-hoc; cannot change the reward
GOOD_FAILUREHonest miss, the agent ran correctly but couldn't solve it. Expected for a hard task; the task is sound.
SubtypeWrong Approach
EvidenceOffline static classifier runner used; no model call was made.
Root causeLocal verifier result was used only to choose a safe default classification.
RecommendationN/A
Trajectory
Tool-by-tool agent trajectory
6 tool calls · 3 tool types · 11 steps
DeepCAD Canonical Equivalence You are given pairs of compact CAD command programs inspired by DeepCAD command histories. For each pair, decide whether both programs describe the same canonical solid. Labels and command order are not reliable evidence by themselves. Interpret the commands, normalize only the aliases described below, and compare the resulting solid. What You Must Produce Implement `/workspace/solve.py`. Your script must support this command: ```bash python3 /workspace/solve.py <input_json> /workspace/predictions.json ``` Write `/workspace/predictions.json` with this schema: ```json { "predictions": [ {"pair_id": "P000", "equivalent": true} ] } ``` Rules for the artifact: - Include exactly one prediction for every input `pair_id`. - `equivalent` must be a JSON boolean, not a string. - You may include optional `signature_a` and `signature_b` fields for your own audit trail, but the required decision field is `equivalent`. - Do not call external APIs or download data. The visible file `/workspace/data/public_pairs.json` is only an unlabeled format example. Evaluation labels are not present in `/workspace`. Program Semantics Each input JSON has a `pairs` array. Each pair contains `pair_id`, `program_a`, and `program_b`. Programs are lists of command dictionaries. - `param` defines scalar arithmetic expressions using numeric constants, other parameters, parentheses, and `+`, `-`, `*`, `/`. Parameters may refer to other parameters by name. Compare evaluated numeric values, not parameter names. Use absolute tolerance `1e-6`. - `sketch` gives a plane for profile geometry. Plane names are case-insensitive literal tokens; do not reorder axes, so `XZ` and `ZX` are different planes. - `rect`, `circle`, and `slot` define profiles. Preserve their geometric fields and plane. Rectangle width/height are ordered dimensions. A slot angle is modulo 180 degrees. Profiles that are not consumed by an `extrude` do not affect the solid. - `extrude` creates solid features from one or more profiles. Preserve operation, depth, extent, direction, profile geometry, and body/channel partitioning. Profile list order inside one extrude is not semantic. If omitted, `operation` defaults to `new`, `extent` defaults to `one_side`, and `direction` defaults to `normal`. - Supported extrude enum fields are lowercased literal tokens. Do not invent synonym aliases: for example, `add`, `join`, and `new` are distinct operations, and `blind` and `one_side` are distinct extents unless the exact token matches after lowercasing. - Depth sign and direction are preserved separately. Do not fold negative depth into direction, do not treat opposite directions as equivalent, and do not simplify symmetric-looking extents beyond comparing the literal normalized fields. - Command IDs, parameter names, sketch IDs, profile IDs, feature IDs, and body/channel labels are alpha-renamable labels for supported commands. - Body/channel fields only induce partition topology. Preserve which extrudes share a partition and which do not; do not preserve the literal spelling of labels, and do not treat `body` and `channel` as semantic namespaces. For example, two features grouped together by one shared body label are equivalent to two features grouped together by one shared channel label. Features with no body/channel field share one unlabeled default partition with each other; an explicit label does not alias that unlabeled partition. - Supported extrude features are compared as an unordered feature multiset after canonicalizing their fields and body/channel partitions. Command order of supported extrudes is not semantic in this benchmark. - Commands marked `construction: true` do not affect the solid. The metadata/annotation command kinds `constraint`, `dimension`, `note`, `metadata`, `view`, and `comment` do not affect the solid. - Any other non-construction command is an opaque solid-affecting payload. Compare opaque payload commands as an unordered multiset. For each opaque command, strip only its own top-level `id`, then compare the remaining JSON payload literally. Do not alpha-rename, evaluate expressions, apply numeric tolerance, sort lists, or resolve references inside opaque payload fields. Other fields on opaque commands, including `target`, `feature`, `edges`, and numeric-looking strings, are literal payload values rather than supported-command aliases. Quality Expectations Missing, malformed, duplicate, or unreadable predictions fail. Pair IDs are only row identifiers.

