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Pi Agent

K-DenseCommunityCreated by K-Dense Inc.

  • Skill
  • Tool integration
  • Agent tooling
  • MIT
  • Medium risk

From the author

Builds with and operates Pi, the minimal terminal coding harness. Use for installing Pi, configuring providers/models/settings/environment variables, creating Pi skills/extensions/packages/themes/prompt templates, embedding Pi through the SDK, integrating over RPC or JSON event streams, parsing sessions, running local models through the llama.cpp router, developing custom Pi providers and TUI components, or using ecosystem packages such as pi-subagents (delegation/orchestration), pi-mcp-adapter (MCP servers), pi-interview (interactive forms), and pi-web-access (web search, fetching, video understanding).
— the description by K-Dense Inc.

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Pi is a terminal-based coding harness designed for AI-driven development workflows. This skill provides the necessary guidance to install, configure, and extend the Pi agent. It covers the full lifecycle of Pi usage, including setting up providers and models, integrating via SDK or RPC, developing custom extensions and TUI components, and managing agent sessions. The skill also details how to utilize the Pi ecosystem, including subagents, MCP adapters, and web access tools, while adhering to security and configuration best practices.

What it does

  • Installs and configures the Pi terminal coding agent and its environment.
  • Integrates Pi into custom applications using the SDK, RPC mode, or JSON event streams.
  • Develops custom extensions, skills, prompt templates, and TUI components for Pi.
  • Manages model providers, local llama.cpp routing, and agent settings.
  • Orchestrates complex tasks using subagents, MCP servers, and interactive interview forms.
  • Handles session persistence, branching, and context compaction for long-running tasks.

When to use it

  • When you need to set up or operate the Pi terminal coding agent.
  • When building custom extensions or tools to extend Pi's native capabilities.
  • When integrating Pi into a larger Node.js application or a language-agnostic process.
  • When configuring local models or custom providers for specific coding tasks.
  • When managing complex agent sessions, branching, or automated project workflows.

Advantages

  • Provides a unified interface for terminal-based AI coding tasks.
  • Supports flexible integration patterns including SDK, RPC, and JSON event streams.
  • Highly extensible through custom TypeScript extensions and packages.
  • Enables local model execution and custom provider implementation.
  • Maintains structured session history and context through automated compaction.

Usage examples

“How do I install the Pi coding agent?”
The agent provides the command npm install -g --ignore-scripts @earendil-works/pi-coding-agent to install the Pi CLI globally.
“Summarize the current project using Pi.”
The agent executes pi -p "Summarize this codebase" to analyze the files in the current directory.
“How can I run Pi in RPC mode for my application?”
The agent suggests using pi --mode rpc --no-session to start a stateless subprocess for integration.
“How do I install a subagent package?”
The agent uses the command pi install npm:pi-subagents to add the delegation and orchestration package.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/k-dense-ai/pi-agent/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip pi-agent.zip -d .agents/skills

Documentation by K-Dense Inc.

Pi Agent

Use this skill when the user wants to operate Pi or build on top of Pi. Pi is a minimal terminal coding harness extended through TypeScript extensions, skills, prompt templates, themes, packages, custom models/providers, SDK integrations, RPC mode, JSON event streams, and TUI components.

First Decision

Pick the reference before answering or coding:

