Reduce context token usage by 79% — fix silent component exclusion (#161)

* Update create-agent-skills to match 2026 official docs, add /triage-prs command

- Rewrite SKILL.md to document that commands and skills are now merged
- Add new frontmatter fields: disable-model-invocation, user-invocable, context, agent
- Add invocation control table and dynamic context injection docs
- Fix skill-structure.md: was incorrectly recommending XML tags over markdown headings
- Update official-spec.md with complete 2026 specification
- Add local /triage-prs command for PR triage workflow
- Add PR triage plan document

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* [2.31.0] Reduce context token usage by 79%, include recent community contributions

The plugin was consuming 316% of Claude Code's description character budget
(~50,500 chars vs 16,000 limit), causing components to be silently excluded.
Now at 65% (~10,400 chars) with all components visible.

Changes:
- Trim all 29 agent descriptions (move examples to body)
- Add disable-model-invocation to 18 manual commands
- Add disable-model-invocation to 6 manual skills
- Include recent community contributions in changelog
- Fix component counts (29 agents, 24 commands, 18 skills)

Contributors: @trevin, @terryli, @robertomello, @zacwilliams,
@aarnikoskela, @samxie, @davidalley

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Fix: keep disable-model-invocation off commands called by /lfg, rename xcode-test

- Remove disable-model-invocation from test-browser, feature-video,
  resolve_todo_parallel — these are called programmatically by /lfg and /slfg
- Rename xcode-test to test-xcode to match test-browser naming convention

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Fix: keep git-worktree skill auto-invocable (used by /workflows:work)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat(converter): support disable-model-invocation frontmatter

Parse disable-model-invocation from command and skill frontmatter.
Commands/skills with this flag are excluded from OpenCode command maps
and Codex prompt/skill generation, matching Claude Code behavior where
these components are user-only invocable.

Bump converter version to 0.3.0.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

plugins/compound-engineering/agents/review/performance-oracle.md

@@ -1,9 +1,36 @@
 ---
 name: performance-oracle
-description: "Use this agent when you need to analyze code for performance issues, optimize algorithms, identify bottlenecks, or ensure scalability. This includes reviewing database queries, memory usage, caching strategies, and overall system performance. The agent should be invoked after implementing features or when performance concerns arise.\\n\\n<example>\\nContext: The user has just implemented a new feature that processes user data.\\nuser: \"I've implemented the user analytics feature. Can you check if it will scale?\"\\nassistant: \"I'll use the performance-oracle agent to analyze the scalability and performance characteristics of your implementation.\"\\n<commentary>\\nSince the user is concerned about scalability, use the Task tool to launch the performance-oracle agent to analyze the code for performance issues.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: The user is experiencing slow API responses.\\nuser: \"The API endpoint for fetching reports is taking over 2 seconds to respond\"\\nassistant: \"Let me invoke the performance-oracle agent to identify the performance bottlenecks in your API endpoint.\"\\n<commentary>\\nThe user has a performance issue, so use the performance-oracle agent to analyze and identify bottlenecks.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: After writing a data processing algorithm.\\nuser: \"I've written a function to match users based on their preferences\"\\nassistant: \"I've implemented the matching function. Now let me use the performance-oracle agent to ensure it will scale efficiently.\"\\n<commentary>\\nAfter implementing an algorithm, proactively use the performance-oracle agent to verify its performance characteristics.\\n</commentary>\\n</example>"
+description: "Analyzes code for performance bottlenecks, algorithmic complexity, database queries, memory usage, and scalability. Use after implementing features or when performance concerns arise."
 model: inherit
 ---
 
+<examples>
+<example>
+Context: The user has just implemented a new feature that processes user data.
+user: "I've implemented the user analytics feature. Can you check if it will scale?"
+assistant: "I'll use the performance-oracle agent to analyze the scalability and performance characteristics of your implementation."
+<commentary>
+Since the user is concerned about scalability, use the Task tool to launch the performance-oracle agent to analyze the code for performance issues.
+</commentary>
+</example>
+<example>
+Context: The user is experiencing slow API responses.
+user: "The API endpoint for fetching reports is taking over 2 seconds to respond"
+assistant: "Let me invoke the performance-oracle agent to identify the performance bottlenecks in your API endpoint."
+<commentary>
+The user has a performance issue, so use the performance-oracle agent to analyze and identify bottlenecks.
+</commentary>
+</example>
+<example>
+Context: After writing a data processing algorithm.
+user: "I've written a function to match users based on their preferences"
+assistant: "I've implemented the matching function. Now let me use the performance-oracle agent to ensure it will scale efficiently."
+<commentary>
+After implementing an algorithm, proactively use the performance-oracle agent to verify its performance characteristics.
+</commentary>
+</example>
+</examples>
+
 You are the Performance Oracle, an elite performance optimization expert specializing in identifying and resolving performance bottlenecks in software systems. Your deep expertise spans algorithmic complexity analysis, database optimization, memory management, caching strategies, and system scalability.
 
 Your primary mission is to ensure code performs efficiently at scale, identifying potential bottlenecks before they become production issues.