H-5721: Adopt canonical Panda preset + styled-system + ui-library pattern

[lunelson]

(WIP, not quite ready, just triggering AI reviews atm)

🌟 What is the purpose of this PR?

This PR restructures the HASH design system into a proper 3-package PandaCSS architecture, replacing the previous ad-hoc approach with one aligned to official Panda CSS documentation.

Background

The original goal was to emulate Park UI, the official component library from the Ark UI / Panda CSS maintainers. However, Park UI uses a shadcn-style registry approach where consumers copy component code into their projects rather than importing from a dependency. This pattern doesn't fit our use case of publishing reusable npm packages.

Instead, this PR implements the "External Package" pattern from Panda CSS docs—a 3-package solution optimized for library authors:

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│   ds-theme      │────▶│   ds-helpers    │────▶│  ds-components  │
│  (Panda Preset) │     │ (Styled System) │     │ (React + Ark UI)│
└─────────────────┘     └─────────────────┘     └─────────────────┘
        │                       │                       │
   Design tokens          css(), cva(),           Button, Checkbox,
   from Figma             tokens, jsx             Avatar, etc.

🔗 Related links

• Panda CSS: Component Library Guide — Architecture patterns we followed
• Park UI Preset — Reference for preset structure (not registry approach)
• Ark UI — Headless component primitives used in ds-components

🚫 Blocked by

• Resolution of @hashintel/refractive module (missing/not built) — causes TSC errors in components using refractive effects

🔍 What does this change?

Package Architecture

@hashintel/ds-theme — The Panda Preset

A pure PandaCSS preset that defines design tokens sourced from Figma variable exports:

• New codegen scripts: generate-colors.ts and generate-tokens.ts transform Figma JSON into Panda token definitions
• Dual exports:
  • Main export (.) — The preset for use in panda.config.ts
  • Theme export (./theme) — Raw color/token definitions for stories and helpers
• Token structure following Panda/Tailwind conventions:
  • Colors: gray.10, blue.50, accent.60 (core palette) + semantic tokens like bg.accent.bold, text.primary, border.neutral
  • Spacing: "3" = 4px, "5" = 8px, etc. (DEFAULT scale is implicit)
  • Radii: md.4 = 8px, md.full = 9999px, plus sm/lg/full scales
  • Typography: text-sm, text-base, font weights as strings ("medium", "semibold")

@hashintel/ds-helpers — The Styled System Package

The single source of truth for Panda CSS utilities across all consuming packages:

• Runs panda codegen using ds-theme preset
• Exports styled-system/* modules: css, cva, tokens, jsx, patterns, types
• Includes Ladle stories for visual documentation
• New: Playwright snapshot testing for visual regression

@hashintel/ds-components — The Component Library

React components built with Ark UI (headless) + Panda CSS (styling):

• Import path change: Components now import from local styled-system/* (generated via panda codegen with ds-theme preset) rather than @hashintel/ds-helpers/*
• Uses importMap in panda config to ensure type consistency
• Components: Avatar, Badge, Button, Checkbox, RadioGroup, SegmentedControl, Slider, Switch
• Storybook for documentation and development

Token Name Migrations

All components updated to use new token naming conventions:

Old Token	New Token
"default.3"	"3"
"spacing.1"	"2"
"border.neutral.default"	"border.neutral"
"bg.accent.bold.default"	"bg.accent.bold"
"surface.default"	"surface"
"radius.4"	"md.4"
"core.gray.20"	"gray.20"
fontWeight: 500	fontWeight: "medium"

Build System Changes

• Migrated ds-theme and ds-components to tsdown for faster builds
• Updated ESLint config for styled-system import resolution
• Added .gitignore / biome.jsonc entries for generated styled-system directories

Pre-Merge Checklist 🚀

🚢 Has this modified a publishable library?

This PR:

• does not modify any publishable blocks or libraries, or modifications do not need publishing
• modifies an npm-publishable library and I have added a changeset file(s)
• modifies a Cargo-publishable library and I have amended the version
• modifies a Cargo-publishable library, but it is not yet ready to publish
• modifies a block that will need publishing via GitHub action once merged
• I am unsure / need advice

📜 Does this require a change to the docs?

The changes in this PR:

• are internal and do not require a docs change
• are in a state where docs changes are not yet required but will be
• require changes to docs which are made as part of this PR
• require changes to docs which are not made in this PR
• I am unsure / need advice

🕸️ Does this require a change to the Turbo Graph?