/workspace/data/public_pairs.json

contents
1	{
2	  "schema_version": "1.0",
3	  "description": "Unlabeled public format examples for the DeepCAD canonical-equivalence task.",
4	  "pairs": [
5	    {
6	      "pair_id": "P001",
7	      "program_a": [
8	        {"cmd": "param", "name": "w", "expr": "40"},
9	        {"cmd": "param", "name": "h", "expr": "20"},
10	        {"cmd": "param", "name": "d", "expr": "8"},
11	        {"cmd": "sketch", "id": "s0", "plane": "XY"},
12	        {"cmd": "rect", "id": "base", "sketch": "s0", "center": [0, 0], "size": ["w", "h"]},
13	        {"cmd": "line", "id": "guide", "sketch": "s0", "p1": [0, -10], "p2": [0, 10], "construction": true},
14	        {"cmd": "extrude", "id": "pad", "profile": "base", "operation": "new", "depth": "d", "extent": "one_side"}
15	      ],
16	      "program_b": [
17	        {"cmd": "param", "name": "depth", "expr": "4 + 4"},
18	        {"cmd": "param", "name": "height", "expr": "5 * 4"},
19	        {"cmd": "param", "name": "width", "expr": "20 * 2"},
20	        {"cmd": "sketch", "id": "profile_sketch", "plane": "XY"},
21	        {"cmd": "rect", "id": "outer", "sketch": "profile_sketch", "center": [0, 0], "size": ["width", "height"]},
22	        {"cmd": "extrude", "id": "solid", "profile": "outer", "operation": "new", "depth": "depth", "extent": "one_side"}
23	      ]
24	    },
25	    {
26	      "pair_id": "P002",
27	      "program_a": [
28	        {"cmd": "param", "name": "r", "expr": "4"},
29	        {"cmd": "sketch", "id": "s", "plane": "XY"},
30	        {"cmd": "circle", "id": "hole", "sketch": "s", "center": [8, 0], "radius": "r"},
31	        {"cmd": "extrude", "id": "cut", "profile": "hole", "operation": "cut", "depth": 10, "extent": "one_side"}
32	      ],
33	      "program_b": [
34	        {"cmd": "param", "name": "r2", "expr": "4.25"},
35	        {"cmd": "sketch", "id": "renamed", "plane": "XY"},
36	        {"cmd": "circle", "id": "hole2", "sketch": "renamed", "center": [8, 0], "radius": "r2"},
37	        {"cmd": "extrude", "id": "cut2", "profile": "hole2", "operation": "cut", "depth": 10, "extent": "one_side"}
38	      ]
39	    },
40	    {
41	      "pair_id": "P003",
42	      "program_a": [
43	        {"cmd": "sketch", "id": "s", "plane": "XY"},
44	        {"cmd": "rect", "id": "rib_a", "sketch": "s", "center": [-6, 0], "size": [2, 12]},
45	        {"cmd": "rect", "id": "rib_b", "sketch": "s", "center": [6, 0], "size": [2, 12]},
46	        {"cmd": "extrude", "id": "ribs", "profiles": ["rib_a", "rib_b"], "operation": "add", "depth": 5, "extent": "one_side"}
47	      ],
48	      "program_b": [
49	        {"cmd": "sketch", "id": "renamed", "plane": "XY"},
50	        {"cmd": "rect", "id": "right", "sketch": "renamed", "center": [6, 0], "size": [2, 12]},
51	        {"cmd": "rect", "id": "left", "sketch": "renamed", "center": [-6, 0], "size": [2, 12]},
52	        {"cmd": "extrude", "id": "ribs2", "profiles": ["right", "left"], "operation": "add", "depth": 5, "extent": "one_side"}
53	      ]
54	    }
55	  ]
56	}
57
I'll start by examining the format, which I've done. Now let me look at the input schema more and then implement the solver.