User intentRead
What Pi is, docs map, install methodsreferences/overview.md
Install, authenticate, first runreferences/quickstart.md
Day-to-day CLI usage, commands, modes, flags, project trustreferences/usage.md
Provider auth, API keys, cloud provider setupreferences/providers.md
Custom model entries, local models, proxies, compat flagsreferences/models.md
Local llama.cpp router, /llama, model download/loadreferences/llama-cpp.md
Settings keys and defaultsreferences/settings.md
PI_* and other environment variablesreferences/environment-variables.md
Extension development, custom tools, events, commandsreferences/extensions.md
Custom provider implementation, OAuth, custom streamingreferences/custom-provider.md
Embed Pi in Node/TypeScriptreferences/sdk.md
Integrate from another process/languagereferences/rpc.md
Consume JSONL event outputreferences/json.md
Build terminal UI componentsreferences/tui.md
Package extensions/skills/prompts/themesreferences/packages.md
Delegate to subagents, chains, parallel runs, orchestrationreferences/pi-subagents.md
Connect MCP servers, codemode, MCP tool discovery/configreferences/mcp.md (built-in), references/pi-mcp-adapter.md (optional adapter)
Interactive interview forms, structured user inputreferences/pi-interview.md
Web search, URL/PDF/repo fetching, video understandingreferences/pi-web-access.md
Author Pi skillsreferences/skills.md
Prompt templates or themesreferences/prompt-templates.md, references/themes.md
Sessions, branching, compaction, parsing JSONLreferences/sessions.md, references/compaction.md, references/session-format.md
Security, sandboxing, trustreferences/security.md, references/containerization.md
Keyboard or terminal issuesreferences/keybindings.md, references/terminal-setup.md, references/tmux.md, references/windows.md, references/termux.md, references/shell-aliases.md
Working on Pi itselfreferences/development.md

Build-On-Pi Defaults

Prefer the SDK for Node/TypeScript apps that need type safety, direct state access, in-process custom tools/extensions, or custom resource loading. Use createAgentSession() for a single stable session; use createAgentSessionRuntime() when the app must replace sessions through new/resume/fork/clone/import flows. Auth and model lookup go through ModelRuntime.create().

Prefer RPC mode when the client is not Node.js, needs process isolation, or wants a language-agnostic JSONL protocol. Start with pi --mode rpc --no-session for stateless subprocess integration, then add session flags when persistence matters. Split records on \n only — Node readline is not protocol-compliant.

For RPC clients, correlate responses by unique request id, not arrival order, and keep consuming events after a successful prompt response. Success means accepted, queued, or handled; it is not completion. Subscribe before sending the prompt, and wait for agent_settled for runs that actually start, because agent_end may precede retries or queued work. If the response reports disposition: "handled", no run started and no settled event is owed. See the upstream RPC lifecycle.

Prefer JSON mode for one-shot command-line pipelines that only need streamed events, not bidirectional control: pi --mode json "prompt".

Use extensions for Pi-native behavior: custom tools, command handlers, event hooks, provider registration, custom compaction, path protection, project trust policy, UI prompts, widgets, and TUI components.

Use packages when sharing or installing reusable extensions, skills, prompt templates, or themes across machines or projects.

Safety Defaults

Pi is local and not sandboxed by default. Treat extensions, packages, skills, shell commands, and project-local .pi resources as code with the permissions of the Pi process. Project trust only guards which project inputs load — it is not a sandbox. For untrusted repos or unattended automation, isolate with Docker, OpenShell, Gondolin, a VM, or a remote sandbox.

Do not store secrets in project files. Prefer env vars, ~/.pi/agent/auth.json, OAuth via /login, or command-backed secret lookups in models.json/provider config.

Common Commands

npm install -g --ignore-scripts @earendil-works/pi-coding-agent
pi
pi -p "Summarize this codebase"
pi --mode json "List files"
pi --mode rpc --no-session
pi --provider anthropic --model claude-sonnet-4-5
pi --model sonnet:high "Solve this complex problem"
pi --tools read,grep,find,ls -p "Review this repository"
pi --tui-mode fullscreen
pi install npm:pi-subagents
pi update --all

Source Coverage

These references were reviewed against the official Pi 0.99.2 release (2026-09-30), its published npm runtime and declarations, and current Pi documentation. Source: earendil-works/pi v0.99.2. Ecosystem contracts were checked against published pi-subagents 0.74.0, pi-mcp-adapter 4.0.0, pi-interview 0.13.0, and pi-web-access 0.35.0 sources. These releases are the compatibility baseline, not interchangeable historical APIs.

