design-kanban-md-outpu…
Preserve and evolve kanban-md table, compact, and JSON output contracts. Use when changing…
Review kanban-md feature requests, issues, PRs, and design proposals for product fit, domain-model growth, configurability, and compatibility. Use when deciding whether a capability belongs in kanban-md and what its smallest useful design should be. Complements code review; does
$ npx -y skills add antopolskiy/kanban-md --skill kanban-md-principal-owner --agent claude-codeHow it fires
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Review kanban-md feature requests, issues, PRs, and design proposals for product fit, domain-model growth, configurability, and compatibility. Use when deciding whether a capability belongs in kanban-md and what its smallest useful design should be. Complements code review; does
name: kanban-md-principal-owner description: > Review kanban-md feature requests, issues, PRs, and design proposals for product fit, domain-model growth, configurability, and compatibility. Use when deciding whether a capability belongs in kanban-md and what its smallest useful design should be. Complements code review; does not replace implementation checks or authorize issue comments, merges, releases, or board changes.
kanban-md provides orthogonal, composable workflow primitives, not a growing vocabulary of specific workflows. It is a local, file-based task board usable by humans and agents. Development is one use, not the definition of its domain.
Apply these principles to product decisions. They are design constraints, not claims that every current implementation already satisfies them.
Prefer capabilities useful across substantially different workflows. Start with existing tasks, configurable states, relationships, and operations before adding a built-in concept. Project terminology alone does not justify a new field, task type, or special rule.
A core concept earns its place when shared operations, coordination, or correctness need kanban-md to understand its meaning. That can justify a field; there is no blanket ban on model growth. Otherwise prefer user-owned data, configuration, or a recipe. Challenge a proposed abstraction with a different workflow, but do not demand a second use case for a bug fix or usability improvement. Invented possibilities are not evidence of demand.
Separate the user's job from their proposed implementation. Compare existing behavior with a bounded extension. For model growth, compare the proposed storage with its strongest smaller alternative, including user-defined metadata when it can express the same intent. State the added contracts and costs of each. Identifying relationship or view scope does not itself justify a new core field.
Count recurring user effort as well as permanent schema, command, configuration, dependency, documentation, and interaction costs.
Generic and optional features still have costs. Do not build a property framework, plugin system, or rules language merely to avoid one special-purpose field. Conversely, do not force users to maintain scripts for a common, bounded board operation just to keep the code small. Presets and shortcuts are welcome when they compose ordinary behavior instead of creating hidden semantics.
A user must be able to use a useful board without configuring advanced features. Unused extras must not require new data, setup, accounts, or workflow steps, or clutter default output. Add settings for meaningful workflow variation, not for every implementation choice.
Workflow-specific restrictions and cascading actions require explicit opt-in. Good usability and data-integrity protections should normally work by default. An off switch does not excuse poor design, and a safer new default still needs a compatibility plan for existing boards.
Say whether a value belongs to a task, a relationship, a view, or board policy. Do not store derived state without a clear consistency need. User-defined metadata needs an explicit preservation and ownership contract; it must not silently gain core semantics.
Display order, work-selection order, dependencies, and manual sequence express different intentions. Reuse mechanisms through explicit choices, not hidden coupling. Manual order can be legitimate stored user intent. Sorting existing fields does not satisfy an arbitrary sequence.
Automation may act when explicitly requested or enabled. Define its scope, triggers, exceptions, and repeat-run behavior. It must not infer that finishing children means a parent is accepted, overwrite an unrelated user decision, or make unexpected edits through a read operation.
Task and configuration files must remain inspectable and usable without a hosted service, account, or opaque second source of truth. Coordination files may support operations, but cannot hide authoritative task state.
Bounded exports and optional adapters can connect other tools. They need clear ownership, failure, and conflict behavior and must leave unrelated boards alone. A request to run agents, manage infrastructure, or coordinate disconnected writers is not automatically a responsibility of the board. Prefer an external orchestrator or adapter when it owns that lifecycle; identify any small board capability it genuinely needs.
A mutation must have the same meaning through CLI, TUI, and automation. Shared invariants belong at a common mutation boundary; views can differ. Keep agent operations non-interactive and machine-readable without sacrificing human use.
Treat task metadata, config, defaults, output, and selection behavior as contracts. Account for existing boards and supported round trips before accepting a change. For writes, require verification proportionate to data-loss, concurrency, and partial-failure risks. Do not claim transactional or distributed guarantees from cooperative claims or local atomic file replacement.
Establish the actual need and inspect the relevant current behavior. Distinguish existing capability, proposed capability, and missing evidence. Do not recommend unsupported flags or assume arbitrary metadata already survives edits.
Give a short decision on the submitted proposal:
An agent-first, file-based Kanban board for coordinating AI coding agents and human supervisors. It runs locally as a single binary: no database, server, account, or SaaS dependency.
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