The evidence for track F, in the shape tracks A, E and B + G used. - benchmarks/tasks_v6.py: 19 tasks, DEFAULT_MATRIX = "v6"; v5 to v2 stay addressable. arch_roundtrip draws the example plan with arch_plan_from_spec and reads it back without the spec: rooms_detect must find each labelled room within 0.1 % of its label and of the net floor computed by hand (4825 x 5750 and 3825 x 5750), the schedules must list D1, D2, W1, W2, and the plan is gated on a zero-issue critique and a finalize score of at least 90. A test removes one room label and the gate fails naming arch_room_unlabelled. - Four correctness checks, every number worked out by hand in the docstring: L / T / X junction corners and wall areas, a 4 x 5 m room labelled 20.00 m2 rather than its 21.84 m2 axis area, a door interrupting both faces, and a plan of plain lines read as 20 and 15 m2 at confidence 0.6. The published A/B report is re-run over 43 checks: 26 / 43 -> 43 / 43, zero regressed. - scripts/smoke_arch_com.py runs the whole plan once on a live seat and closes every document it opens; the CHANGELOG records what it returned. - The token suite measures a TOOL_PACKS=core,arch row; check_doc_numbers derives the task count from the v6 matrix; CLAUDE.md, both READMEs and the spec status line say what shipped. - fix(com): the first live smoke exited 1 - the room reader found 0 wall segments. Measured on AutoCAD 2026 (2026-09-23): with a makepy cache, ModelSpace.Item(i) returns the gen_py IAcadEntity wrapper (type(item).__name__ == "IAcadEntity") and item.StartPoint on an AcDbLine raises AttributeError, so every entity_list row lost its type-specific properties (28 wall LINEs, 0 with start/end). _entity_info now re-dispatches exactly that wrapper through _com_unnarrow; after the fix 38 of 53 rows carry start/end and the smoke exits 0 with both rooms at 27 743 750 / 21 993 750 mm2 and 0 critique issues. Re-dispatch measured at ~1.7 ms per entity (dynamic vs gencache alike). Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01FKFStjEFzpGyLq5bMpWxTd
Benchmarks
Two evidence layers
This repository publishes two deliberately separate forms of evidence:
- Source-reviewed capability benchmark. Nine named AutoCAD MCP projects are
scored with a fixed 100-point rubric covering CAD breadth, correctness and
delivery, backend reach, engineering production, tests, and security. The
dated data lives in
source_review.json, and the README graphic is generated—not hand-edited—from that file. - Fixed-task runtime benchmark. Adapters execute the same task matrix and
return
pass,partial,unsupported,fail,timeout, ornot_run. AutoCAD MCP Pro currently has the reference adapter; other projects do not receive runtime scores until an adapter actually runs their public interface.
Regenerate the source-review chart:
pip install -e ".[pdf]"
python -m benchmarks.render_chart
The source-review chart is not presented as a shared live AutoCAD run. Review dates, evidence grades, project URLs, and the boundary are stored with the data.
Fixed-task runtime runner
The runner separates runtime evidence from the source-review rubric. Every
adapter receives the same tasks and produces the same closed result enum:
pass, partial, unsupported, fail, timeout, or not_run. A timeout is
reported per task, and a capability refusal is recorded unsupported rather
than fail — "cannot reach this" and "got this wrong" are different findings.
Execution is in-process, so adapters that delegate blocking work must provide
cancellation-safe task implementations or be wrapped by an external process
supervisor. Reports include commit SHA, Python/platform details, backend
capability claims, durations, coverage, and hashes for returned artifacts.
Unsupported tasks remain in the fixed-matrix denominator with score zero,
preventing partial implementations from receiving an inflated score.
python -m benchmarks.run_competitors --list --matrix v5
python -m benchmarks.run_competitors --server autocad-mcp-pro --backend ezdxf --matrix v5 --json
python -m benchmarks.run_competitors --task table_mleader --task hatch_islands --json
The release-machine ezdxf self-check is 18/18 (100.0) on the v5 matrix
(--matrix v4 / --matrix v3 / --matrix v2 reproduce the earlier sets).
