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@@ -13,6 +13,7 @@ Deliver the product described by the repository, specification, requirements, re
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Persist until the intended outcome is genuinely achieved.
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Do not stop at:
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- research,
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- planning,
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- a plausible conceptual design,
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@@ -26,6 +27,7 @@ The final result must be conceptually coherent, technically sound, usable, imple
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Bias toward action and completion.
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Resolve discoverable questions yourself through:
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- repository exploration,
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- web and literature research,
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- primary documentation,
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@@ -76,27 +78,35 @@ Maintain a concise durable Task Ledger in `harness/TASK_LEDGER.md`, unless an eq
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It should distinguish:
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### Goal and success criteria
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What outcome must ultimately exist.
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### Verified facts
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Facts established from authoritative sources, repository evidence, experiments, or direct observation.
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### Given facts
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Requirements or constraints explicitly supplied by me.
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### Assumptions
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Things currently treated as true but not yet verified.
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### Open questions
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Important unknowns.
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### Candidate hypotheses / designs
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Competing explanations or approaches that remain plausible.
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### Decisions
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Choices that have been made, together with their rationale and supporting evidence.
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### Current strategy
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The current high-level route toward the goal.
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Do not silently convert an assumption into a fact.
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@@ -179,6 +189,7 @@ Possible roles include:
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- integration reviewer.
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Give every subagent:
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- one bounded question or responsibility,
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- relevant context,
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- clear boundaries,
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@@ -215,15 +226,19 @@ For consequential, uncertain, difficult-to-reverse design problems, do not accep
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Use an idea-tournament process.
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### Generate
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Produce several materially different candidate solutions or hypotheses.
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Aim for diversity rather than cosmetic variations of one idea.
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### Explore
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Where useful, assign independent agents to develop promising candidates in greater depth.
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### Reflect
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Have independent critics examine candidates for:
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- correctness,
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- hidden assumptions,
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- internal consistency,
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@@ -238,6 +253,7 @@ Have independent critics examine candidates for:
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Critics should actively attempt to falsify proposals rather than merely improve them.
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### Rank
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Compare candidates against explicit criteria derived from the actual project goals.
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Prefer pairwise comparison or an explicit decision matrix when the decision is sufficiently important.
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@@ -245,6 +261,7 @@ Prefer pairwise comparison or an explicit decision matrix when the decision is s
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Do not rank based on eloquence.
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### Evolve
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Improve the strongest candidates.
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Combine complementary ideas when a hybrid is genuinely better.
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@@ -252,6 +269,7 @@ Combine complementary ideas when a hybrid is genuinely better.
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Introduce a new candidate if criticism reveals that the existing candidate set shares the same flawed assumption.
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### Decide
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Select an approach only when enough evidence exists to justify convergence.
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Record the decision and why alternatives lost.
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@@ -456,6 +474,7 @@ Do not equate technical functionality with usability.
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Use independent reviewers throughout the project, but select reviewers according to the artifact being evaluated.
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A conceptual or semantic design may need:
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- domain review,
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- consistency review,
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- adversarial / falsification review,
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@@ -463,6 +482,7 @@ A conceptual or semantic design may need:
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- and user-workflow review.
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A language may need:
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- ambiguity review,
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- grammar / round-trip review,
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- human-editability review,
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@@ -470,6 +490,7 @@ A language may need:
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- and version-control review.
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An implementation may need:
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- correctness review,
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- architecture review,
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- requirements review,
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@@ -481,6 +502,7 @@ A final release should receive a cross-disciplinary review rather than only a co
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Require concrete findings and evidence.
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For material findings:
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1. verify the finding,
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2. determine whether the problem is conceptual, specification-level, architectural, implementation-level, or interaction-level,
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3. fix it at the correct layer,
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@@ -562,11 +584,11 @@ Do not automatically use maximum reasoning for every delegated task.
