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pi-share / buildwithpi Session Loader

pi-share

Load and parse session transcripts from shittycodingagent.ai/buildwithpi.ai/buildwithpi.com (pi-share) URLs. Fetches gists, decodes embedded session data, and extracts conversation history.

SKILL.md

Full skill instructions

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/?<gist_id>
  • https://buildwithpi.ai/​session/?<gist_id>
  • https://buildwithpi.com/​session/?<gist_id>
  • Or just a gist ID like 46aee35206aefe99257bc5d5e60c6121

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

  1. Session exports are stored as GitHub Gists
  2. The URL contains a gist ID after the ?
  3. The gist contains a session.html file with base64-encoded session data
  4. 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 "<url-or-gist-id>"

# Get just the header
node ~/​.pi/​agent/​skills/​pi-share/​fetch-session.mjs <gist-id> --header

# Get entries as JSON lines (one entry per line)
node ~/​.pi/​agent/​skills/​pi-share/​fetch-session.mjs <gist-id> --entries

# Get the system prompt
node ~/​.pi/​agent/​skills/​pi-share/​fetch-session.mjs <gist-id> --system

# Get tool definitions
node ~/​.pi/​agent/​skills/​pi-share/​fetch-session.mjs <gist-id> --tools

# Get human-centric summary (what did the human do in this session?)
node ~/​.pi/​agent/​skills/​pi-share/​fetch-session.mjs <gist-id> --human-summary

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 "<url>" --entries | jq 'select(.type == "message" and .message.role == "user")'

# Count tool calls
node ~/​.pi/​agent/​skills/​pi-share/​fetch-session.mjs "<url>" --entries | jq -s '[.[] | select(.type == "message") | .message.content[]? | select(.type == "toolCall")] | length'

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