Repository stars and raw tool counts do not contribute to the score. Adapter
registration lives in competitors.yaml.
Matrix v3 (v1.5.0) — five tasks that can fail
v2 scored this server 10/10, and that number carried no information: every task
in it exercised something the server was designed around. tasks_v3.py keeps
the v2 ten unchanged — their ids and weights key the published v1.4 reports —
and adds five chosen because they can fail. Three of them did, while being
written:
| Task | Category | Verified against |
|---|---|---|
tool_discovery |
discovery | six AutoCAD command names, each found in the top 3 of the 154-tool registry the harness ranks — all six came back #1 in the published run |
token_budget |
efficiency | 40,305 → 356 tokens advertised, against a 2,000 ceiling fixed in advance |
hatch_islands |
hatch | 300 filled with the island, 400 ignoring it |
selection_filter |
selection | window 1, crossing 2, bounding box 3, polygon 1 |
measure_from_handle |
measurement | 139.2699 against the 100.0 a vertex shoelace gives |
Token counts come from the offline ratio estimator and the report labels them
ratio/v1 (estimate); token_suite.py --tokenizer anthropic counts for real.
Two renames from the release plan, and they are the point.
tool_discovery_bilingual → tool_discovery: a Turkish query normalizer was
written and then removed, because this repository is English throughout and the
Turkish was inferred from the author's chat language rather than required by the
product. measurement_massprops → measure_from_handle: no centroid or
moment-of-inertia tool ships.
The competitor reports are not re-scored. Those servers are pinned at v1.4
commits and were run against the v2 matrix; they have never been asked these
five questions. Their scores stand over the ten they ran, and the matrix chart
leaves the five new rows blank (not run) instead of scoring them zero — a
zero we invented would be indistinguishable from a zero we measured.
--matrix v2 stays available so a v1.4 report can be reproduced rather than
only described, and --publish writes the artifact-path-free file that
results/published/ holds.
Matrix v4 (v1.6) — the P&ID round trip and the page-setup truth
tasks_v4.py keeps the v3 fifteen unchanged and adds two tasks that can each
fail on their own:
| Task | Category | Verified against |
|---|---|---|
pid_roundtrip |
pid | the example spec drawn through pid_from_spec's code, then read back by the graph builder, which never sees the spec: 5 nodes, 4 edges, 0 dangling ends, confidence_min 1.0, zero critique issues, an instrument index of exactly FIC-101 wired to FCV-101, and the two authored line numbers back on the two process lines while the two unnumbered lines carry sequence-built numbers from XDATA |
page_setup_truth |
pagesetup | page_setup_apply("Layout1", ANSI_B landscape 1:1) then batch_plot — the PDF's own /MediaBox must parse to 432 × 279 mm (±0.5), a size no fresh document has; then page_setup_apply("Layout1", ISO_A3 landscape 1:1) and batch_plot again — 420 × 297, the setter's changed.size_mm must read [[432, 279], [420, 297]], the page-setup list must say ISO_A3 / landscape / [420, 297], and the ctb must be a known one. A setter that writes nothing fails at the first PDF (tests/test_benchmark_v4.py stubs it to prove that) |
The competitor reports carry no result for either, for the same reason they
carry none for the v3 five. --matrix v3 reproduces the v1.5 set exactly.