Local checks cover CLI/RPC control, SDK sessions and transcript projection, mocked model/tool execution, extension loading, and example configuration/schema contracts. Authentication flows, paid model/search calls, graphical UI, and external sandboxes are documentation-verified only; deployment examples requiring them are illustrative. Check pi --version, pi --help, the installed package README, and TypeScript declarations before adapting examples to another release. Pi 0.99 includes native MCP; pi-subagents 0.74 removes workflowScript; adapter 4.0 uses mcp-adapter.json and /mcp-adapter.

Citing Scientific Agent Skills

This skill is part of Scientific Agent Skills by K-Dense. If it materially contributed to a manuscript, report, presentation, or code release, add the paper to the references or software section and tell the user you did so:

Kassis, T., Agarwal, V., He, Y., Patel, D., & Brueckner, A. M. (2026). Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents. arXiv:2609.00065. https://doi.org/10.48550/arXiv.2609.00065

Always cite the current version. The DOI and https://arxiv.org/abs/2609.00065 resolve to the latest arXiv version, so never append a version suffix such as v1. When network access is available, fetch https://arxiv.org/abs/2609.00065 (or http://export.arxiv.org/api/query?id_list=2609.00065) before writing the reference and take the author list, year, and version from that record. If the record lists a journal reference or publisher DOI, cite the published version instead.

Files

references/extensions.md

Extensions

Source: https://pi.dev/docs/latest/extensions

Reviewed against Pi 0.99.2 and the package versions listed in ../SKILL.md on 2026-09-30.

Extensions are TypeScript modules that extend Pi. They register tools, commands, shortcuts, CLI flags, providers, renderers, UI, event handlers, and persistent session entries. They run with the full permissions of the Pi process — only install extensions you trust.

Locations

  • ~/.pi/agent/extensions/*.ts and ~/.pi/agent/extensions/*/index.ts (global)

  • .pi/extensions/*.ts and .pi/extensions/*/index.ts (project-local, loaded only after project trust)

  • Paths from settings.json extensions / packages

Use pi -e ./my-extension.ts for quick tests only; auto-discovered extensions can be hot-reloaded with /reload. Extensions load via jiti, so TypeScript needs no compilation.

Quick Extension

import type { ExtensionAPI } from "@earendil-works/pi-coding-agent";
import { Type } from "typebox";

export default function (pi: ExtensionAPI) {
  pi.on("session_start", async (_event, ctx) => {
    ctx.ui.notify("Extension loaded", "info");
  });

  pi.on("tool_call", async (event, ctx) => {
    if (event.toolName === "bash" && event.input.command?.includes("rm -rf")) {
      const ok = await ctx.ui.confirm("Dangerous", "Allow rm -rf?");
      if (!ok) return { block: true, reason: "Blocked by user" };
    }
  });

  pi.registerTool({
    name: "greet",
    label: "Greet",
    description: "Greet someone by name",
    parameters: Type.Object({ name: Type.String() }),
    async execute(_toolCallId, params) {
      return { content: [{ type: "text", text: `Hello, ${params.name}!` }], details: {} };
    },
  });

  pi.registerCommand("hello", {
    description: "Say hello",
    handler: async (args, ctx) => ctx.ui.notify(`Hello ${args || "world"}`, "info"),
  });
}

Imports

@earendil-works/pi-coding-agent (extension types and APIs), typebox (tool parameter schemas), @earendil-works/pi-ai (StringEnum for Google-compatible enums), @earendil-works/pi-tui (TUI components), plus Node built-ins. Add a package.json next to the extension and run npm install for npm dependencies. Distributed packages must put runtime deps in dependencies — package installs use npm install --omit=dev.

