Lanjutan audit alur AI agent (round 2), mengisi celah yang tersisa dari
perpbaikan paralel tool di loop utama (74b1ad4) agar lebih mirip Claude Code.
- feat(subagent): eksekusi batch tool read-only paralel di subagent engine
(engine.rs). Tool::run sinkron, jadi pakai scoped OS thread (bounded
window 8); hasil dipertahankan dalam urutan panggilan asli. Batch dengan
tool mutating jatuh balik ke jalur sequential aman.
- feat(agent): auto-load AGENTS.md/CLAUDE.md/.cursorrules ke system prompt
tiap turn (seperti Claude Code load AGENTS.md saat startup). Fungsi
main_agent_prompt_with_project_context menempel blok PROJECT CONTEXT;
dibaca dari workspace root pertama & dibatasi 12k char.
- feat(prompt): arahan VERIFY AFTER EDIT — setelah edit/write, agent wajib
jalankan cargo check/clippy/test (atau lint/test sesuai stack) via bash
sebelum mengakhiri turn; perbaiki error yang terlihat, jangan klaim
'compiles/works' tanpa hasil nyata.
- feat(infra): build_rich_context kini membaca AGENTS.md & CLAUDE.md juga
(untuk explore_codebase/scout).
- test: +3 subagent engine (order paralel, kecepatan konkuren, fallback
mutating), +2 domain prompt (konteks proyek & fallback kosong).
Sebelumnya loop utama mengeksekusi semua tool call satu-per-satu
(sequential for loop). Seperti Claude Code, tool read-only yang
independen dalam satu pesan assistant (read/grep/glob/semantic_search
dsb.) kini dijalankan konkuren dengan bounded parallelism (max 8),
mengurangi latensi per turn secara signifikan untuk beban coding.
- feat(registry): tool_is_parallel_safe() — whitelist tool read-only
yang aman dijalankan paralel; tool mutating/shell tetap sequential
- feat(executor): is_parallel_safe() delegasi ke registry; ToolExecutor
trait Default=false (konservatif)
- fix(application): execute_tool_calls_in_parallel() — join_all +
semaphore bounded 8, hasil dikumpulkan dalam URUTAN panggilan asli
(kontrak OpenAI/Anthropic tool-result ordering)
- loop utama: batch paralel hanya jika SEMUA tool parallel-safe; jika
ada satu tool mutating, jatuh balik ke jalur sequential aman
- test: +2 registry test, +2 application test (konkurensi & urutan,
fallback batch mutating)
Ganti explore phase MANDATORY (3 subagent tiap turn, boros) dengan
tool explore_codebase yang DIPUTUSKAN agent sendiri (lazy, token-aware):
- hapus ExploreService trait + with_explore + Phase 0 dari turn loop
- ExploreServiceImpl kini jadi tool 'explore_codebase' (1 context-scout
subagent, read-only, cap output 4k chars)
- system prompt: instruksi TOKEN BUDGET (jawab langsung utk query simple,
panggil explore_codebase sekali utk task kompleks)
Loop utama kini adaptif & self-healing:
- max_tokens adaptif (800/1600/4096 by request length) — bukan selalu 4096
- temperature 0.2 saat tool-calling, 0.7 utk final answer
- ErrorTracker: deteksi tool error berulang → inject recovery note,
stop setelah 8 error total (bukan 50 iterasi sia-sia)
- auto-compact history > 60k chars sebelum LLM call
- tool output di-truncate ke 12k chars sebelum masuk konteks
Tambah 8 unit test (truncation, adaptive tokens, error tracker).
- Added `ExploreService` trait and `ExploreServiceImpl` struct to handle the exploration of codebase context before agent turns.
- Implemented three parallel subagents: Code Structure, Symbol Index, and Semantic Context, each with specific directives.
- Integrated the explore phase into the agent turn process, ensuring that each turn starts with a consolidated context message.
- Enhanced `spawn_agent_turn` function to include explore service wiring and context preparation.
- Add AppStateRest as the central state struct for managing TUI state.
- Implement InputState for handling user input, autocomplete, and history.
- Create MiscState to manage overlays, notifications, and editor state.
- Introduce ScrollState for viewport scrolling functionality.
- Develop TranscriptCache for efficient message rendering in the chat pane.
- Implement SimpleAgent and SimpleWorkflowEngine for agent lifecycle management.
- Add helper functions for managing effort levels and token counting.
- Organize state-related modules for better maintainability and clarity.
- Moved `AccessTier` and `SubagentEvent` enums to `zesdex_domain::subagent`.
- Consolidated workflow-related types into `zesdex_domain::workflow`.
- Updated references across the codebase to use the new domain models.
- Refactored tool execution logic to utilize a new `ToolExecutor` trait.
- Enhanced `AgentTurnService` to handle tool calls and events more effectively.
- Adjusted API handlers and state management to align with new domain structure.
feat(bootstrap): create temporary settings and config files to prevent data loss
refactor(edit_log): switch from Vec to VecDeque for efficient memory management
fix(gateway): ensure store directories are created before starting the API server
refactor(bgbash): implement a global singleton for BashControl
feat(auth): enhance session authentication middleware to use SessionRepository
fix(edit_log_repo): update to use VecDeque for in-memory edit log storage
fix(memory_repo): add newline escaping for frontmatter fields
fix(session_lock_repo): improve error handling for lock file operations
fix(bash_tools): prevent path traversal in job_id argument
refactor(delete): enforce empty directory deletion in file system tools
fix(edit): optimize string replacement to only replace the first occurrence
fix(git_cred): improve credential management with piped input to git commands
feat(git_operator): add safety filter to block destructive git operations
fix(shell): register background jobs in Bash control
feat(spawn): add access tier specification for pipeline stages
refactor(hive_mind): run directives concurrently for improved performance
fix(auth): update refresh token verification in the refresh handler
fix(chat): optimize LLM client usage based on model matching
fix(conversations): enhance message deletion to target specific indices
feat(api): add JWT authentication middleware for all API routes
fix(state): implement refresh token verification in JwtTokenService
fix(daemon): improve usage tracking with saturating addition
fix(tui): handle compacted messages in the TUI state management
feat(tui): implement status bar with connection and turn state indicators
feat(tui): create workflow panel for agent status and progress visualization
feat(web): introduce web frontend interface with static file serving
feat(ws): add WebSocket interface for real-time communication and session management
asepharyana