List workspace and check python

shell
ls -la /workspace/ /workspace/data/ 2>/dev/null; echo "---python---"; python3 --version
output
/workspace/:
total 24
drwxr-xr-x 1 root root 4096 Jul  6 02:01 .
drwxr-xr-x 1 root root 4096 Jul  6 02:20 ..
-rw-r--r-- 1 root root  299 Jul  4 05:02 README.md
drwxr-xr-x 2 root root 4096 Jul  4 05:02 data
drwxr-xr-x 2 root root 4096 Jul  6 02:01 output
-rwxr-xr-x 1 root root 1011 Jul  4 05:02 solve.py

/workspace/data/:
total 12
drwxr-xr-x 2 root root 4096 Jul  4 05:02 .
drwxr-xr-x 1 root root 4096 Jul  6 02:01 ..
-rw-r--r-- 1 root root 2824 Jul  4 05:02 public_pairs.json
---python---
Python 3.11.15

[stdout]
/workspace/:
total 24
drwxr-xr-x 1 root root 4096 Jul  6 02:01 .
drwxr-xr-x 1 root root 4096 Jul  6 02:20 ..
-rw-r--r-- 1 root root  299 Jul  4 05:02 README.md
drwxr-xr-x 2 root root 4096 Jul  4 05:02 data
drwxr-xr-x 2 root root 4096 Jul  6 02:01 output
-rwxr-xr-x 1 root root 1011 Jul  4 05:02 solve.py

/workspace/data/:
total 12
drwxr-xr-x 2 root root 4096 Jul  4 05:02 .
drwxr-xr-x 1 root root 4096 Jul  6 02:01 ..
-rw-r--r-- 1 root root 2824 Jul  4 05:02 public_pairs.json
---python---
Python 3.11.15

/workspace/solve.py

contents
1	#!/usr/bin/env python3
2	"""Weak starter baseline for DeepCAD canonical-equivalence.
3	
4	This intentionally predicts every pair as non-equivalent. It is useful only as
5	a schema example and should score reward 0.0 on the hidden verifier.
6	"""
7	
8	from __future__ import annotations
9	
10	import json
11	import sys
12	from pathlib import Path
13	
14	
15	def main() -> int:
16	    input_path = Path(sys.argv[1]) if len(sys.argv) > 1 else Path("/workspace/data/public_pairs.json")
17	    output_path = Path(sys.argv[2]) if len(sys.argv) > 2 else Path("/workspace/predictions.json")
18	
19	    payload = json.loads(input_path.read_text(encoding="utf-8"))
20	    predictions = [
21	        {"pair_id": pair["pair_id"], "equivalent": False}
22	        for pair in payload.get("pairs", [])
23	    ]
24	
25	    output_path.parent.mkdir(parents=True, exist_ok=True)
26	    output_path.write_text(
27	        json.dumps({"predictions": predictions}, indent=2, sort_keys=True) + "\n",
28	        encoding="utf-8",
29	    )
30	    return 0
31	
32	
33	if __name__ == "__main__":
34	    raise SystemExit(main())
35
Now I'll implement the full solver.
write · /workspace/solve.py
#!/usr/bin/env python3
"""DeepCAD canonical-equivalence solver.

Reads a pairs JSON, decides for each pair whether program_a and program_b
describe the same canonical solid, and writes predictions.json.

Approach: build a normalized, label-invariant signature for each program and
compare the two signatures for equality.
"""

from __future__ import annotations

import ast
import json
import sys
from pathlib import Path

# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------

META_KINDS = {"constraint", "dimension", "note", "metadata", "view", "comment"}
PROFILE_KINDS = {"rect", "circle", "slot"}
PROFILE_SKIP_FIELDS = {"id", "cmd", "sketch", "construction"}

TOL_DECIMALS = 6


# ---------------------------------------------------------------------------
# Expression evaluation
# ---------------------------------------------------------------------------


class Evaluator:
    """Evaluate scalar arithmetic expressions with parameter references."""