Factory Semantics

The default export receives ExtensionAPI and may be async; Pi awaits it before session_start, resources_discover, and flushing queued pi.registerProvider() calls. Use async factories for one-time startup work such as dynamic model discovery. Do not start background resources (processes, sockets, watchers, timers) in the factory — factories can run in invocations that never start a session. Start them in session_start or on demand, and close them in an idempotent session_shutdown handler.

Event Lifecycle

Startup: project_trust (user/global and CLI -e extensions only) → session_start { reason: "startup" } → resources_discover { reason: "startup" }.

Prompt: extension commands checked first (they bypass input) → input → skill/template expansion → before_agent_start → agent_start → message events → per turn: turn_start, context, before_provider_headers, before_provider_request, after_provider_response, then tool_execution_start, tool_call, tool_execution_update, tool_result, tool_execution_end → turn_end → agent_end → agent_settled.

Session replacement (/new, /resume): session_before_switch (cancellable) → session_shutdown → session_start { reason: "new" | "resume", previousSessionFile } → resources_discover. /fork and /clone use session_before_fork (with position: "before" | "at") then reason: "fork". /name emits session_info_changed. Compaction: session_before_compact → session_compact. /tree: session_before_tree → session_tree. Model changes: thinking_level_select then model_select. Exit: session_shutdown.

High-Value Hooks

  • project_trust — must return { trusted: "yes" | "no" | "undecided", remember?: boolean }. First yes/no decision wins and suppresses the built-in prompt. ctx is a limited trust context (cwd, mode, hasUI, select/confirm/input/notify).

  • resources_discover — return { skillPaths, promptPaths, themePaths }.

  • before_agent_start — return { message } to inject a persistent custom message. Prefer structured prompt-section/tool updates so Pi persists transcript deltas; { systemPrompt } or forceSystemPrompt forces the leading provider prompt for this run. event.systemPromptOptions exposes the structured inputs Pi used: customPrompt, selectedTools, toolSnippets, promptGuidelines, appendSystemPrompt, cwd, contextFiles, skills.

  • context — transforms the conversation without prompt/tool system messages; Pi restores that state afterward. Use context_with_system only to own the complete request-local transcript and preserve a system message at index zero.

  • provider_stream_event — observes each parsed provider event before normalization; awaited, notification-only, not persisted.

  • turn_end / agent_before_settle — may propose custom, custom_message, context_edit, or compaction entries and request one continuation with continue: true; guard against unconditional loops.

  • before_provider_headers — mutate event.headers in place; a string adds/overrides, null deletes. Fires once per request; retries reuse the headers.

  • before_provider_request — inspect or replace event.payload; handlers run in load order and undefined keeps it unchanged. Payload-level system-instruction rewrites are not reflected by ctx.getSystemPrompt().

  • after_provider_response — event.status and normalized event.headers before the stream body is consumed.

  • tool_call — event.input is mutable and mutations affect execution (no re-validation); return { block: true, reason?, terminate? } to block. terminate applies only to a blocked call, and the agent stops early only when every finalized result in the batch is terminating. Narrow with isToolCallEventType("bash", event), or isToolCallEventType<"my_tool", MyToolInput>(...) for custom tools.

  • tool_result — middleware-style chain; return partial patches (content, details, isError, usage). Use isBashToolResult(event) for typed bash details and ctx.signal for nested async work.

  • message_end — return { message } to replace the finalized message; the replacement must keep the same role.

  • user_bash — intercept !/!!: return { operations } (optionally wrapping createLocalBashOperations()) or { result }.

  • input — sees raw text before skill/template expansion. Return { action: "continue" | "transform" | "handled" }; event.source is "interactive" | "rpc" | "extension" and event.streamingBehavior is "steer" | "followUp" | undefined.

In parallel tool mode, sibling tool calls are preflighted sequentially then executed concurrently, so tool_call is not guaranteed to see sibling tool results; tool_result/tool_execution_end may interleave in completion order while final toolResult message events stay in assistant source order.