Matrix v5 (v1.6) — the mechanical sheet
tasks_v5.py keeps the v4 seventeen unchanged and adds roadmap criterion 3:
| Task | Category | Verified against |
|---|---|---|
mech_assembly |
mech | a flange-coupling A3 sheet built through the code the tools call — apply_titleblock (ISO 5457 frame with zones and marks, ISO 7200 title block), a hub drawn by draw_part with a full section by add_view and chain dimensions by dimension_part, a flange with its bolt-circle end view, two ISO 4014 M12x60 bolts and two ISO 4032 M12 nuts by insert_std_part, the ISO 7573 parts list read off the drawing by extract_records and drawn by draw_bom_table, and one balloon per row linked to that row's inserts by add_balloon. The sheet is saved, then gated on two numbers that cannot be negotiated: run_critique(focus=None) returns zero issues and combine(validator, critique) scores at least 90. The focuses that fired come back in the metrics, and tests/test_benchmark_v5.py drops one balloon to prove the gate fails and names mech_bom_balloon_mismatch |
Nothing in the task tidies up after the tools: the view engine draws the ISO
128-23 centre lines of every circle it emits, so the sheet is clean because it
was drawn clean. Building it found four defects that every headless test had
missed — the headless diameter text on the wrong side of the chord, the
validator reading a fastener designation (M12x60) as a fake dimension, and on
the live seat a missing MECH layer and a parts list that could not see a
BLOCKREFERENCE; each is fixed with a test. The competitor reports carry no
result for it.
Matrix v6 (v1.6) — the architectural plan
tasks_v6.py keeps the v5 eighteen unchanged and adds track F's evidence:
| Task | Category | Verified against |
|---|---|---|
arch_roundtrip |
arch | the plan of engineering/arch/spec.py::EXAMPLE_SPEC — a 9 × 6 m brick ring at 250 mm split by a 100 mm AAC wall, an entrance door, an interior door, two windows, a straight stair, two labelled rooms, the exterior chains and the door / window / room schedules — drawn in one transaction by draw_plan_from_spec, then read back without the spec: rooms_detect on the wall layer must find each labelled room within 0.1 % of the area its label carries and of the net floor computed by hand (4825 × 5750 = 27 743 750 and 3825 × 5750 = 21 993 750 mm²), schedule_rows must list exactly D1, D2 and W1, W2, and the saved plan is gated like mech_assembly: run_critique(focus=None) returns zero issues and combine(validator, critique) scores at least 90. tests/test_benchmark_v6.py removes one room label to prove the gate fails and names arch_room_unlabelled |
The competitor reports carry no result for it.
Live competitor lane (v1.4)
Two competitor adapters now execute the exact same task matrix, black-box over
MCP stdio, against commits pinned in competitors.yaml:
| Server | Matrix | Pinned | Score | Pass | Coverage |
|---|---|---|---|---|---|
| autocad-mcp-pro (reference) | v3 (15) | working tree | 100.0 | 15/15 | 100% |
| beiming183-cloud/AutoCAD-MCP | v2 (10) | 11f7c47e |
50.0 | 5/10 | 50% |
| puran-water/autocad-mcp | v2 (10) | 95476a33 |
45.0 | 4/10 | 50% |
The competitor rows are the v1.4 runs, unchanged. Read the matrix column before the score column: the denominators differ because the five v3 tasks were added after those runs and have not been put to them.
Method and boundaries:
benchmarks/competitors_env.pyclones the pinned SHA intobenchmarks/.competitors/<id>/(gitignored), builds an isolated venv, and installs the competitor from its ownpyproject.toml.benchmarks/adapters/mcp_stdio.pydrives the competitor exactly like an MCP host (fastmcpClientover stdio). No competitor code is imported.- Task playbooks call each server's own documented tool contract, read from
the pinned source (consolidated
operation+ payload tools; beiming'sdoc_id/expected_revisiondiscipline is honored viatransaction(operation="context")). - Verification never trusts the competitor's response: every geometry claim
must survive
save/save_as_dxfand re-opening the DXF with ezdxf inside the harness. - Tasks with no documented equivalent are reported
unsupportedwith the reason string; they stay in the fixed-matrix denominator at score zero. - This lane is headless (ezdxf backends only). File-IPC / live-AutoCAD lanes (including COM-only servers such as best-cad-mcp or daobataotie/CAD-MCP) require a local AutoCAD session and are out of CI scope by design.
