FE-1652: Keep Brunch planning protocols outside the product repository

[lunelson]

🌟 What is the purpose of this PR?

Brunch's repository guidance had accumulated branch-specific planning machinery — missions, successor spines, ADRs, agent workflow protocols, archived research, evidence ledgers, evaluation protocols and oracles — alongside the durable product and development guidance. That made temporary process look like part of Brunch's permanent operating contract, and it forced CI to copy those directories into pruned builds.

This PR removes that planning machinery from the product repository and replaces it with two short documents describing what exists now: an implementation ARCHITECTURE.md and an EVALUATIONS.md for the one retained evaluation surface (browser-visible persona runs). Runtime code, prompts, skills and persona cases are unchanged apart from comment and guidance pointers.

🔗 Related links

• FE-1652: Keep planning protocols outside the product repository (internal)
• Stacked child: FE-1763: Let Brunch build Petrinaut nets as capably as the existing assistant #9811

🚫 Blocked by

None.

🔍 What does this change?

• Deletes Brunch's AGENTS.md, CLAUDE.md, CONTEXT.md, MISSION.md and MISSION.next.md, plus docs/adr/, docs/agents/, docs/archive/, docs/evidence/, docs/mission-*, docs/reference/, docs/research/ and docs/specs/.
• Deletes the evaluation protocols, oracles, answer keys and non-persona fixtures under evaluations/, keeping only the persona cases (opening-message.md and situation-pack.md).
• Removes the headless runbook construction probe (runbook:headless, src/evaluations/runbook/construction-run.ts) and its README section.
• Adds libs/@hashintel/brunch-agent/ARCHITECTURE.md (runtime composition, conversation and workpiece authority, invariants) and EVALUATIONS.md (persona-run operation and limits), and rewrites the Brunch README.md as a package map.
• Reduces apps/brunch-agent/AGENTS.md to HASH root guidance plus the application's dependency boundary, and restates the Flue/Pi patch boundary as a whole.
• Stops copying libs/@hashintel/brunch-agent/{docs,evaluations} in the prune-repository action and removes those paths from @apps/brunch-agent test inputs in turbo.json.
• Updates apps/petrinaut-website/MISSION.md, the persona-testing guide and a net-ledger.ts comment so nothing points at the deleted mission documents.

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:

• affected the execution graph, and the turbo.json's have been updated to reflect this

⚠️ Known issues

• EVALUATIONS.md lists seven maintained persona cases, but evaluations/cases/support-desk-staffing/ is also retained and discoverable by the launcher.
• Two test-fixture READMEs (apps/brunch-agent/test/fixtures/provider-accounting/, plugin-sdcpn/test/fixtures/reconciliation/) still name docs/evidence/... paths as the provenance of their checked-in fixtures. The fixtures remain self-contained; only the provenance references now point at deleted history.
• apps/petrinaut-website/README.md still refers to its MISSION.md as current, while this PR marks that file as historical FE-1722 scope.

🐾 Next steps

• The removed material remains available in Git history. Any planning that still needs a home belongs outside the product repository.

🛡 What tests cover this?

• No behavior changes. Existing @apps/brunch-agent and Brunch package suites pass in CI without the removed directories in the pruned build inputs.

❓ How to test this?

1. git grep -nE 'MISSION(\.next)?\.md|CONTEXT\.md|docs/adr|brunch-agent/docs/evidence' -- apps libs/@hashintel/brunch-agent .github returns only the fixture provenance and website README references listed under known issues.
2. yarn brunch:persona --list-cases still lists the persona cases.
3. yarn workspace @apps/brunch-agent test:unit

---

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[vercel]

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

Project	Deployment	Actions	Updated
hash	Ready	Preview	Sep 23, 2026 1:33pm UTC
hashdotdesign-tokens	Ready	Preview	Sep 23, 2026 1:33pm UTC
petrinaut	Ready	Preview	Sep 23, 2026 1:33pm UTC
petrinaut-docs	Ready	Preview	Sep 23, 2026 1:33pm UTC

[cursor]

PR Summary

Medium Risk
Removes a real construction/evaluation entrypoint and extensive agent/mission documentation that may still be relied on for process; runtime product code changes are minimal aside from a comment in net-ledger.ts.