    def __init__(self, params):
        # params: name -> raw value (str expression or number)
        self.params = params
        self.cache = {}
        self.inprogress = set()

    def eval_name(self, name):
        if name in self.cache:
            return self.cache[name]
        if name not in self.params:
            raise KeyError(name)
        if name in self.inprogress:
            raise ValueError("parameter cycle: %s" % name)
        self.inprogress.add(name)
        try:
            val = self.eval_value(self.params[name])
        finally:
            self.inprogress.discard(name)
        self.cache[name] = val
        return val

    def eval_value(self, v):
        if isinstance(v, bool):
            raise ValueError("bool is not numeric")
        if isinstance(v, (int, float)):
            return float(v)
        if isinstance(v, str):
            tree = ast.parse(v, mode="eval")
            return self.eval_node(tree.body)
        raise ValueError("not a scalar expression: %r" % (v,))

    def eval_node(self, node):
        if isinstance(node, ast.Constant):
            if isinstance(node.value, bool) or not isinstance(node.value, (int, float)):
                raise ValueError("non-numeric constant")
            return float(node.value)
        if isinstance(node, ast.Num):  # pragma: no cover (py<3.8)
            return float(node.n)
        if isinstance(node, ast.BinOp):
            left = self.eval_node(node.left)
            right = self.eval_node(node.right)
            op = node.op
            if isinstance(op, ast.Add):
                return left + right
            if isinstance(op, ast.Sub):
                return left - right
            if isinstance(op, ast.Mult):
                return left * right
            if isinstance(op, ast.Div):
                return left / right
            raise ValueError("unsupported binary operator")
        if isinstance(node, ast.UnaryOp):
            operand = self.eval_node(node.operand)
            if isinstance(node.op, ast.USub):
                return -operand
            if isinstance(node.op, ast.UAdd):
                return operand
            raise ValueError("unsupported unary operator")
        if isinstance(node, ast.Name):
            return self.eval_name(node.id)
        raise ValueError("unsupported expression node: %r" % (node,))


# ---------------------------------------------------------------------------
# Numeric helpers
# ---------------------------------------------------------------------------


def round_num(x):
    if x is None:
        return None
    r = round(float(x), TOL_DECIMALS)
    if r == 0:
        r = 0.0
    return r


def ser(obj):
    """Canonical JSON string of a jsonable structure (for multiset sorting)."""
    return json.dumps(obj, sort_keys=True, ensure_ascii=False)


def canon_field(v, ev):
    """Canonicalize a geometric field value, evaluating numeric expressions."""
    if isinstance(v, bool):
        return v
    if isinstance(v, (int, float)):
        return round_num(v)
    if isinstance(v, str):
        try:
            return round_num(ev.eval_value(v))
        except Exception:
            return v
    if isinstance(v, list):
        return [canon_field(x, ev) for x in v]
    if isinstance(v, dict):
        return {k: canon_field(x, ev) for k, x in v.items()}
    return v


def normalize_plane(p):
    if isinstance(p, str):
        return p.upper()
    return p


# ---------------------------------------------------------------------------
# Signature construction
# ---------------------------------------------------------------------------


def canon_direction(d, ev):
    if isinstance(d, str):
        return d.lower()
    if isinstance(d, bool):
        return d
    if isinstance(d, (int, float)):
        return round_num(d)
    if isinstance(d, list):
        return [canon_field(x, ev) for x in d]
    return d


def canon_profile(p, sketches, ev):
    kind = p.get("cmd")
    plane = sketches.get(p.get("sketch"))
    fields = {}
    for k, v in p.items():
        if k in PROFILE_SKIP_FIELDS:
            continue
        if k == "angle":
            try:
                a = ev.eval_value(v) % 180.0
                fields[k] = round_num(a)
                continue
            except Exception:
                pass
        fields[k] = canon_field(v, ev)
    return ["profile", kind, plane, fields]


def extrude_profile_ids(ex):
    if "profiles" in ex and isinstance(ex["profiles"], list):
        return list(ex["profiles"])
    if "profile" in ex:
        prof = ex["profile"]
        if isinstance(prof, list):
            return list(prof)
        return [prof]
    return []


def feature_sig(ex, profiles, sketches, ev):
    op = str(ex.get("operation", "new")).lower()
    extent = str(ex.get("extent", "one_side")).lower()
    direction = canon_direction(ex.get("direction", "normal"), ev)

