Add AgentTool.prepareArguments and ToolDefinition.prepareArguments hook
that runs before schema validation in the agent loop. This lets tools
silently accept legacy argument shapes from resumed old sessions without
polluting the public schema.
The built-in edit tool uses this to fold legacy top-level oldText/newText
into edits[] when resuming sessions that predate the edits-only schema.
- AgentTool/ToolDefinition: typed prepareArguments returning Static<TParameters>
- agent-loop: prepareToolCallArguments() runs before validateToolArguments()
- edit tool: prepareEditArguments folds legacy fields, validateEditInput is strict
- Documented in extensions.md with edit-tool example
When a provider (e.g., Google Gemini CLI) requests a retry delay longer
than maxDelayMs (default: 60s), the request fails immediately with an
informative error instead of waiting silently for hours.
The error is then handled by agent-level auto-retry, which shows the
delay to the user and allows aborting with Escape.
- Add maxRetryDelayMs to StreamOptions (packages/ai)
- Add maxRetryDelayMs to AgentOptions (packages/agent)
- Add retry.maxDelayMs to settings (packages/coding-agent)
- Update _isRetryableError to match 'retry delay' errors
fixes#1123
- Add sessionId to StreamOptions for providers that support session-based caching
- OpenAI Codex provider uses sessionId for prompt_cache_key and routing headers
- Agent class now accepts and forwards sessionId to stream functions
- coding-agent passes session ID from SessionManager and updates on session changes
- Update ai package README with table of contents, OpenAI Codex OAuth docs, and env vars table
- Increase Codex instructions cache TTL from 15 minutes to 24 hours
- Add tests for sessionId forwarding in ai and agent packages
- Remove per-thinking-level model variants (gpt-5.2-codex-high, etc.)
- Remove thinkingLevels from Model type
- Provider clamps reasoning effort internally
- Omit reasoning field when thinking is off
fixes#472
Breaking changes:
- Settings: 'hooks' and 'customTools' arrays replaced with 'extensions'
- CLI: '--hook' and '--tool' flags replaced with '--extension' / '-e'
- API: HookMessage renamed to CustomMessage, role 'hookMessage' to 'custom'
- API: FileSlashCommand renamed to PromptTemplate
- API: discoverSlashCommands() renamed to discoverPromptTemplates()
- Directories: commands/ renamed to prompts/ for prompt templates
Migration:
- Session version bumped to 3 (auto-migrates v2 sessions)
- Old 'hookMessage' role entries converted to 'custom'
Structural changes:
- src/core/hooks/ and src/core/custom-tools/ merged into src/core/extensions/
- src/core/slash-commands.ts renamed to src/core/prompt-templates.ts
- examples/hooks/ and examples/custom-tools/ merged into examples/extensions/
- docs/hooks.md and docs/custom-tools.md merged into docs/extensions.md
New test coverage:
- test/extensions-runner.test.ts (10 tests)
- test/extensions-discovery.test.ts (26 tests)
- test/prompt-templates.test.ts
Breaking change: replaces queueMessage() with two separate methods:
- steer(msg): interrupt mid-run, delivered after current tool execution
- followUp(msg): wait until agent finishes before delivery
Also renames:
- queueMode -> steeringMode/followUpMode
- getQueuedMessages -> getSteeringMessages/getFollowUpMessages
Refs #403
Agent.prompt() and Agent.continue() now throw if called while already
streaming, preventing race conditions and corrupted state. Use
queueMessage() to queue messages during streaming, or await the
previous call.
AgentSession.prompt() has the same guard with a message directing
users to queueMessage().
Ref #403
- agentLoop now accepts AgentMessage[] instead of single message
- agent.prompt() accepts AgentMessage | AgentMessage[]
- Emits message_start/end for each message in the array
- AgentSession.prompt() builds array with hook message + user message
- TUI now receives events for before_agent_start injected messages
- StreamFn type now allows returning Promise
- agent-loop awaits streamFn result
- createStreamFn takes getProxyUrl callback, reads settings on each call
- Removed Attachment from agent package (now in web-ui/coding-agent)
- Agent.prompt now takes (text, images?: ImageContent[])
- Removed transports from web-ui (duplicate of agent package)
- Updated coding-agent to use local message types
- Updated mom package for new agent API
Remaining: Fix AgentInterface.ts to compose UserMessageWithAttachments
- Renamed AppMessage to AgentMessage throughout
- New agent-loop.ts with AgentLoopContext, AgentLoopConfig
- Removed transport abstraction, Agent now takes streamFn directly
- Extracted streamProxy to proxy.ts utility
- Removed agent-loop from pi-ai (now in agent package)
- Updated consumers (coding-agent, mom) for AgentMessage rename
- Tests updated but some consumers still need migration
Known issues:
- AgentTool, AgentToolResult not exported from pi-ai
- Attachment not exported from pi-agent-core
- ProviderTransport removed but still referenced
- messageTransformer -> convertToLlm migration incomplete
- CustomMessages declaration merging not working properly
HookMessage (role: hookMessage) was being passed directly to transport
without transformation. Now it's transformed via messageTransformer
which converts it to a proper user message for the LLM.