ExtensionContext

ctx.ui (see Custom UI), ctx.mode ("tui" | "rpc" | "json" | "print"), ctx.hasUI (true in TUI and RPC), ctx.cwd, ctx.signal (agent abort signal; usually undefined outside active turns), ctx.isProjectTrusted(), ctx.sessionManager (read-only: getEntries, getBranch, buildContextEntries, getLeafId, …), ctx.modelRegistry (getProvider(id), getProviderAuth(id), find(...)), ctx.model, ctx.thinkingLevel, ctx.scopedModels, ctx.isIdle(), ctx.abort(), ctx.hasPendingMessages(), ctx.shutdown(), ctx.getContextUsage(), ctx.compact({ customInstructions, onComplete, onError }), ctx.getSystemPrompt().

ctx.scopedModels is the read-only list of models scoped to the session — the same set /scoped-models shows, resolved at session start from --models and the enabledModels setting (minimatch against provider/modelId or a bare modelId). It is empty when no scoping is configured, meaning every available model is usable. Entries are { model, thinkingLevel? }, with thinkingLevel set only when a pattern pinned it (e.g. anthropic/*:high). Use it for a model picker that mirrors the built-in one instead of enumerating ctx.modelRegistry.getAvailable().

Use the exported CONFIG_DIR_NAME instead of hardcoding .pi — rebranded distributions use a different name.

ExtensionCommandContext

Command handlers additionally get session-control methods that would deadlock from event handlers: getSystemPromptOptions(), waitForIdle(), newSession({ parentSession, setup, withSession }), fork(entryId, { position: "before" | "at", withSession }), navigateTree(targetId, { summarize, customInstructions, replaceInstructions, label }), switchSession(path, { withSession }), reload().

withSession receives a fresh ReplacedSessionContext with async sendMessage()/sendUserMessage(). It runs only after the old session emitted session_shutdown and the new instance already received session_start, but still executes in the original closure — so captured old pi/ctx/sessionManager objects are stale and throw. Capture only plain data (strings, ids) across the boundary. Treat await ctx.reload() as terminal for that handler (await ctx.reload(); return;); tools cannot call it, so expose a command and have the tool queue it with pi.sendUserMessage("/my-reload", { deliverAs: "followUp" }).

ExtensionAPI

Tools: registerTool(definition) (works during load and at runtime — new tools are callable without /reload), getActiveTools(), getAllTools() (returns name, description, parameters, promptGuidelines, sourceInfo), setActiveTools(names).

Messages and session: sendMessage(message, { deliverAs: "steer" | "followUp" | "nextTurn", triggerTurn }), sendUserMessage(content, { deliverAs, expandPromptTemplates }) (deliverAs required while streaming; expandPromptTemplates defaults to false and opts into extension-command dispatch plus skill/prompt-template expansion), appendEntry(customType, data), setSessionName, getSessionName, setLabel(entryId, label).

Commands and input: registerCommand(name, { description, handler, getArgumentCompletions }) (duplicate names get :1/:2 suffixes in load order), getCommands() (extension → prompt → skill order, each with sourceInfo.scope/origin), registerShortcut(key, options), registerFlag(name, options) + getFlag(name).

Rendering: registerMessageRenderer(customType, renderer) (custom messages, in LLM context), registerEntryRenderer(customType, renderer) (custom entries, TUI only), registerMarkdownTransformer(transformer).

registerMarkdownTransformer transforms the Markdown of normal user text, assistant text, and thinking blocks before Pi's built-in renderer runs. Transformers run in extension load order, each receiving the previous transformer's output plus a context of messageType ("user" | "assistant" | "assistant-thinking"), isStreaming (true only for partial assistant updates), and availableWidth (exact terminal columns):

pi.registerMarkdownTransformer((markdown, { messageType, isStreaming }) => {
  if (isStreaming || messageType === "assistant-thinking") return markdown;
  return markdown.replaceAll("-->", "→");
});

A throwing transformer keeps the Markdown produced so far and continues with the next one. The hook is display-only — the session and model context keep the original message. It fires for new user messages, assistant streaming updates, restored session messages, and terminal width changes, so keep transformers synchronous and cheap.