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Allocate reasoning effort according to the task:
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* Use maximum reasoning for foundational semantic, methodological, formalization, metamodel, language-design, cross-domain synthesis, and other consequential hard-to-reverse decisions.
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* Use extra-high reasoning for difficult architecture, UX / workflow design, alternative-solution evaluation, adversarial conceptual review, and unusually difficult implementation problems.
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* Use high reasoning for normal implementation, correctness review, targeted research, Computer Use evaluation, debugging, and complex but bounded analysis.
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* Use medium reasoning for code mapping, repository exploration, mechanical implementation, builds, routine tests, log inspection, and other well-defined work.
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* Use lower effort only for genuinely trivial mechanical tasks.
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- Use maximum reasoning for foundational semantic, methodological, formalization, metamodel, language-design, cross-domain synthesis, and other consequential hard-to-reverse decisions.
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- Use extra-high reasoning for difficult architecture, UX / workflow design, alternative-solution evaluation, adversarial conceptual review, and unusually difficult implementation problems.
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- Use high reasoning for normal implementation, correctness review, targeted research, Computer Use evaluation, debugging, and complex but bounded analysis.
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- Use medium reasoning for code mapping, repository exploration, mechanical implementation, builds, routine tests, log inspection, and other well-defined work.
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- Use lower effort only for genuinely trivial mechanical tasks.
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Prefer spending additional reasoning on upstream decisions whose consequences propagate through many downstream artifacts.
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@@ -578,12 +600,18 @@ Use GPT-6 Astra model exclusively.
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## Application specification
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Create a modern clone of ARCADIA Capella using Rust Iced framework. It should be cross platform (supporting Windows and Linux at least). Use Rust exclusively (wherever possible & practical). Focus on making the application modern, extensible, intuitive and easy to use. Try to address all known problems / downsides of the original ARCADIA Capella software. When writing code and making software architecture decisions focus on long term maintainability, extensibility while making the project friendly for active development
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### General description
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Create a modern clone of ARCADIA Capella using Rust Iced framework. It should be cross platform (supporting Windows and Linux at least). Use Rust exclusively (wherever possible & practical).
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Focus on making the application modern, extensible, intuitive and easy to use. When writing code and making software architecture decisions focus on long term maintainability, extensibility while making the project friendly for active development
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Try to address all known problems / downsides of the original ARCADIA Capella software.
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Version 1 MVP in the form of working Operational Analysis layer is done.
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Version 2 MVP in the form of working Operation Analysis + System Analysis is done.
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You should make the 1-st release version of the project with fully feature complete Operation Analysis + System Architecture, according to this application specification.
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And the remaining ARCADIA layers will be added in future releases.
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You should make the 1st release version of the project with fully feature complete Operation Analysis + System Architecture, according to this application specification.
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Remaining ARCADIA layers will be added in future releases.
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Transitioning of model elements between layers (in both directions) should be easy and intuitive.
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@@ -591,33 +619,52 @@ Keep in mind that the target audience for the application are system engineers.
