Pi returns tool results in format: {"content": [{"type": "text", "text": "..."}]}
Previously we were JSON.stringify-ing the whole object, showing as:
{"content":[{"type":"text","text":"..."}]}
Now we extract the actual text content for cleaner display.
The turn_end event includes toolResults array with toolName. Previously
the parsing only included toolCallId, now we also extract toolName so
the UI can display the correct tool name even when tool_result entries
arrive without a preceding tool_call.
When tool_result entries arrive without a matching tool_call, the transcript
was showing generic 'tool' as the name. Now pl-local parses toolName from
tool_execution_end events and passes it through, so the UI can display
the actual tool name (e.g., 'bash', 'Read', 'Ls') instead of 'tool'.
- Hoist PI_AGENT_SKILLS_DIR to module-level constant to avoid duplicate path computation
- Always create ~/.pi/agent/skills directory before early return in ensurePiSkillsInjected, so the path is valid when --skill flag is passed
- Add --skill ~/.pi/agent/skills to pi CLI invocation so it loads the paperclip skill
- Enable pi_local in the AgentConfigForm adapter type dropdown (was showing as coming soon)
The $AGENT_HOME environment variable was referenced by skills (e.g.
para-memory-files) but never actually set, causing runtime errors like
"/HEARTBEAT.md: No such file or directory" when agents tried to resolve
paths relative to their home directory.
Add agentHome to the paperclipWorkspace context in the heartbeat service
and propagate it as the AGENT_HOME env var in all local adapters.
Co-Authored-By: Paperclip <noreply@paperclip.ing>
Major improvements to the Pi local adapter:
Bug Fixes (Greptile-identified):
- Fix string interpolation in models.ts error message (was showing literal ${detail})
- Fix tool matching in parse.ts to use toolCallId instead of toolName for correct
multi-call handling and result assignment
- Fix dead code in execute.ts by tracking instructionsReadFailed flag
Feature Improvements:
- Switch from print mode (-p) to RPC mode (--mode rpc) to prevent agent from
exiting prematurely and ensure proper lifecycle completion
- Add stdin command sending via JSON-RPC format for prompt delivery
- Add line buffering in execute.ts to handle partial JSON chunks correctly
- Filter RPC protocol messages (response, extension_ui_request, etc.) from transcript
Cost Tracking:
- Extract cost and usage data from turn_end assistant messages
- Support both Pi format (input/output/cacheRead/cost.total) and generic format
- Add tests for cost extraction and accumulation across multiple turns
All tests pass (12/12), typecheck clean, server builds successfully.