Published machine-readable reports (artifact paths sanitized to filenames)
live under results/published/; the README charts are
regenerated from them:
python -m benchmarks.run_competitors --server puran-water-autocad-mcp --backend ezdxf --matrix v2
python -m benchmarks.run_competitors --server beiming183-autocad-mcp --backend ezdxf --matrix v2
python -m benchmarks.render_live_chart # score bars
python -m benchmarks.render_matrix_chart # tasks x servers status heatmap
--publish <path> writes the same report with artifact paths reduced to
filenames, which is how results/published/ is produced; the sha256 stays,
because that is what makes an artifact checkable.
Headless performance lane
perf_suite.py measures wall time on fixed workloads through the same backend
methods the MCP tools call (server-side overhead included): 2,000 individual
line creates, a 10,000-entity build → DXF export → reopen roundtrip, a region
query over 10,000 entities, and a full premium quality pass (ISO layers,
geometry, dimensions, complete critique). The report records the machine
fingerprint; numbers move with hardware, workload definitions do not.
Self-measurement only — competitor servers would pay an extra stdio
serialization cost that in-process runs do not, so no cross-server timing
claims are made.
python -m benchmarks.perf_suite --out benchmarks/results/published/perf-ezdxf.json
python -m benchmarks.render_perf_chart
What the call-timeout guard costs
The published v1.4 report was recorded on CPython 3.14 and the later ones on
3.11.15, so comparing those two files directly shows an apparent 2–6× speedup
that is almost entirely the interpreter. The comparison that means something is
the guard against no guard, on one interpreter, back to back. Three runs of
each configuration, median taken by hand — perf_suite executes each workload
once per invocation and cannot produce a median itself:
| Workload | EZDXF_CALL_TIMEOUT=0 |
default (120 s) | Cost |
|---|---|---|---|
create_lines_2k |
243.7 ms | 294.3 ms | +20.8% |
roundtrip_10k |
1,709.6 ms | 2,049.2 ms | +19.9% |
v1.5.0 paid 28.6% on the first workload; v1.5.1 rebuilt the wrapper around a
single asyncio.timeout_at instead of two asyncio.wait_fors — wait_for
wraps its awaitable in a Task, so the old shape created two extra Tasks and two
timer handles per call — which recovered about a third of the overhead. The
rest is the Task the abandon-on-timeout design genuinely needs. The guard is
what stops one hung ezdxf call wedging a server whose document lock is a single
asyncio.Lock, so it stays; the knob is documented rather than hidden.
These figures are hand-collected and have no published artifact —
perf-ezdxf.json records one default-configuration run only. Reproduce:
for i in 1 2 3; do
python -m benchmarks.perf_suite --out /tmp/on-$i.json
EZDXF_CALL_TIMEOUT=0 python -m benchmarks.perf_suite --out /tmp/off-$i.json
done
Correctness A/B suite
correctness_suite.py is a set of deterministic, headless (ezdxf-backend) checks
that exercise real drawing operations. compare_versions.py runs the same
suite against an older git ref and the current checkout, each check in its own
subprocess so a hard crash (e.g. a matplotlib-in-thread SIGSEGV) is recorded as
a miss rather than taking down the run.
Reproduce:
python benchmarks/compare_versions.py # current tree vs origin/main
python benchmarks/compare_versions.py v1.0.0 # vs a tag/ref
python benchmarks/compare_versions.py --json results.json
Result — this branch (1.6.0-dev) vs v1.5.1 (release gate)
43 checks, ezdxf backend, one subprocess per check. Machine-readable report:
results/published/ab-v1.5.1-vs-v1.6.0-dev.json.
