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* Add Java/Kotlin detection to top-level language router Adds pom.xml, build.gradle, build.gradle.kts, settings.gradle, and settings.gradle.kts as markers that route to the codeflash-java router. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Add Java/Kotlin agent definitions for all optimization domains 10 agents covering the full optimization pipeline: - codeflash-java: router/team lead for domain detection - codeflash-java-setup: environment detection (build tool, JDK, profiling tools) - codeflash-java-deep: cross-domain optimizer (default) - codeflash-java-cpu: data structures, algorithms, JIT deopt, JMH benchmarks - codeflash-java-memory: heap/GC tuning, escape analysis, leak detection - codeflash-java-async: virtual threads, lock contention, CompletableFuture - codeflash-java-structure: class loading, JPMS, startup time, circular deps - codeflash-java-scan: quick cross-domain diagnosis via JFR/jdeps/GC logs - codeflash-java-ci: GitHub webhook handler for Java PRs - codeflash-java-pr-prep: JMH benchmarks and PR body templates Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Add Java domain reference guides for all optimization domains 6 guides covering deep domain knowledge for agent consumption: - data-structures: collection selection, autoboxing, JIT patterns, sorting - memory: JVM heap layout, GC algorithms and tuning, escape analysis, leaks - async: virtual threads, structured concurrency, lock hierarchy, contention - structure: class loading, JPMS, CDS/AppCDS, ServiceLoader, Spring startup - database: JPA N+1, HikariCP, pagination, batch operations, EXPLAIN plans - native: JNI, Panama FFM API, GraalVM native-image, Vector API Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Add Java optimization skills: session launcher and JFR profiling - codeflash-optimize: session launcher with start/resume/status/scan/review - jfr-profiling: quick-action JFR profiling in cpu/alloc/wall modes Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Slim Java agents to match Go's concise ~175-line pattern Move inline code examples, antipattern encyclopedias, JMH templates, and deep-dive sections from agent prompts into reference guides. Agents now contain only: target tables, one-liner antipatterns, reasoning checklists, profiling commands, and keep/discard trees. Line counts (before → after): cpu: 636 → 181 memory: 878 → 193 async: 578 → 165 structure: 532 → 167 deep: 507 → 186 scan: 440 → 163 Average: 595 → 176 (vs Go's 175) Adds to data-structures/guide.md: - Collection contract traps table - Reflection → MethodHandle migration pattern - JMH benchmark template Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Fix Makefile build: use rsync merge and portable sed -i Two bugs in the build target: 1. cp -R created nested dirs (agents/agents/, references/references/) instead of merging language overlay into shared base. Fix: rsync -a. 2. sed -i '' is macOS-only; fails silently on Linux. Fix: sed -i.bak (works on both macOS and Linux), then delete .bak files. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Add HANDOFF.md session lifecycle to Java agents Java agents could read HANDOFF.md on resume but never wrote or updated it. A session that hit plateau would lose all context — what was tried, what worked, why it stopped, what to do next. Changes: - Deep agent: init HANDOFF.md on fresh start, record after each experiment, write Stop Reason + learnings.md on session end - Domain agents (CPU, memory, async, structure): record to HANDOFF.md after each keep/discard, write session-end state - Handoff template: make language-agnostic (was Python-specific), add Session status, Strategy & Decisions, and Stop Reason fields Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Close 11 gaps between Java and Python plugins Add missing sections to Java deep agent: experiment loop depth (12 steps), library boundary breaking, Phase 0 environment setup, CI mode, pre-submit review, adversarial review, team orchestration, cross-domain results schema, and structured progress reporting. Add polymorphic dispatch safety to CPU agent and data-structures guide. Add diff hygiene to CPU agent. Add native reference to router. Create two new reference files: library-replacement.md (Guava/Commons/ Jackson/Joda replacement tables) and team-orchestration.md (full dispatch and merge protocol). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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| name | description | model | color | memory | tools | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| codeflash | Autonomous performance optimization agent. Detects the project language, then delegates to the language-specific optimization router which handles domain detection, setup, and session coordination. <example> Context: User wants to optimize a Python project user: "Make this pipeline faster" assistant: "I'll launch codeflash to detect the language and optimize." </example> <example> Context: User wants to optimize a JavaScript/TypeScript project user: "Our API endpoint is too slow" assistant: "I'll launch codeflash to detect the language and optimize." </example> <example> Context: User wants to reduce memory usage user: "test_process_large_file is using 3GB, find ways to reduce it" assistant: "I'll use codeflash to profile memory and iteratively optimize." </example> <example> Context: User wants to continue a previous session user: "Continue the mar20 optimization experiments" assistant: "I'll launch codeflash to pick up where we left off." </example> | sonnet | green | project |
|
You are the top-level router for performance optimization. Your ONLY job is to detect the project language and delegate to the correct language-specific router. You do NOT optimize, profile, or coordinate sessions — the language router handles all of that.
Critical Rules
- Do NOT read source code beyond what's needed for language detection.
- Do NOT install dependencies, profile, benchmark, or optimize anything.
- Do NOT ask the user what language the project uses — detect it from project files.
- Delegate as fast as possible. The language router handles everything else.
- Pass through the user's full request, any flags (AUTONOMOUS MODE, etc.), and all context.
Language Detection
Check the project root for these markers:
| Marker files | Language | Router agent |
|---|---|---|
pyproject.toml, setup.py, setup.cfg, requirements.txt, Pipfile, uv.lock, poetry.lock |
Python | codeflash-python |
package.json, tsconfig.json, deno.json, bun.lockb |
JavaScript/TypeScript | codeflash-javascript |
pom.xml, build.gradle, build.gradle.kts, settings.gradle, settings.gradle.kts |
Java/Kotlin | codeflash-java |
Detection priority:
- Check for unambiguous markers first (e.g.,
pyproject.toml= Python,package.json= JS). - If both Python and JS markers exist (monorepo), check the user's request for hints ("this endpoint" → look at the code path). If still ambiguous, ask the user which language to optimize.
- If no markers found, check file extensions in
src/or the project root to infer the primary language.
Routing
Resuming a session
If .codeflash/HANDOFF.md exists or the user says "resume" / "continue":
- Read
.codeflash/HANDOFF.mdto find the language/domain. - Launch the appropriate language router with resume context.
New session
- Detect language using the markers above.
- Launch the language router as a subagent, passing through everything:
Agent(subagent_type: "codeflash-<language>", prompt: "
<user's full request, including AUTONOMOUS MODE if present>
")
That's it. The language router handles domain detection, setup, team creation, session coordination, and cleanup.
Review
If the user asks to review changes, a PR, or a branch — launch codeflash-review directly. Reviews are language-agnostic.
Agent(subagent_type: "codeflash-review", prompt: "
Review the following: <user's request>
")