The changes in this PR:

• do not affect the execution graph
• affected the execution graph, and the turbo.json's have been updated to reflect this
• I am unsure / need advice

⚠️ Known issues

1. @hashintel/refractive module not found — Components using refractive glass effects (SegmentedControl, Slider, Switch, Playground) fail TSC until this package is built/available
2. exactOptionalPropertyTypes errors — Some Ark UI component props and Storybook args have type mismatches with strict optional property checking (pre-existing, not introduced by this PR)

🐾 Next steps

1. Build/publish @hashintel/refractive to resolve remaining TSC errors
2. Fix exactOptionalPropertyTypes issues in component stories and Ark UI prop spreading
3. Apply same token migrations to @hashintel/petrinaut (partially complete in this PR)
4. Add more Playwright snapshot tests for component states
5. Consider publishing ds-theme and ds-helpers to npm for external consumption

🛡 What tests cover this?

• Playwright snapshot tests in ds-helpers — Visual regression testing for color/token stories
• TypeScript compilation — yarn lint:tsc in each package validates token name correctness
• Storybook build — Validates components render correctly with new token structure

❓ How to test this?

1. Checkout the branch
2. Run yarn install at repo root
3. Build the design system packages:

   cd libs/@hashintel/ds-theme && yarn build
   cd libs/@hashintel/ds-helpers && yarn build
   cd libs/@hashintel/ds-components && yarn codegen && yarn build

4. Run type checking:

   cd libs/@hashintel/ds-components && yarn lint:tsc

5. Launch Storybook to verify components:

   cd libs/@hashintel/ds-components && yarn storybook

6. Run snapshot tests:

   cd libs/@hashintel/ds-helpers && yarn test

📹 Demo

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 70.38%. Comparing base (86f263f) to head (ca7f1e2).
⚠️ Report is 1 commits behind head on main.

Additional details and impacted files

@@             Coverage Diff             @@
##             main    #8191       +/-   ##
===========================================
+ Coverage   59.26%   70.38%   +11.12%     
===========================================
  Files        1191      344      -847     
  Lines      113436    27726    -85710     
  Branches     4982     1407     -3575     
===========================================
- Hits        67232    19516    -47716     
+ Misses      45428     7960    -37468     
+ Partials      776      250      -526     

Flag	Coverage Δ
apps.hash-ai-worker-py	?
apps.hash-ai-worker-ts	?
apps.hash-api	0.00% <ø> (ø)
backend-integration-tests	?
blockprotocol.type-system	?
deer	?
error-stack	?
local.claude-hooks	?
local.harpc-client	?
local.hash-backend-utils	?
local.hash-graph-sdk	10.88% <ø> (ø)
local.hash-isomorphic-utils	?
local.hash-subgraph	?
rust.antsi	?
rust.deer	?
rust.error-stack	?
rust.harpc-codec	?
rust.harpc-net	?
rust.harpc-tower	66.80% <ø> (ø)
rust.harpc-types	?
rust.harpc-wire-protocol	?
rust.hash-codec	72.76% <ø> (ø)
rust.hash-graph-api	?
rust.hash-graph-authorization	?
rust.hash-graph-postgres-store	?
rust.hash-graph-store	?
rust.hash-graph-temporal-versioning	47.95% <ø> (ø)
rust.hash-graph-types	?
rust.hash-graph-validation	?
rust.hashql-ast	87.25% <ø> (ø)
rust.hashql-compiletest	?
rust.hashql-core	?
rust.hashql-diagnostics	?
rust.hashql-eval	68.54% <ø> (ø)
rust.hashql-hir	89.10% <ø> (ø)
rust.hashql-mir	88.29% <ø> (ø)
rust.hashql-syntax-jexpr	?
rust.sarif	?
sarif	?
tests.hash-backend-integration	?
unit-tests	?