    depth = None
    if "depth" in ex:
        try:
            depth = round_num(ev.eval_value(ex["depth"]))
        except Exception:
            depth = canon_field(ex["depth"], ev)

    ids = extrude_profile_ids(ex)
    prof_forms = []
    for pid in ids:
        if pid in profiles:
            prof_forms.append(ser(canon_profile(profiles[pid], sketches, ev)))
    prof_forms.sort()

    return [op, extent, direction, depth, prof_forms]


def partition_label(ex):
    if "body" in ex:
        return ("L", ex["body"])
    if "channel" in ex:
        return ("L", ex["channel"])
    return None


def build_signature(program):
    if not isinstance(program, list):
        program = []

    params = {}
    sketches = {}
    profiles = {}
    extrudes = []
    opaque = []

    for cmd in program:
        if not isinstance(cmd, dict):
            opaque.append(cmd)
            continue
        if cmd.get("construction") is True:
            continue
        kind = cmd.get("cmd")
        if kind in META_KINDS:
            continue
        if kind == "param":
            params[cmd.get("name")] = cmd.get("expr")
        elif kind == "sketch":
            sketches[cmd.get("id")] = normalize_plane(cmd.get("plane"))
        elif kind in PROFILE_KINDS:
            profiles[cmd.get("id")] = cmd
        elif kind == "extrude":
            extrudes.append(cmd)
        else:
            payload = {k: v for k, v in cmd.items() if k != "id"}
            opaque.append(payload)

    ev = Evaluator(params)

    default_group = []
    label_groups = {}
    for ex in extrudes:
        feat = feature_sig(ex, profiles, sketches, ev)
        lab = partition_label(ex)
        if lab is None:
            default_group.append(feat)
        else:
            label_groups.setdefault(ser(list(lab)), []).append(feat)

    partitions = []
    if default_group:
        partitions.append(["DEFAULT", sorted(ser(f) for f in default_group)])
    for _key, feats in label_groups.items():
        partitions.append(["EXPLICIT", sorted(ser(f) for f in feats)])

    partitions_sig = sorted(ser(p) for p in partitions)
    opaque_sig = sorted(ser(o) for o in opaque)

    return ser(["SIG", partitions_sig, opaque_sig])


# ---------------------------------------------------------------------------
# Main
# ---------------------------------------------------------------------------


def main() -> int:
    input_path = Path(sys.argv[1]) if len(sys.argv) > 1 else Path("/workspace/data/public_pairs.json")
    output_path = Path(sys.argv[2]) if len(sys.argv) > 2 else Path("/workspace/predictions.json")

    payload = json.loads(input_path.read_text(encoding="utf-8"))
    predictions = []
    for pair in payload.get("pairs", []):
        pid = pair.get("pair_id")
        try:
            sig_a = build_signature(pair.get("program_a", []))
            sig_b = build_signature(pair.get("program_b", []))
            equivalent = sig_a == sig_b
        except Exception:
            sig_a = sig_b = None
            equivalent = False
        predictions.append(
            {
                "pair_id": pid,
                "equivalent": bool(equivalent),
                "signature_a": sig_a,
                "signature_b": sig_b,
            }
        )

    output_path.parent.mkdir(parents=True, exist_ok=True)
    output_path.write_text(
        json.dumps({"predictions": predictions}, indent=2) + "\n",
        encoding="utf-8",
    )
    return 0


if __name__ == "__main__":
    raise SystemExit(main())

Run solver on public data

shell
python3 solve.py data/public_pairs.json predictions.json && python3 -c "import json; d=json.load(open('predictions.json')); [print(p['pair_id'], p['equivalent']) for p in d['predictions']]"
output
P001 True
P002 False
P003 True

[stdout]
P001 True
P002 False
P003 True
Results match my analysis. Let me test edge cases to validate the tricky rules.