Overview
Replaces the Brunch mission/ADR/agent charter stack with shorter operational docs (ARCHITECTURE.md, EVALUATIONS.md, slimmer READMEs) and drops large authority files (MISSION.md, MISSION.next.md, CONTEXT.md, AGENTS.md, and the ADR set).

Removes the headless runbook construction path: deletes construction-run.ts, the runbook:headless script, and related README/runbook references. Persona testing stays as the documented evaluation surface, with operator docs retargeted to EVALUATIONS.md and tighter wording on live-provider authorization and test scope.

CI and Turbo follow the slimmer tree: the prune action no longer copies @hashintel/brunch-agent/docs and evaluations into pruned checkouts, and test:unit no longer lists those paths as inputs. apps/petrinaut-website/MISSION.md is reframed as historical FE-1722 scope instead of pointing at the removed Brunch mission.

^{Reviewed by Cursor Bugbot for commit 5c01631. Bugbot is set up for automated code reviews on this repo. Configure here.}

[TimDiekmann]

infra ✅, still requires code reviewer.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 65.83%. Comparing base (0982b29) to head (5c01631).
⚠️ Report is 4 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #9810      +/-   ##
==========================================
+ Coverage   65.56%   65.83%   +0.27%     
==========================================
  Files        1896     1900       +4     
  Lines      201506   209432    +7926     
  Branches     8028     8185     +157     
==========================================
+ Hits       132115   137884    +5769     
- Misses      67841    70002    +2161     
+ Partials     1550     1546       -4     

Flag	Coverage Δ
antsi	1.96% <ø> (?)
apps.hash-ai-worker-ts	1.99% <ø> (ø)
apps.hash-api	15.35% <ø> (ø)
blockprotocol.type-system	38.15% <ø> (ø)
error-stack	90.55% <ø> (?)
harpc-codec	84.61% <ø> (?)
harpc-net	96.26% <ø> (?)
harpc-tower	67.11% <ø> (?)
harpc-types	0.00% <ø> (?)
harpc-wire-protocol	93.85% <ø> (?)
hash-codec	72.09% <ø> (?)
hash-config	83.57% <ø> (?)
hash-graph	14.11% <ø> (+1.78%)	⬆️
hash-graph-api	33.17% <ø> (+0.97%)	⬆️
hash-graph-atlas	80.00% <ø> (-0.20%)	⬇️
hash-graph-authentication	97.34% <ø> (?)
hash-graph-authorization	67.68% <ø> (?)
hash-graph-embeddings	91.54% <ø> (?)
hash-graph-postgres-store	31.94% <ø> (-0.15%)	⬇️
hash-graph-store	51.71% <ø> (?)
hash-graph-temporal-versioning	50.53% <ø> (?)
hash-graph-types	0.00% <ø> (?)
hash-graph-validation	85.37% <ø> (?)
hash-middleware	90.94% <ø> (?)
hashql-ast	90.01% <ø> (+0.39%)	⬆️
hashql-compiletest	28.71% <ø> (+0.30%)	⬆️
hashql-core	81.47% <ø> (?)
hashql-diagnostics	72.85% <ø> (?)
hashql-eval	79.77% <ø> (-0.30%)	⬇️
hashql-hir	89.10% <ø> (+<0.01%)	⬆️
hashql-mir	87.74% <ø> (+0.12%)	⬆️
hashql-syntax-jexpr	94.77% <ø> (+0.73%)	⬆️
local.claude-hooks	0.00% <ø> (ø)
local.harpc-client	51.49% <ø> (ø)
local.hash-backend-utils	3.27% <ø> (ø)
local.hash-graph-sdk	10.02% <ø> (ø)
local.hash-isomorphic-utils	12.22% <ø> (ø)
problematic	78.78% <ø> (?)