- Rename HookAppMessage to HookMessage, isHookAppMessage to isHookMessage
- Remove entries array from SessionContext (use isHookMessage type guard instead)
- HookMessage.content now accepts string directly (not just array)
- Fix streamMessage type in AgentState (AppMessage, not Message)
- Rename CustomMessageComponent to HookMessageComponent
- Fix test hook to use pi.sendMessage
- Change from contextTransform (runs once at agent start) to preprocessor
- preprocessor runs before EACH LLM call inside the agent loop
- ContextEvent now uses Message[] (pi-ai format) instead of AppMessage[]
- Deep copy handled by pi-ai preprocessor, not Agent
This enables:
- Pruning rules applied on every turn (not just agent start)
- /prune during long agent loop takes effect immediately
- Compaction can use same transforms (future work)
- Add contextTransform option to Agent (runs before messageTransformer)
- Deep copy messages before passing to contextTransform (modifications are ephemeral)
- Add ContextEvent and ContextEventResult types
- Add emitContext() to HookRunner (chains multiple handlers)
- Wire up in sdk.ts when creating Agent with hooks
Enables dynamic context pruning: hooks can modify messages sent to LLM
without changing session data. See discussion #330.
Cleans up the temporary emitLastMessage plumbing since we now use
Agent.prompt(AppMessage) for hook messages instead of appendMessage+continue.
- Remove emitLastMessage parameter from Agent.continue()
- Remove from transport interface and implementations
- Remove from agentLoopContinue()
Instead of using continue() which validates roles, prompt() now accepts
an AppMessage directly. This allows hook messages with role: 'hookMessage'
to trigger proper agent loop with message events.
- Add overloads: prompt(AppMessage) and prompt(string, attachments?)
- sendHookMessage uses prompt(appMessage) instead of appendMessage+continue
When calling continue() with emitLastMessage=true, the agent loop
emits message_start/message_end events for the last message in context.
This allows messages added outside the loop (e.g., hook messages via
sendHookMessage) to trigger proper TUI rendering.
Changes across packages:
- packages/ai: agentLoopContinue() accepts emitLastMessage parameter
- packages/agent: Agent.continue(), transports updated to pass flag
- packages/coding-agent: sendHookMessage passes true when triggerTurn
- Add XHIGH_MODELS constant and getAvailableThinkingLevels() to AgentSession
- Update ThinkingSelectorComponent to accept availableLevels parameter
- Both shift+tab cycling and /thinking command now show xhigh for supported models
- Update types.ts documentation to list supported models
Add getApiKey hook to AgentLoopConfig that resolves API keys dynamically
before each LLM call. This allows short-lived OAuth tokens (e.g. GitHub
Copilot, Anthropic OAuth) to be refreshed between turns when tool
execution takes a long time.
Previously, the API key was resolved once when ProviderTransport.run()
was called and passed as a static string to the agent loop. If the loop
ran for longer than the token lifetime (e.g. 30 minutes for Copilot),
subsequent LLM calls would fail with expired token errors.
Changes:
- Add getApiKey hook to AgentLoopConfig (packages/ai)
- Call getApiKey before each LLM call in streamAssistantResponse
- Update ProviderTransport to pass getApiKey instead of static apiKey
- Update web-ui ProviderTransport with same pattern
- Add AgentToolUpdateCallback type and optional onUpdate callback to AgentTool.execute()
- Add tool_execution_update event with toolCallId, toolName, args, partialResult
- Normalize tool_execution_end to always use AgentToolResult (no more string fallback)
- Bash tool streams truncated rolling buffer output during execution
- ToolExecutionComponent shows last N lines when collapsed (not first N)
- Interactive mode handles tool_execution_update events
- Update RPC docs and ai/agent READMEs
fixes#44
- Add agentLoopContinue() to pi-ai for resuming from existing context
- Add Agent.continue() method and transport.continue() interface
- Simplify AgentSession compaction to two cases: overflow (auto-retry) and threshold (no retry)
- Remove proactive mid-turn compaction abort
- Merge turn prefix summary into main summary
- Add isCompacting property to AgentSession and RPC state
- Block input during compaction in interactive mode
- Show compaction count on session resume
- Rename RPC.md to rpc.md for consistency
Related to #128
Previously, Agent.emit() was called before state was updated (e.g., appendMessage).
This meant event handlers saw stale state - when message_end fired,
agent.state.messages didn't include the message yet.
Now state is updated first, then events are emitted, so handlers see
consistent state that matches the event.
- Add 'xhigh' to ThinkingLevel type in ai and agent packages
- Map xhigh to reasoning_effort: 'max' for OpenAI providers
- Add thinkingXhigh color token to theme schema and built-in themes
- Show xhigh option only when using codex-max models
- Update CHANGELOG for both ai and coding-agent packages
closes#143
- Added totalTokens field to Usage interface in pi-ai
- Anthropic: computed as input + output + cacheRead + cacheWrite
- OpenAI/Google: uses native total_tokens/totalTokenCount
- Fixed openai-completions to compute totalTokens when reasoning tokens present
- Updated calculateContextTokens() to use totalTokens field
- Added comprehensive test covering 13 providers
fixes#130
Previously, errors in turn_end events (e.g., from OpenRouter Auto Router)
were not captured in agent.state.error, making failed requests appear as
successful completions.
Fixes#6