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The application should be a general systems modeling tool, like ARCADIA Capella or SysML v2
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You should implement most of the ARCADIA semantics, while adressing original ARCADIA Capella problems / downsides
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You should implement most of the ARCADIA semantics, while adressing original ARCADIA Capella problems / downsides
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The original ARCADIA Capella UI is very bloated, clunky, unintuitive and hard to use. In addition, it lacks a number of quality of life features. You should at all cost avoid making the same mistakes as the developers of the original ARCADIA Capella
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You should explore the functionality & UI of the original ARCADIA Capella to take the most useful and powerful ideas from it. While making them modern, easy to use and understand
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Original ARCADIA Capella uses "nested" elements to signify various relationships, such as "Containment relationship" or "Deployment relationship". Instead of using visually noisy arrows / graph edges. I pretty much like this approach and want to see something similar to it in this application
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Original ARCADIA Capella uses "nested" elements (visually nested) to signify various relationships, such as "Containment relationship" or "Deployment relationship". Instead of using visually noisy arrows / graph edges. I pretty much like this approach and want to see something similar to it in this application
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To explore the original ARCADIA Capella UI & semantics you may use web resources / web search / official and community docs. Or open the original ARCADIA Capella installed on this desktop machine for exploration
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Your second, parallel goal is to create a textual representation for ARCADIA, similar to SysML v2. So a user can either edit a system model using UI (graphical representation) or text. Both graphical and textual representations should be fully equivalent and have full parity. You may take inspiration from SysML v2. Both graphical and textual representations should have one overarching, concrete, unambiguous spec in reST format, similar to SysML v2 strictness
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The application should support both forms of editing
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The textual representation should be easily editable and understandble for both humans and AI
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The textual representation should be easily handled by version control tools such as Git
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Your second, parallel, goal is to create a textual representation for ARCADIA, similar to SysML v2. So a user can either edit a system model using UI (graphical representation) or text. Both graphical and textual representations should be fully equivalent and have full parity. You may take inspiration from SysML v2. Both graphical and textual representations should have one overarching, concrete, unambiguous spec in reST format, similar to SysML v2 strictness
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The application should support both forms of editing
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The textual representation should be easily editable and understandble for both humans and AI
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The textual representation should be easily handled by version control tools such as Git
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The underlying semantics of the textual / graphical representation should support traceability of various development artifacts (for example - code, CAD files, electrical schematics, Docx files and anything in between)
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The textual representation editor should have syntax highlighting and linting
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The project should also have a backend server / service that you can deploy. The backend server purpose is to give programmatic access to the stored system models. So, there also should be a clear REST API for querying, editing and working with models. The purpose of the REST API is to allow automation, scripting and AI-driven workflows
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An example could be - writing custom plugins for various domain specific software (version control software, CAD software etc...) to establish traceability between development artifacts and a system model
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The project should also have a backend server / service that you can deploy. The backend server purpose is to give programmatic access to stored system models. So, there also should be a clear REST API for querying, editing and working with models. The purpose of the REST API is to allow automation, scripting and AI-driven workflows
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An example could be - writing custom plugins for various domain specific software (version control software, CAD software etc...) to establish traceability between development artifacts and a system model
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The desktop application should contain built-in guide / help / tutorial with clear and concise info on modeling concepts, underlying semantics, common modeling scenarios and application features / how to use the app. It should be easy to navigate and explore
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@Computer
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@Computer
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### Semantic model / metamodel
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Requirements:
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- Textual notation.
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- Graphical notation.
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- Constraints and calculations.
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- Quantities and units.
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- State and behavior modeling.
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- Reusable model libraries.
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- Strong, standardized specification.
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- Strong, standardized API.
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### UI
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The focus should be on reducing system engineer's cognitive load when creating / working with a system model. Regardless of the model size (big or small).
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Long, homogeneous lists in the UI that require user to scroll far or search for a desired option for too long - is a bad design.
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## Active issues / current guidance
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Right now, the behavior & scenarios UI is hard to use. It contains static / uneditable diagrams, which is highly dubious. In addition, user workflow with the behavior & scenarios UI differ significantly from the other UIs - you can't edit diagrams and instead suppose to click on menus for model development
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Right now, the behavior & scenarios UI is hard to use. It contains static / uneditable diagrams, which is highly dubious. In addition, user workflow with the behavior & scenarios UI differ significantly from the other UIs - you can't edit diagrams and instead suppose to click on menus for model development
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---
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---
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The current project state is nowhere near the usability of the original ARCADIA Capella (despite its downfalls) or its functionality / semantics. You should focus on that by studying original ARCADIA Capella very closely and implementing its features in a modern, ergonomic and easy to use way
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The current project state is nowhere near the usability of the original ARCADIA Capella (despite its downfalls) or its functionality / semantics. You should focus on that by studying original ARCADIA Capella very closely and implementing its features in a modern, ergonomic and easy to use way
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