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Combat disciplines: integrate techniques with content and monster AI #13

Description

@zoeyrose

Important

This issue is implemented in the fresh MIT-licensed Go server under the replacement program. Its gameplay and content-design decisions remain authoritative. C, CPython, classic packet, file-path, and enum details in the preserved specification are historical evidence only; do not copy, translate, or structurally port GPL implementation code.

Replacement implementation contract

Preserve trainer, respec, AI, telegraph, and tuning decisions. Player and monster AI submit the same typed Go action requests; native dialogue/content services replace runtime scripts.

The server remains authoritative, consumes versioned compiled content, and exposes bounded generated Game Protocol 1 messages. Pure rules may use a specifically approved typed CEL environment. Starlark is not part of this issue unless the separate residual-scripting decision explicitly approves it.

Required verification

  • Preserve every observable rule, balance decision, disclosure boundary, and anti-exploit invariant from the specification below.
  • Add deterministic Go unit/property tests and wrapper-managed scenario coverage at the appropriate integration boundary.
  • Add bounded malformed-input and persistence-failure cases where this feature accepts content, network, or stored data.
  • Add Go/Rust protocol conformance fixtures for every new cross-process field; the client must not reconstruct authoritative rules from prose.
  • Demonstrate that implementation and tests contain no copied GPL source/test material and execute no runtime Python.
Preserved product/design specification and historical implementation notes

Parent and roadmap

Outcome

Reuse the finished action vocabulary in trainers, respecialization, selected monster abilities, encounter telegraphs, and final progression tuning.

Scope

  • Add lore-appropriate instructors and masters-at-arms using the common purchase/refund contracts.
  • Give selected monsters authored techniques without forking player and AI action resolution.
  • Add bounded telegraphs/effects and coordinate them with rare/named encounter mechanics.
  • Tune point schedules, trees, cooldowns, recovery, and content reuse against Redesign player cap and endgame progression around level-101–115 group encounters #30's cap/Renown model.

Superseded path / cleanup target

Remove provisional commands/content and any monster-only copy of technique shapes, cooldowns, telegraphs, or registry data.

Acceptance criteria

  • Players can learn and respec through supported content using the same server contracts as UI/commands.
  • Representative monsters execute shared authored techniques with visible counterplay.
  • Technique progression respects the functional cap and does not create uncapped power.
  • Content validation finds no missing profile, technique, trainer, icon, or effect references.

Validation baseline

Before: discipline trees are player-focused systems without complete world or AI integration.

After: one combat vocabulary serves players, trainers, monsters, and encounter design.

Run instructor/respec quests, monster AI/action tests, encounter telegraph fixtures, whole-content validation, playtests, and client/server builds.

This issue is a bounded child of #27. The parent remains open until every sibling child is complete.

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