pi-share / buildwithpi Session Loader
Load and parse session transcripts from pi-share URLs (shittycodingagent.ai, buildwithpi.ai, buildwithpi.com).
When to Use
Loading sessions: Use this skill when the user provides a URL like:
https://shittycodingagent.ai/session/?
Human summaries: Use --human-summary when the user asks you to:
Summarize what a human did in a pi/coding agent session Understand how a user interacted with an agent Analyze user behavior, steering patterns, or prompting style Get a human-centric view of a session (not what the agent did, but what the human did)
The human summary focuses on: initial goals, re-prompts, steering/corrections, interventions, and overall prompting style.
How It Works Session exports are stored as GitHub Gists The URL contains a gist ID after the ? The gist contains a session.html file with base64-encoded session data The helper script fetches and decodes this to extract the full conversation Usage
Get full session data (default)
node ~/.pi/agent/skills/pi-share/fetch-session.mjs "
Get just the header
node ~/.pi/agent/skills/pi-share/fetch-session.mjs
Get entries as JSON lines (one entry per line)
node ~/.pi/agent/skills/pi-share/fetch-session.mjs
Get the system prompt
node ~/.pi/agent/skills/pi-share/fetch-session.mjs
Get tool definitions
node ~/.pi/agent/skills/pi-share/fetch-session.mjs
Get human-centric summary (what did the human do in this session?)
node ~/.pi/agent/skills/pi-share/fetch-session.mjs
Human Summary
The --human-summary flag generates a ~300 word summary focused on the human's experience:
What was their initial goal? How often did they re-prompt or steer the agent? What kind of interventions did they make? (corrections, clarifications, frustration) How specific or vague were their instructions?
This uses claude-haiku-4-5 via pi -p to analyze the condensed session transcript.
Session Data Structure
The decoded session contains:
interface SessionData { header: { type: "session"; version: number; id: string; // Session UUID timestamp: string; // ISO timestamp cwd: string; // Working directory }; entries: SessionEntry[]; // Conversation entries (JSON lines format) leafId: string | null; // Current branch leaf systemPrompt?: string; // System prompt text tools?: { name: string; description: string }[]; }
Entry types include:
message - User/assistant/toolResult messages with content blocks model_change - Model switches thinking_level_change - Thinking mode changes compaction - Context compaction events
Message content block types:
text - Text content toolCall - Tool invocation with toolName and args thinking - Model thinking content image - Embedded images Example: Analyze a Session
Pipe entries through jq to filter
node ~/.pi/agent/skills/pi-share/fetch-session.mjs "
Count tool calls
node ~/.pi/agent/skills/pi-share/fetch-session.mjs "