pi-share
Load and parse session transcripts from shittycodingagent.ai/buildwithpi.ai/buildwithpi.com/pi.dev (pi-share) URLs.
Skill by darkamenosa
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/darkamenosa-pi-share
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: data
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Node.js package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/pi-share
What's inside
- Skill name
pi-share- Description
- Load and parse session transcripts from shittycodingagent.ai/buildwithpi.ai/buildwithpi.com/pi.dev (pi-share) URLs. Fetches gists, decodes embedded session data, and extracts conversation history.
- License
- Apache-2.0
- Instructions
- 105 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (2)
- SKILL.md
- fetch-session.mjs
SKILL.md (first lines)
# pi-share / buildwithpi Session Loader
Load and parse session transcripts from pi-share URLs (shittycodingagent.ai, buildwithpi.ai, buildwithpi.com, pi.dev).
## 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>`
- `https://pi.dev/session/?<gist_id>`
- `https://pi.dev/session/#<gist_id>`
- Or just a gist ID like `46aee35206aefe99257bc5d5e60c6121`
- Or hash-prefixed shorthand 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
```bash
# 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:
```typescript
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
```bash
# 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'
```From darkamenosa/pi-setup, Apache-2.0.
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Signals
- Stars
- 18
- Forks
- 5
- Open issues
- 0
- Last commit (this folder)
- Aug 1, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/darkamenosa/pi-setup
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
pi-share skill. Agent Mart. https://agentmart.dev/skills/darkamenosa-pi-share (last updated 2026-10-24)