| Version | Checks passing | Pass rate | Fixed | Regressed |
|---|---|---|---|---|
| v1.5.1 (baseline) | 26 / 43 | 60.5 % | — | — |
| v1.6.0-dev (this branch) | 43 / 43 | 100 % | 17 | 0 |
The seventeen are all miss → pass — v1.5.1 has none of the methods. Four are track F: arch_junction_l_t_x (L, T and X junction outlines against hand-computed corners and wall areas), arch_room_area_net (a 4 × 5 m room between 200 mm walls is labelled 20.00 m², not its 21.84 m² axis area), arch_opening_cuts_wall (both faces interrupted across a door, two jambs) and arch_rooms_detect_foreign (plain lines on a WALLS layer read as 20 and 15 m² at confidence 0.6, nothing written). Seven
are tracks B and G: mech_part_roundtrip (a part read back from its own
ACADMCP_MECH XDATA equals the part drawn), mech_section_hatch_area (a
sleeve 60 long, ⌀40 outside, ⌀20 bore: a full section cuts two 60 × 10 faces,
1200 mm² exactly, measured out of the drawing by entity_measure — never from
the code that drew it), mech_iso286_on_dimension (ISO 286-1: 40 H7 is
+0.025 / 0, and the fit survives layout_dimensions),
mech_thread_unrepresented_is_caught (the ISO 6410 focus fires on a thread
drawn as a plain circle and stops firing once the thin ¾ arc is there — the
mechanical twin of dim_overlap_critique_fires), std_part_iso4014_m12 (ISO
4014:2011 table 1, M12: s = 18, k = 7.5, matched by value; the inserted block
carries its designation back), sheet_frame_iso5457_a3 (the frame runs 20,10
to 410,287 inside the 420 × 297 trimmed sheet) and bom_balloon_link (two
identical bolts collapse into one row of quantity 2 with a stable item number,
and that row's balloon carries it). The other six are the three
P&ID checks track A added (pid_block_define_attdef_roundtrip,
pid_tag_parse_fic, pid_graph_edge_count) and the three settings checks of
track E (settings_dimstyle_iso25_values: the ISO-25 preset reaches the
DIMSTYLE table with ISO 129-1's numbers, read back through ezdxf and not
through the lister; settings_layer_state_roundtrip: save → change → restore
puts the layer table back and the state survives save/reopen as an XRECORD in
the file; settings_pdf_mediabox_a3: the plotted PDF's own /MediaBox reads
420 × 297 mm). Every one of the 26 checks it was released on still passes, so
the four tracks added capability without moving a number it had already earned.
Result — v1.5.1 vs v1.5.0
26 checks at the time, ezdxf backend, one subprocess per check. Machine-readable report:
results/published/ab-v1.5.0-vs-v1.5.1.json.
| Version | Checks passing | Pass rate | Fixed | Regressed |
|---|---|---|---|---|
| v1.5.0 (baseline) | 24 / 26 | 92.3 % | — | — |
| v1.5.1 (that release) | 26 / 26 | 100 % | 2 | 0 |
v1.5.0 fails diameter_dim_measures_the_diameter and
radius_dim_ignores_the_leader_length: it has both methods and gets both
wrong. That is the defect 1.5.1 exists to fix and the reason 1.5.0 is yanked.
Result — v1.5.1 vs v1.4.0
Same 26-check suite, older baseline:
results/published/ab-v1.4.0-vs-v1.5.1.json.
| Version | Checks passing | Pass rate | Fixed | Regressed |
|---|---|---|---|---|
| v1.4.0 (baseline) | 21 / 26 | 80.8 % | — | — |
| v1.5.1 (that release) | 26 / 26 | 100 % | 5 | 0 |
This row used to read
v1.5.0 | 24 / 26 | 92.3 % | 5, which was impossible on its face — 21 passing plus 5 fixed is 26, not 24 — and it contradicted the report it linked. The cause is worth recording: the file namedab-v1.4.0-vs-v1.5.0.jsonwas regenerated from a tree that already carried the dimension fixes, so it never measured the v1.5.0 tag. The v1.5.0 tag really does score 24/26, which is what the v1.5.0-baseline table above reports. This table now names the tree it actually measured.
