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codeflash-agent/plugin/references/shared/handoff-template.md
mashraf-222 270cb56cee
Feat/java language support (#12) 
* 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>
2026-04-14 18:49:41 -05:00

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Session: {{TAG}}

Current State

  • Branch: codeflash/{{DOMAIN_PREFIX}}-{{TAG}}
  • Base branch: (fill in after discovery)
  • Project root: (fill in after discovery)
  • Session status: in-progress | plateau | completed | escalated

Environment

  • Language: (fill in: Java 21, Python 3.12, Node 20, etc.)
  • Build tool: (fill in: Maven, Gradle, pip, npm, etc.)
  • Test command: (fill in after discovery)
  • GC / Runtime: (fill in: G1GC, ZGC, etc. — JVM only; omit for other languages)

Hotspot Summary

File Function Pattern Impact Status
(fill in after Phase 0 profiling)

Kept Optimizations

(none yet)

Discarded Experiments

(none yet)

Strategy & Decisions

  • Current strategy: (fill in after profiling — e.g., "collection swaps first, then algorithmic")
  • Pivots: (record each strategy change with reason)

Stop Reason

(fill in when session ends)

  • Why stopped: plateau / user request / escalation / all targets below threshold
  • What was tried last: (last 3 experiments and their outcomes)
  • What remains: (actionable targets that were deprioritized or not reached)

Next Steps

  1. Run discovery phase
  2. Run Phase 0 baseline profiling
  3. Begin experiment loop