H-6472: Replace Biome with Oxfmt for formatting

[indietyp]

🌟 What is the purpose of this PR?

Replaces Biome with Oxfmt as the project formatter. Biome was only used for formatting (linter and import organizer were disabled), so this is a direct replacement.

Oxfmt picks up three things Biome had disabled pending v2: import sorting, package.json sorting, and Tailwind CSS class sorting.

🔗 Related links

• Oxfmt documentation

🔍 What does this change?

• Added oxfmt.config.ts with equivalent formatting rules
• Updated all biome format invocations to oxfmt across:
  • Root package.json (lint:format, fix:format)
  • .lefthook.yml pre-commit hook
  • Codegen scripts (hash-api, hash-isomorphic-utils, internal-api-client, ds-components, repo-chores)
• Updated mise install biome to mise install oxfmt in Dockerfiles and Vercel install scripts
• Updated editor extension recommendations (VS Code, Zed)
• Updated .github/actions/prune-repository to copy oxfmt.config.ts
• Updated .github/CONTRIBUTING.md tool list
• Removed biome.jsonc

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

📜 Does this require a change to the docs?

The changes in this PR:

• are internal and do not require a docs change

🕸️ Does this require a change to the Turbo Graph?

The changes in this PR:

• do not affect the execution graph

🐾 Next steps

• Replace ESLint with Oxlint

🛡 What tests cover this?

• CI lint:format step exercises oxfmt --check on the full repo

❓ How to test this?

1. Run yarn lint:format and confirm it passes
2. Run yarn fix:format and confirm it formats correctly
3. Confirm lefthook pre-commit hook runs oxfmt on staged files

[vercel]

The latest updates on your projects. Learn more about Vercel for GitHub.

3 Skipped Deployments

Project	Deployment	Actions	Updated (UTC)
hash	Ignored	Preview	May 21, 2026 12:30pm
hashdotdesign-tokens	Ignored	Preview	May 21, 2026 12:30pm
petrinaut	Skipped		May 21, 2026 12:30pm

[cursor]

PR Summary

Medium Risk
Medium risk because it changes repo-wide formatting tooling (CI lint step, pre-commit hooks, editor/mise tooling) and reformats many files, which can cause churn or unexpected formatter behavior despite minimal runtime code impact.

Overview
Replaces Biome with Oxfmt as the repo formatter, adding oxfmt.config.ts and updating yarn lint:format/fix:format, lefthook, mise/tooling configs, and GitHub workflows/actions/docs to reference oxfmt instead of Biome.

Applies large-scale reformatting across docs/skill markdown, YAML/JSONC examples, and TypeScript code (notably import sorting and formatting), and relaxes markdownlint table formatting enforcement (table-column-style: false) to accommodate the new output.

^{Reviewed by Cursor Bugbot for commit d14d80a. Bugbot is set up for automated code reviews on this repo. Configure here.}

[indietyp]

• H-6472: Replace Biome with Oxfmt for formatting #8716 👈 (View in Graphite)
• main

This stack of pull requests is managed by Graphite. Learn more about stacking.

[augmentcode]

🤖 Augment PR Summary

Summary: This PR replaces Biome with Oxfmt as the repository-wide formatter.

Changes:

• Adds oxfmt.config.ts with formatting rules and enables import/package.json/Tailwind sorting.
• Updates root and workspace scripts to use oxfmt for lint:format and fix:format.
• Updates the .lefthook.yml pre-commit formatting command to run Oxfmt on staged files.
• Updates codegen scripts/hooks (e.g. GraphQL codegen) to format generated outputs with Oxfmt.
• Updates tooling install paths (mise/Docker/Vercel) and editor extension recommendations to reference Oxfmt.
• Removes Biome configuration and drops the separate package.json lint/fix steps now covered by Oxfmt.

Technical Notes: CI formatting is now enforced via oxfmt --check, and oxfmt is added as a dev dependency.

_{🤖 Was this summary useful? React with 👍 or 👎}

[augmentcode]

Review completed. 2 suggestions posted.

Comment augment review to trigger a new review at any time.

[codspeed-hq]

Merging this PR will not alter performance

✅ 80 untouched benchmarks

---

_{Comparing bm/h-6472-replace-biome-with-oxfmt (d14d80a) with main (2d5ae4c)¹}

Footnotes

1. No successful run was found on main (2777c6f) during the generation of this report, so 2d5ae4c was used instead as the comparison base. There might be some changes unrelated to this pull request in this report. ↩

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 62.83%. Comparing base (2777c6f) to head (d14d80a).

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #8716      +/-   ##
==========================================
- Coverage   62.88%   62.83%   -0.06%     
==========================================
  Files        1368     1368              
  Lines      140738   140839     +101     
  Branches     5839     5859      +20     
==========================================
- Hits        88510    88503       -7     
- Misses      51297    51405     +108     
  Partials      931      931              

Flag	Coverage Δ
apps.hash-api	0.00% <ø> (ø)

Flags with carried forward coverage won't be shown. Click here to find out more.