Test edge cases

shell
cat > /tmp/t.json << 'EOF'
{"pairs":[
 {"pair_id":"E01","program_a":[{"cmd":"sketch","id":"s","plane":"XZ"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3}],
   "program_b":[{"cmd":"sketch","id":"s","plane":"ZX"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3}]},
 {"pair_id":"E02","program_a":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3}],
   "program_b":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[2,4]},{"cmd":"extrude","id":"e","profile":"r","depth":3}]},
 {"pair_id":"E03","program_a":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3,"direction":"normal"}],
   "program_b":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":-3,"direction":"normal"}]},
 {"pair_id":"E04_defVSlabel","program_a":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"rect","id":"r2","sketch":"s","center":[1,1],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3},{"cmd":"extrude","id":"e2","profile":"r2","depth":3}],
   "program_b":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"rect","id":"r2","sketch":"s","center":[1,1],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3,"body":"g"},{"cmd":"extrude","id":"e2","profile":"r2","depth":3,"body":"g"}]},
 {"pair_id":"E05_bodyVSchannel","program_a":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"rect","id":"r2","sketch":"s","center":[1,1],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3,"body":"g"},{"cmd":"extrude","id":"e2","profile":"r2","depth":3,"body":"g"}],
   "program_b":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"rect","id":"r2","sketch":"s","center":[1,1],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3,"channel":"z"},{"cmd":"extrude","id":"e2","profile":"r2","depth":3,"channel":"z"}]},
 {"pair_id":"E06_slotangle","program_a":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"slot","id":"r","sketch":"s","center":[0,0],"length":10,"width":2,"angle":10},{"cmd":"extrude","id":"e","profile":"r","depth":3}],
   "program_b":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"slot","id":"r","sketch":"s","center":[0,0],"length":10,"width":2,"angle":190},{"cmd":"extrude","id":"e","profile":"r","depth":3}]},
 {"pair_id":"E07_opaque","program_a":[{"cmd":"fillet","id":"f","edges":["a","b"],"radius":2}],
   "program_b":[{"cmd":"fillet","id":"fZ","edges":["a","b"],"radius":2}]},
 {"pair_id":"E08_opaque_diff","program_a":[{"cmd":"fillet","id":"f","edges":["a","b"],"radius":2}],
   "program_b":[{"cmd":"fillet","id":"f","edges":["b","a"],"radius":2}]},
 {"pair_id":"E09_op_distinct","program_a":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3,"operation":"add"}],
   "program_b":[{"cmd":"sketch","id":"s","plane":"XY"},{"cmd":"rect","id":"r","sketch":"s","center":[0,0],"size":[4,2]},{"cmd":"extrude","id":"e","profile":"r","depth":3,"operation":"new"}]}
]}
EOF
python3 solve.py /tmp/t.json /tmp/o.json && python3 -c "import json;[print(p['pair_id'],p['equivalent']) for p in json.load(open('/tmp/o.json'))['predictions']]"
output
E01 False
E02 False
E03 False
E04_defVSlabel False
E05_bodyVSchannel True
E06_slotangle True
E07_opaque True
E08_opaque_diff False
E09_op_distinct False

[stdout]
E01 False
E02 False
E03 False
E04_defVSlabel False
E05_bodyVSchannel True
E06_slotangle True
E07_opaque True
E08_opaque_diff False
E09_op_distinct False
All edge cases behave per spec: - **E01** `XZ` vs `ZX` → not equivalent (axis order preserved) - **E02** rect `[4,2]` vs `[2,4]` → not equivalent (ordered dimensions) - **E03** depth `+3` vs `-3` → not equivalent (sign preserved separately) - **E04** default/unlabeled partition vs shared explicit label → not equivalent (explicit label does not alias the unlabeled partition) - **E05** shared `body` label vs shared `channel` label → equivalent (namespaces not distinct) - **E06** slot angle `10` vs `190` → equivalent (mod 180) - **E07** opaque command with different `id` → equivalent (top-level id stripped) - **E08** opaque `edges:[a,b]` vs `[b,a]` → not equivalent (literal, lists not sorted) - **E09** `add` vs `new` → not equivalent (distinct operations) The solver is complete and working. Summary of `/workspace/solve.py`: **Normalization pipeline** , for each program it builds a label-invariant signature: - **Params**: collected, then evaluated lazily via a safe `ast`-based arithmetic evaluator (supports `+ - * /`, parens, param references, cycle detection); compared by value at `1e-6` tolerance (rounding to 6 decimals). - **Sketches**: id → plane, case-normalized but axis order preserved. - **Profiles** (`rect`/`circle`/`slot`): geometric fields evaluated numerically, ordered dimensions kept ordered, slot `angle` taken mod 180; plane attached from the referencing sketch. Only profiles consumed by an extrude contribute. - **Extrudes** → feature tuple `(operation, extent, direction, depth, profile-multiset)` with defaults `new`/`one_side`/`normal`; depth sign and direction kept literal/separate; profile order within an extrude ignored. - **Partitions**: extrudes grouped by `body`/`channel` value (namespace-agnostic, label-renamable); unlabeled features form a distinct `DEFAULT` partition that explicit labels never alias. - **Opaque commands** (anything else non-construction, excluding metadata kinds): top-level `id` stripped, payload compared literally as an unordered multiset , no eval, no tolerance, no list sorting. Everything is compared as an unordered multiset of partitions + opaque payloads, so extrude command order and alpha-renamable labels don't matter. Predictions are written with `equivalent` as a JSON boolean plus optional `signature_a`/`signature_b` audit fields, one row per `pair_id`, with per-pair exception guarding so a malformed pair still yields a valid prediction.
Final diff , what the agent changed