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

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[codspeed]

Merging this PR will improve performance by 18.61%

⚠️ 6 benchmarks measured no execution time

Nothing ran under measurement, usually because the compiler removed the code under test. These results are not comparable, so they count as unchanged.

Preventing compiler optimizations

⚠️ Different runtime environments detected

Some benchmarks with significant performance changes were compared across different runtime environments,
which may affect the accuracy of the results.

Open the report in CodSpeed to investigate

⚡ 2 improved benchmarks
✅ 96 untouched benchmarks

Performance Changes

	Benchmark	BASE	HEAD	Efficiency
⚡	bit_matrix/dense/iter_row[64]	169.2 ns	140 ns	+20.83%
⚡	bit_matrix/dense/iter_row[200]	206.7 ns	177.5 ns	+16.43%
⚠️	as_constant	< 1 ns	< 1 ns	N/A
⚠️	constant_equal	< 1 ns	< 1 ns	N/A
⚠️	constant_not_equal	< 1 ns	< 1 ns	N/A
⚠️	access	< 1 ns	< 1 ns	N/A
⚠️	runtime_equal	< 1 ns	< 1 ns	N/A
⚠️	runtime_not_equal	< 1 ns	< 1 ns	N/A

Tip

Curious why performance improved? Comment @codspeedbot explain why performance improved on this PR, or directly use the CodSpeed MCP with your agent.

---

_{Comparing ln/reduce-brunch-process (5c01631) with main (2b08b38)¹}

Footnotes

1. No successful run was found on main (6fbd2c7) during the generation of this report, so 2b08b38 was used instead as the comparison base. There might be some changes unrelated to this pull request in this report. ↩

[github-actions]