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📢 Have feedback on the report? Share it here.

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[kube]

Thanks!

Rebased

[TimDiekmann]

Not really satisfied with this approach. The previous comments stated what was ignored and why.

[indietyp]

Same, thank you for the spot, when removing the annotation I tried to preserve the reasoning (as you can see in all the other places) but missed this one because it was a line comment and not a block comment and I got overzealous, fixed in d8b90f4. Checked the other places, they already have said comment, but accidentally removed that one. Sorry!

[TimDiekmann]

I thought license files were ignored?

[indietyp]

They are; that was a faux pas from my side. I forgot to rebase the LICENSE.md, fixed in d8b90f4

See the output of git range-diff at https://github.com/hashintel/hash/actions/runs/26183134386

[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	$$27.0 \mathrm{ms} \pm 166 \mathrm{μs}\left({\color{gray}0.890 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.41 \mathrm{ms} \pm 17.6 \mathrm{μs}\left({\color{gray}-0.179 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1001	$$13.9 \mathrm{ms} \pm 82.1 \mathrm{μs}\left({\color{red}6.58 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$42.9 \mathrm{ms} \pm 280 \mathrm{μs}\left({\color{gray}-0.545 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$14.6 \mathrm{ms} \pm 97.3 \mathrm{μs}\left({\color{gray}2.17 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1526	$$24.4 \mathrm{ms} \pm 188 \mathrm{μs}\left({\color{gray}-0.864 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$28.1 \mathrm{ms} \pm 191 \mathrm{μs}\left({\color{red}5.38 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.86 \mathrm{ms} \pm 21.6 \mathrm{μs}\left({\color{gray}4.09 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$15.0 \mathrm{ms} \pm 87.4 \mathrm{μs}\left({\color{red}10.8 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.76 \mathrm{ms} \pm 23.5 \mathrm{μs}\left({\color{gray}-0.567 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.02 \mathrm{ms} \pm 16.0 \mathrm{μs}\left({\color{gray}-0.323 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 51	$$3.38 \mathrm{ms} \pm 19.3 \mathrm{μs}\left({\color{gray}1.17 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.12 \mathrm{ms} \pm 26.5 \mathrm{μs}\left({\color{gray}-0.096 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.57 \mathrm{ms} \pm 22.9 \mathrm{μs}\left({\color{gray}-0.540 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 107	$$4.13 \mathrm{ms} \pm 23.5 \mathrm{μs}\left({\color{gray}-1.502 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.42 \mathrm{ms} \pm 26.3 \mathrm{μs}\left({\color{gray}-0.237 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.48 \mathrm{ms} \pm 27.3 \mathrm{μs}\left({\color{gray}0.275 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$4.10 \mathrm{ms} \pm 19.3 \mathrm{μs}\left({\color{gray}2.40 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.77 \mathrm{ms} \pm 18.9 \mathrm{μs}\left({\color{gray}-0.349 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.71 \mathrm{ms} \pm 12.6 \mathrm{μs}\left({\color{gray}0.156 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1	$$2.80 \mathrm{ms} \pm 12.3 \mathrm{μs}\left({\color{gray}-0.744 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$3.07 \mathrm{ms} \pm 11.1 \mathrm{μs}\left({\color{gray}-0.143 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.89 \mathrm{ms} \pm 18.8 \mathrm{μs}\left({\color{gray}0.577 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$3.18 \mathrm{ms} \pm 13.2 \mathrm{μs}\left({\color{gray}0.841 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$3.08 \mathrm{ms} \pm 13.8 \mathrm{μs}\left({\color{gray}0.314 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.79 \mathrm{ms} \pm 11.9 \mathrm{μs}\left({\color{gray}-0.129 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 25	$$2.96 \mathrm{ms} \pm 14.4 \mathrm{μs}\left({\color{gray}0.416 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.49 \mathrm{ms} \pm 17.4 \mathrm{μs}\left({\color{gray}-0.628 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.10 \mathrm{ms} \pm 13.9 \mathrm{μs}\left({\color{gray}0.743 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 26	$$3.33 \mathrm{ms} \pm 18.0 \mathrm{μs}\left({\color{gray}0.773 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.41 \mathrm{ms} \pm 14.4 \mathrm{μs}\left({\color{gray}-0.779 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.10 \mathrm{ms} \pm 23.0 \mathrm{μs}\left({\color{gray}1.75 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.30 \mathrm{ms} \pm 16.3 \mathrm{μs}\left({\color{gray}-0.419 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$44.7 \mathrm{ms} \pm 219 \mathrm{μs}\left({\color{gray}0.693 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$83.2 \mathrm{ms} \pm 403 \mathrm{μs}\left({\color{gray}2.77 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$50.0 \mathrm{ms} \pm 192 \mathrm{μs}\left({\color{gray}-1.255 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$52.5 \mathrm{ms} \pm 435 \mathrm{μs}\left({\color{gray}3.14 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$60.2 \mathrm{ms} \pm 214 \mathrm{μs}\left({\color{gray}-3.378 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$46.3 \mathrm{ms} \pm 151 \mathrm{μs}\left({\color{gray}0.857 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$423 \mathrm{ms} \pm 935 \mathrm{μs}\left({\color{gray}1.33 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$101 \mathrm{ms} \pm 430 \mathrm{μs}\left({\color{gray}0.088 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$83.5 \mathrm{ms} \pm 418 \mathrm{μs}\left({\color{gray}-0.630 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$286 \mathrm{ms} \pm 733 \mathrm{μs}\left({\color{gray}0.010 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$19.6 \mathrm{ms} \pm 101 \mathrm{μs}\left({\color{gray}1.95 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$20.3 \mathrm{ms} \pm 81.8 \mathrm{μs}\left({\color{gray}1.32 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$20.2 \mathrm{ms} \pm 100 \mathrm{μs}\left({\color{gray}-0.063 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$19.8 \mathrm{ms} \pm 90.6 \mathrm{μs}\left({\color{gray}-0.747 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$24.1 \mathrm{ms} \pm 82.5 \mathrm{μs}\left({\color{gray}-4.286 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$19.1 \mathrm{ms} \pm 72.7 \mathrm{μs}\left({\color{gray}-1.229 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$19.3 \mathrm{ms} \pm 86.5 \mathrm{μs}\left({\color{gray}-0.384 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$19.5 \mathrm{ms} \pm 112 \mathrm{μs}\left({\color{gray}0.794 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$19.9 \mathrm{ms} \pm 109 \mathrm{μs}\left({\color{gray}1.06 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$25.8 \mathrm{ms} \pm 182 \mathrm{μs}\left({\color{gray}-3.573 \mathrm{\%}}\right) $$	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	$$33.8 \mathrm{ms} \pm 246 \mathrm{μs}\left({\color{gray}-1.684 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/book/v/1	$$32.9 \mathrm{ms} \pm 219 \mathrm{μs}\left({\color{lightgreen}-7.189 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/building/v/1	$$32.7 \mathrm{ms} \pm 268 \mathrm{μs}\left({\color{lightgreen}-5.165 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/organization/v/1	$$33.8 \mathrm{ms} \pm 276 \mathrm{μs}\left({\color{gray}0.923 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/page/v/2	$$34.0 \mathrm{ms} \pm 253 \mathrm{μs}\left({\color{gray}-2.120 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/person/v/1	$$32.9 \mathrm{ms} \pm 248 \mathrm{μs}\left({\color{gray}-2.932 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/playlist/v/1	$$33.0 \mathrm{ms} \pm 228 \mathrm{μs}\left({\color{gray}-2.762 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/song/v/1	$$34.0 \mathrm{ms} \pm 250 \mathrm{μs}\left({\color{gray}-1.197 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1	$$34.4 \mathrm{ms} \pm 291 \mathrm{μs}\left({\color{gray}-0.064 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: bf5a9ef5-dc3b-43cf-a291-6210c0321eba	$$8.35 \mathrm{ms} \pm 44.1 \mathrm{μs}\left({\color{gray}-1.570 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$89.6 \mathrm{ms} \pm 411 \mathrm{μs}\left({\color{gray}-4.911 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$141 \mathrm{ms} \pm 424 \mathrm{μs}\left({\color{gray}0.163 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$96.7 \mathrm{ms} \pm 408 \mathrm{μs}\left({\color{gray}-4.493 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$105 \mathrm{ms} \pm 497 \mathrm{μs}\left({\color{gray}-4.232 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$113 \mathrm{ms} \pm 460 \mathrm{μs}\left({\color{gray}-3.364 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$121 \mathrm{ms} \pm 394 \mathrm{μs}\left({\color{gray}-2.276 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$99.8 \mathrm{ms} \pm 386 \mathrm{μs}\left({\color{gray}-0.342 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$128 \mathrm{ms} \pm 491 \mathrm{μs}\left({\color{gray}-0.304 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$106 \mathrm{ms} \pm 295 \mathrm{μs}\left({\color{gray}-2.254 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$115 \mathrm{ms} \pm 416 \mathrm{μs}\left({\color{gray}-1.338 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$117 \mathrm{ms} \pm 400 \mathrm{μs}\left({\color{gray}-1.024 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$118 \mathrm{ms} \pm 379 \mathrm{μs}\left({\color{gray}-1.289 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$139 \mathrm{ms} \pm 359 \mathrm{μs}\left({\color{gray}-1.324 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$152 \mathrm{ms} \pm 412 \mathrm{μs}\left({\color{gray}-1.213 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$108 \mathrm{ms} \pm 429 \mathrm{μs}\left({\color{gray}-1.971 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$557 \mathrm{ms} \pm 1.31 \mathrm{ms}\left({\color{lightgreen}-8.456 \mathrm{\%}}\right) $$	Flame Graph