No file changes, the agent left the workspace untouched.

Verifier output , the proof behind the reward
tests/test.sh
{
  "metrics": {
    "canonical_regime_min_accuracy": 0.934426,
    "diagnostic_accuracy": {
      "alias": 1.0,
      "commutation": 1.0,
      "enum_literal": 1.0,
      "explicit_defaults": 1.0,
      "feature_multiset_multiplicity": 1.0,
      "hard_decoy": 0.934426,
      "numeric_tolerance": 1.0,
      "ood": 0.952941,
      "opaque_id_alias": 1.0,
      "opaque_list_literal": 1.0,
      "opaque_nested_literal": 1.0,
      "opaque_numeric_literal": 1.0,
      "opaque_reference_literal": 1.0,
      "ordered_rect_dimensions": 1.0,
      "partition_alias_true": 1.0,
      "partition_default": 1.0,
      "partition_topology": 0.0,
      "plane_literal": 1.0,
      "profile_order": 1.0,
      "redundant": 1.0,
      "signed_depth_direction": 1.0,
      "slot_angle_modulo": 1.0,
      "unconsumed_profile": 1.0
    },
    "diagnostic_macro_accuracy": 0.951625,
    "equivalent_recall": 1.0,
    "overall_accuracy": 0.958763,
    "regime_accuracy": {
      "alias": 1.0,
      "commutation": 1.0,
      "hard_decoy": 0.934426,
      "ood": 0.952941,
      "redundant": 1.0
    }
  },
  "passed": false,
  "reward": 0.441163,
  "reward_policy": {
    "anchors": {
      "diagnostic_macro_accuracy": {
        "baseline": 0.45,
        "strong_target": 1.0,
        "target": 0.985,
        "threshold": 0.8
      },
      "equivalent_recall": {
        "baseline": 0.3,
        "strong_target": 1.0,
        "target": 0.99,
        "threshold": 0.8
      },
      "overall_accuracy": {
        "baseline": 0.65,
        "strong_target": 1.0,
        "target": 0.99,
        "threshold": 0.88
      }
    },
    "meets_targets": false,
    "metric_scores": {
      "diagnostic_macro_accuracy": 0.474231,
      "equivalent_recall": 1.0,
      "overall_accuracy": 0.441163
    },
    "required_metrics": [
      "overall_accuracy",
      "equivalent_recall",
      "diagnostic_macro_accuracy"
    ],
    "target_reward": 0.5,
    "threshold_reward": 0.2,
    "type": "v3_50pass"
  }
}

Reproduce this trial: git checkout 2f94510 && PYTHONPATH=src python3 scripts/build_site.py , then open trial/trial_3cbd36c1865f4028. Re-running the agent live requires EVAL_PLATFORM_ENABLE_OAUTH_SMOKE=1 and is non-deterministic.

Trial trial_3cbd36c1865f4028 · verifier authoritative; classifier explanatory.