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[github-actions]

Benchmark results

@rust/hash-graph-benches – Integrations

policy_resolution_large

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2002	$$26.3 \mathrm{ms} \pm 150 \mathrm{μs}\left({\color{gray}-1.602 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.28 \mathrm{ms} \pm 15.1 \mathrm{μs}\left({\color{gray}1.97 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$12.3 \mathrm{ms} \pm 84.0 \mathrm{μs}\left({\color{gray}-0.810 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$42.1 \mathrm{ms} \pm 277 \mathrm{μs}\left({\color{gray}-1.245 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$14.8 \mathrm{ms} \pm 122 \mathrm{μs}\left({\color{gray}3.64 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$23.5 \mathrm{ms} \pm 146 \mathrm{μs}\left({\color{gray}-2.101 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$36.9 \mathrm{ms} \pm 223 \mathrm{μs}\left({\color{lightgreen}-14.352 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$5.19 \mathrm{ms} \pm 40.8 \mathrm{μs}\left({\color{lightgreen}-74.595 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$18.6 \mathrm{ms} \pm 130 \mathrm{μs}\left({\color{lightgreen}-34.719 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.64 \mathrm{ms} \pm 17.8 \mathrm{μs}\left({\color{gray}-1.183 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.82 \mathrm{ms} \pm 15.0 \mathrm{μs}\left({\color{gray}-2.608 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$3.14 \mathrm{ms} \pm 13.7 \mathrm{μs}\left({\color{gray}-3.151 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.06 \mathrm{ms} \pm 37.7 \mathrm{μs}\left({\color{gray}-0.054 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.36 \mathrm{ms} \pm 12.8 \mathrm{μs}\left({\color{gray}-2.984 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$3.93 \mathrm{ms} \pm 20.7 \mathrm{μs}\left({\color{gray}-2.168 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.18 \mathrm{ms} \pm 24.1 \mathrm{μs}\left({\color{gray}-0.979 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.25 \mathrm{ms} \pm 12.1 \mathrm{μs}\left({\color{gray}-2.684 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$3.80 \mathrm{ms} \pm 14.7 \mathrm{μs}\left({\color{lightgreen}-5.028 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.55 \mathrm{ms} \pm 9.66 \mathrm{μs}\left({\color{red}6.58 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.49 \mathrm{ms} \pm 10.7 \mathrm{μs}\left({\color{red}5.83 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.59 \mathrm{ms} \pm 12.4 \mathrm{μs}\left({\color{red}6.23 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.81 \mathrm{ms} \pm 15.0 \mathrm{μs}\left({\color{red}7.38 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.69 \mathrm{ms} \pm 10.8 \mathrm{μs}\left({\color{red}7.24 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.87 \mathrm{ms} \pm 13.6 \mathrm{μs}\left({\color{red}6.30 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$2.91 \mathrm{ms} \pm 15.0 \mathrm{μs}\left({\color{gray}3.47 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.62 \mathrm{ms} \pm 12.8 \mathrm{μs}\left({\color{red}6.08 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$2.76 \mathrm{ms} \pm 10.9 \mathrm{μs}\left({\color{red}5.04 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.25 \mathrm{ms} \pm 17.3 \mathrm{μs}\left({\color{gray}4.19 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.86 \mathrm{ms} \pm 25.2 \mathrm{μs}\left({\color{red}5.22 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$3.02 \mathrm{ms} \pm 14.5 \mathrm{μs}\left({\color{gray}1.72 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.14 \mathrm{ms} \pm 14.1 \mathrm{μs}\left({\color{gray}3.32 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.79 \mathrm{ms} \pm 11.7 \mathrm{μs}\left({\color{red}5.52 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.04 \mathrm{ms} \pm 14.5 \mathrm{μs}\left({\color{red}5.55 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$38.7 \mathrm{ms} \pm 170 \mathrm{μs}\left({\color{gray}-1.795 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$75.7 \mathrm{ms} \pm 351 \mathrm{μs}\left({\color{gray}0.509 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$43.6 \mathrm{ms} \pm 224 \mathrm{μs}\left({\color{gray}3.39 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$45.6 \mathrm{ms} \pm 287 \mathrm{μs}\left({\color{gray}-0.163 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$54.1 \mathrm{ms} \pm 259 \mathrm{μs}\left({\color{gray}2.54 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$40.8 \mathrm{ms} \pm 145 \mathrm{μs}\left({\color{gray}0.973 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$415 \mathrm{ms} \pm 822 \mathrm{μs}\left({\color{gray}0.496 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$95.0 \mathrm{ms} \pm 376 \mathrm{μs}\left({\color{gray}0.036 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$84.0 \mathrm{ms} \pm 367 \mathrm{μs}\left({\color{gray}0.872 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$278 \mathrm{ms} \pm 676 \mathrm{μs}\left({\color{gray}-1.673 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$14.5 \mathrm{ms} \pm 61.9 \mathrm{μs}\left({\color{gray}-2.215 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$15.0 \mathrm{ms} \pm 90.1 \mathrm{μs}\left({\color{gray}1.49 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$15.3 \mathrm{ms} \pm 71.2 \mathrm{μs}\left({\color{gray}-0.858 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$15.1 \mathrm{ms} \pm 73.5 \mathrm{μs}\left({\color{gray}4.40 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$18.0 \mathrm{ms} \pm 79.3 \mathrm{μs}\left({\color{gray}-2.531 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$14.9 \mathrm{ms} \pm 69.2 \mathrm{μs}\left({\color{gray}-0.453 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$14.8 \mathrm{ms} \pm 73.3 \mathrm{μs}\left({\color{gray}-1.891 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$14.5 \mathrm{ms} \pm 55.5 \mathrm{μs}\left({\color{gray}-3.324 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$15.3 \mathrm{ms} \pm 67.0 \mathrm{μs}\left({\color{gray}-1.717 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$22.4 \mathrm{ms} \pm 147 \mathrm{μs}\left({\color{gray}-2.076 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity

Function	Value	Mean	Flame graphs
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/block/v/1	$$30.2 \mathrm{ms} \pm 278 \mathrm{μs}\left({\color{gray}-0.235 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/book/v/1	$$30.0 \mathrm{ms} \pm 293 \mathrm{μs}\left({\color{gray}-1.199 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/building/v/1	$$30.7 \mathrm{ms} \pm 296 \mathrm{μs}\left({\color{gray}-1.354 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/organization/v/1	$$29.5 \mathrm{ms} \pm 264 \mathrm{μs}\left({\color{gray}-4.697 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/page/v/2	$$30.5 \mathrm{ms} \pm 271 \mathrm{μs}\left({\color{gray}-1.804 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/person/v/1	$$30.6 \mathrm{ms} \pm 254 \mathrm{μs}\left({\color{gray}-1.720 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/playlist/v/1	$$29.5 \mathrm{ms} \pm 263 \mathrm{μs}\left({\color{gray}-4.835 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/song/v/1	$$29.6 \mathrm{ms} \pm 330 \mathrm{μs}\left({\color{gray}-4.084 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1	$$31.4 \mathrm{ms} \pm 277 \mathrm{μs}\left({\color{gray}0.760 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: bf5a9ef5-dc3b-43cf-a291-6210c0321eba	$$8.01 \mathrm{ms} \pm 30.5 \mathrm{μs}\left({\color{gray}1.24 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$47.1 \mathrm{ms} \pm 248 \mathrm{μs}\left({\color{gray}0.297 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$93.4 \mathrm{ms} \pm 392 \mathrm{μs}\left({\color{gray}0.451 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$52.8 \mathrm{ms} \pm 270 \mathrm{μs}\left({\color{gray}0.030 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$60.7 \mathrm{ms} \pm 384 \mathrm{μs}\left({\color{gray}0.939 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$69.1 \mathrm{ms} \pm 418 \mathrm{μs}\left({\color{gray}1.52 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$75.2 \mathrm{ms} \pm 376 \mathrm{μs}\left({\color{gray}1.41 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$50.9 \mathrm{ms} \pm 266 \mathrm{μs}\left({\color{gray}1.01 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$80.4 \mathrm{ms} \pm 322 \mathrm{μs}\left({\color{gray}4.31 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$57.5 \mathrm{ms} \pm 250 \mathrm{μs}\left({\color{gray}-0.376 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$65.4 \mathrm{ms} \pm 358 \mathrm{μs}\left({\color{gray}0.787 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$68.8 \mathrm{ms} \pm 314 \mathrm{μs}\left({\color{gray}3.23 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$70.2 \mathrm{ms} \pm 293 \mathrm{μs}\left({\color{gray}3.68 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$139 \mathrm{ms} \pm 618 \mathrm{μs}\left({\color{gray}4.10 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$135 \mathrm{ms} \pm 460 \mathrm{μs}\left({\color{gray}-0.260 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$39.8 \mathrm{ms} \pm 169 \mathrm{μs}\left({\color{lightgreen}-61.619 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$573 \mathrm{ms} \pm 1.17 \mathrm{ms}\left({\color{lightgreen}-6.391 \mathrm{\%}}\right) $$	Flame Graph