The pass rate is against the 26-check current suite; v1.4.0 passed 21/21 of the
checks that existed when it shipped. The five splits into two kinds, and the
difference is the whole reason this lane distinguishes miss from fail:
- Three are new capability. v1.4.0 has no
entity_measureand no boundary tracing, so it misseshatch_area_subtracts_its_island,boundary_area_agrees_with_measureandtwo_vertex_circle_has_areaby not having the method (miss → pass). They are in the suite because all three broke during v1.5.0 development and nothing outside their own unit tests would have caught it. - Two are repaired defects. v1.4.0 and v1.5.0 both have
dimension_diameteranddimension_radiusand both get them wrong (fail → pass):leader_length, a text placement, was being measured as geometry, so at default settings every diameter callout came out 2 ×leader_lengthtoo large. Only 1.5.1 passes them.
The 21 pre-existing checks are unchanged and all still pass: the discovery
layer, cad_batch, the 19-module contract split, the layout/viewport family
and Wave A landed with zero correctness regressions.
Result — v1.4.0 vs v1.3.0
21 checks. Report:
results/published/ab-v1.3.0-vs-v1.4.0.json.
| Version | Checks passing | Pass rate | Fixed | Regressed |
|---|---|---|---|---|
| v1.3.0 (baseline) | 21 / 21 | 100 % | — | — |
| v1.4.0 | 21 / 21 | 100 % | 0 | 0 |
Result — v1.1.0 vs v1.0.0 (origin/main, commit 15fa2bc)
21 checks, ezdxf backend, CPython 3.14, one subprocess per check.
| Version | Checks passing | Pass rate |
|---|---|---|
| v1.0.0 (public release) | 8 / 21 | 38.1 % |
| v1.1.0 (this release) | 21 / 21 | 100 % |
13 defects fixed, 0 regressions — a 2.6× higher correctness pass-rate (+61.9 pts).
Fixed (failed on v1.0.0, pass on v1.1.0):
| Check | Category | What it proves |
|---|---|---|
dim_aligned_no_error |
Dimensions | aligned dim no longer raises TypeError |
dim_angular_no_error |
Dimensions | angular dim no longer raises TypeError |
array_polar_360_distinct |
Modify | full-circle array no longer duplicates the original |
point_intersection_line_line |
Geometry | deterministic line/line intersection exists & is correct |
point_tangent_external |
Geometry | external-point tangent is perpendicular & on-circle |
arc_has_length |
Query | ARC carries a length property |
arc_select_by_length |
Query | entity_select_smart length_range selects arcs |
ezdxf_bounding_box |
Query | bounding_box populated (COM/ezdxf parity) |
mtext_rotation_roundtrip |
Entities | MTEXT honors caller rotation |
screenshot_png |
Render | headless render returns a valid PNG (no GUI-thread crash) |
dim_overlap_critique_fires |
Quality gate | dim_overlap critique is live (was a no-op) |
iso13567_dim_layer |
Quality gate | dimension_auto lands dims on the active set's layer |
gear_no_self_overlap |
Engineering | gear outline never dips inside the root circle (z ≥ 42) |
Passing on both versions (6 core ops + 2 others) keep the suite honest — it is not a cherry-picked list of failures; the baseline genuinely does basic CAD work.
Caveats / honesty notes
- The baseline is
origin/main(the public v1.0.0). All four audited fix sprints land between it and v1.1.0 — seedocs/analysis/. screenshot_pngon the baseline is host-dependent: it is recorded as a miss here because the default matplotlib backend is a GUI backend and the render runs off the main thread. On a host where matplotlib defaults toAgg, the baseline may not crash. v1.1.0 forcesAggand is deterministic.center_linetype_appliedpasses on both because it only checks the linetype attribute string (set on both); the v1.0.0 "renders as Continuous because the linetype was never loaded" defect is not observable throughEntityInfo.- COM-backend behaviour is not covered here (no live AutoCAD); see the mocked-COM
suites in
tests/.
Model-by-model tool-call success rates remain future work; scale/throughput numbers live in the headless performance lane above.