Benchmark results

hash-graph-benches – Integrations

policy_resolution_large

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2002	$$17.4 \mathrm{ms} \pm 322 \mathrm{μs}\left({\color{red}10.9 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.12 \mathrm{ms} \pm 16.1 \mathrm{μs}\left({\color{lightgreen}-17.623 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1002	$$8.34 \mathrm{ms} \pm 118 \mathrm{μs}\left({\color{red}6.64 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$28.5 \mathrm{ms} \pm 425 \mathrm{μs}\left({\color{lightgreen}-13.152 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$10.1 \mathrm{ms} \pm 107 \mathrm{μs}\left({\color{red}12.9 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1527	$$16.9 \mathrm{ms} \pm 177 \mathrm{μs}\left({\color{red}11.2 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$19.1 \mathrm{ms} \pm 268 \mathrm{μs}\left({\color{red}8.29 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.45 \mathrm{ms} \pm 36.2 \mathrm{μs}\left({\color{red}8.59 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$10.2 \mathrm{ms} \pm 83.0 \mathrm{μs}\left({\color{red}30.0 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$2.47 \mathrm{ms} \pm 26.1 \mathrm{μs}\left({\color{gray}2.70 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$1.90 \mathrm{ms} \pm 10.5 \mathrm{μs}\left({\color{lightgreen}-9.303 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 52	$$2.10 \mathrm{ms} \pm 20.5 \mathrm{μs}\left({\color{lightgreen}-5.941 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$3.21 \mathrm{ms} \pm 40.2 \mathrm{μs}\left({\color{lightgreen}-5.751 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.21 \mathrm{ms} \pm 22.5 \mathrm{μs}\left({\color{gray}-1.713 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 108	$$2.53 \mathrm{ms} \pm 23.1 \mathrm{μs}\left({\color{lightgreen}-5.225 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$2.73 \mathrm{ms} \pm 18.3 \mathrm{μs}\left({\color{lightgreen}-6.994 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.28 \mathrm{ms} \pm 16.4 \mathrm{μs}\left({\color{lightgreen}-14.651 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$2.61 \mathrm{ms} \pm 34.9 \mathrm{μs}\left({\color{gray}-4.466 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$1.72 \mathrm{ms} \pm 12.4 \mathrm{μs}\left({\color{gray}1.73 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$1.72 \mathrm{ms} \pm 13.6 \mathrm{μs}\left({\color{gray}3.96 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 2	$$1.81 \mathrm{ms} \pm 13.0 \mathrm{μs}\left({\color{red}8.43 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$1.92 \mathrm{ms} \pm 16.5 \mathrm{μs}\left({\color{gray}2.65 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$1.82 \mathrm{ms} \pm 14.4 \mathrm{μs}\left({\color{gray}2.98 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.00 \mathrm{ms} \pm 19.5 \mathrm{μs}\left({\color{gray}-2.752 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$1.91 \mathrm{ms} \pm 15.8 \mathrm{μs}\left({\color{gray}-2.344 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$1.78 \mathrm{ms} \pm 12.9 \mathrm{μs}\left({\color{gray}1.53 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 26	$$1.85 \mathrm{ms} \pm 11.2 \mathrm{μs}\left({\color{gray}-1.871 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$2.17 \mathrm{ms} \pm 22.7 \mathrm{μs}\left({\color{gray}0.145 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$1.92 \mathrm{ms} \pm 16.3 \mathrm{μs}\left({\color{gray}-3.587 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 27	$$2.01 \mathrm{ms} \pm 12.5 \mathrm{μs}\left({\color{gray}-3.113 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$2.10 \mathrm{ms} \pm 24.0 \mathrm{μs}\left({\color{gray}2.55 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$1.85 \mathrm{ms} \pm 7.21 \mathrm{μs}\left({\color{lightgreen}-6.943 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$2.00 \mathrm{ms} \pm 11.7 \mathrm{μs}\left({\color{gray}-0.469 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$21.1 \mathrm{ms} \pm 144 \mathrm{μs}\left({\color{gray}3.72 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$42.5 \mathrm{ms} \pm 330 \mathrm{μs}\left({\color{gray}0.676 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$24.8 \mathrm{ms} \pm 304 \mathrm{μs}\left({\color{red}9.34 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$25.3 \mathrm{ms} \pm 294 \mathrm{μs}\left({\color{gray}3.69 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$29.1 \mathrm{ms} \pm 259 \mathrm{μs}\left({\color{red}10.1 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$21.7 \mathrm{ms} \pm 239 \mathrm{μs}\left({\color{red}6.81 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$233 \mathrm{ms} \pm 1.27 \mathrm{ms}\left({\color{gray}4.64 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$54.1 \mathrm{ms} \pm 546 \mathrm{μs}\left({\color{gray}0.671 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$43.5 \mathrm{ms} \pm 350 \mathrm{μs}\left({\color{red}5.91 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$180 \mathrm{ms} \pm 1.20 \mathrm{ms}\left({\color{red}6.61 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$6.61 \mathrm{ms} \pm 78.2 \mathrm{μs}\left({\color{gray}-2.443 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$6.73 \mathrm{ms} \pm 75.3 \mathrm{μs}\left({\color{lightgreen}-5.976 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$6.98 \mathrm{ms} \pm 40.1 \mathrm{μs}\left({\color{gray}-2.304 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$6.65 \mathrm{ms} \pm 72.8 \mathrm{μs}\left({\color{gray}-2.547 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$7.17 \mathrm{ms} \pm 90.4 \mathrm{μs}\left({\color{lightgreen}-15.491 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$7.33 \mathrm{ms} \pm 66.1 \mathrm{μs}\left({\color{red}5.86 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$7.38 \mathrm{ms} \pm 92.1 \mathrm{μs}\left({\color{red}13.1 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$6.84 \mathrm{ms} \pm 95.2 \mathrm{μs}\left({\color{gray}3.30 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$6.72 \mathrm{ms} \pm 64.8 \mathrm{μs}\left({\color{gray}-1.447 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$7.05 \mathrm{ms} \pm 69.9 \mathrm{μs}\left({\color{gray}-1.937 \mathrm{\%}}\right) $$	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	$$6.79 \mathrm{ms} \pm 53.4 \mathrm{μs}\left({\color{gray}-2.810 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/book/v/1	$$7.28 \mathrm{ms} \pm 77.1 \mathrm{μs}\left({\color{red}5.42 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/building/v/1	$$7.17 \mathrm{ms} \pm 53.8 \mathrm{μs}\left({\color{gray}3.35 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/organization/v/1	$$7.07 \mathrm{ms} \pm 57.6 \mathrm{μs}\left({\color{gray}1.93 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/page/v/2	$$6.83 \mathrm{ms} \pm 29.8 \mathrm{μs}\left({\color{gray}-3.659 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/person/v/1	$$7.24 \mathrm{ms} \pm 61.4 \mathrm{μs}\left({\color{gray}3.71 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/playlist/v/1	$$7.19 \mathrm{ms} \pm 123 \mathrm{μs}\left({\color{gray}0.140 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/song/v/1	$$7.69 \mathrm{ms} \pm 61.1 \mathrm{μs}\left({\color{red}9.75 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1	$$7.31 \mathrm{ms} \pm 101 \mathrm{μs}\left({\color{red}6.10 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: bf5a9ef5-dc3b-43cf-a291-6210c0321eba	$$5.04 \mathrm{ms} \pm 22.6 \mathrm{μs}\left({\color{gray}-3.334 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$36.6 \mathrm{ms} \pm 293 \mathrm{μs}\left({\color{gray}-0.198 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$74.7 \mathrm{ms} \pm 831 \mathrm{μs}\left({\color{red}10.5 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$41.2 \mathrm{ms} \pm 437 \mathrm{μs}\left({\color{gray}2.18 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$48.9 \mathrm{ms} \pm 456 \mathrm{μs}\left({\color{red}9.12 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$54.6 \mathrm{ms} \pm 565 \mathrm{μs}\left({\color{red}6.98 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$63.7 \mathrm{ms} \pm 896 \mathrm{μs}\left({\color{red}8.55 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$30.3 \mathrm{ms} \pm 262 \mathrm{μs}\left({\color{red}15.9 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$46.3 \mathrm{ms} \pm 269 \mathrm{μs}\left({\color{red}6.62 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$34.9 \mathrm{ms} \pm 285 \mathrm{μs}\left({\color{red}16.2 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$41.4 \mathrm{ms} \pm 405 \mathrm{μs}\left({\color{red}22.4 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$41.5 \mathrm{ms} \pm 339 \mathrm{μs}\left({\color{red}14.7 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$41.6 \mathrm{ms} \pm 329 \mathrm{μs}\left({\color{red}13.6 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$76.9 \mathrm{ms} \pm 355 \mathrm{μs}\left({\color{gray}1.74 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$86.4 \mathrm{ms} \pm 557 \mathrm{μs}\left({\color{gray}4.94 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$14.0 \mathrm{ms} \pm 99.0 \mathrm{μs}\left({\color{gray}1.19 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$323 \mathrm{ms} \pm 1.00 \mathrm{ms}\left({\color{gray}1.97 \mathrm{\%}}\right) $$	Flame Graph

[kostandinang]

Nice cleanup! Easier to navigate, and removing planning material from product and CI paths makes sense.

A few notes:
The deleted ADRs and mission archive were historical, but held rationale for the current core/plugin shape. If that moves elsewhere, could the README link to it?

ARCHITECTURE.md omits draft_petrinaut_experiment, while EVALUATIONS.md lists seven of eight cases. Pointing to tool-catalogue.ts and --list-cases would avoid duplicate inventories.

client-integration.mdx still links to the deleted topology.md.

Non-blocking; noting for follow-up. Approving.