Model and provider: setModel(model) (returns false without an API key), getThinkingLevel(), setThinkingLevel(level), registerProvider(nameOrProvider, config?), unregisterProvider(name). Calls after the load phase take effect immediately. Dynamic providers can implement refreshModels, and a complete pi-ai Provider from createProvider(...) can be registered as the composition base with models.json overrides layered above.

refreshModels receives the canonical credential/stored-catalog/network/signal context: context.stored is the persisted provider snapshot, and persistence goes through generation-checked context.publish({ persist: entry }) (persist: null deletes the snapshot). Live servers such as llama.cpp can return models without persisting. context.signal is always a concrete signal and provider callbacks must pass it to blocking I/O; public ModelRuntime.refresh() / ModelRegistry.refresh() accept an optional signal and are unbounded when it is omitted, so extensions choose their own deadlines. Cancellation stops the caller waiting even if a provider ignores the signal. OAuth refreshToken(credentials, signal) now takes the signal as a second argument.

Other: exec(command, args, { signal, timeout }) → { stdout, stderr, code, killed }, on(event, handler) (returns unsubscribe), events (inter-extension bus), registerMcpServer/unregisterMcpServer/getMcpServers for native MCP. Tools can call ctx.executeTool(name, args, { signal, onUpdate }); nested calls pass normal validation/hooks and emit parentToolCallId. Pi records bounded nested-call metadata and aggregates nested usage; callers must not double-count it.

Custom Tools

pi.registerTool({
  name: "my_tool",
  label: "My Tool",
  description: "What this tool does (shown to the LLM)",
  promptSnippet: "One-line entry in the system prompt's Available tools section",
  promptGuidelines: ["Use my_tool when the user asks to summarize generated text."],
  parameters: Type.Object({ action: StringEnum(["list", "add"] as const), text: Type.Optional(Type.String()) }),
  prepareArguments(args) { return args; },
  async execute(toolCallId, params, signal, onUpdate, ctx) {
    onUpdate?.({ content: [{ type: "text", text: "Working..." }], details: { progress: 50 } });
    return { content: [{ type: "text", text: "Done" }], details: {}, terminate: true };
  },
  renderShell: "self",
  renderCall(args, theme, context) { /* Component */ },
  renderResult(result, options, theme, context) { /* Component */ },
});
  • Use StringEnum from @earendil-works/pi-ai for string enums; Type.Union/Type.Literal breaks Google's API.

  • promptGuidelines bullets are appended flat with no tool-name prefix — always name the tool ("Use my_tool when…"), never "this tool".

  • prepareArguments runs before schema validation; use it to fold legacy argument shapes from resumed sessions instead of loosening parameters.

  • Throw to fail a tool, or return isError: true when a structured failure result should remain available to script callers. With outputSchema, return matching structuredContent; ordinary model callers still receive content.

  • terminate: true hints that the follow-up LLM call should be skipped, and only applies when every finalized result in the batch terminates.

  • Return usage for nested LLM calls; Pi persists it and includes it in footer, /session, and RPC totals.

  • Strip a leading @ from path arguments (some models add it), and wrap read-modify-write windows in withFileMutationQueue(absolutePath, fn) so the tool shares the per-file queue with built-in edit/write — tools run in parallel by default. Resolve to an absolute path first; the helper canonicalizes existing files through realpath().

  • Truncate output. The built-in limit is 50 KB / 2000 lines, whichever hits first. Use truncateHead (beginning matters), truncateTail (end matters), truncateLine, formatSize, DEFAULT_MAX_BYTES, DEFAULT_MAX_LINES, and tell the LLM where the full output was saved.

Overriding built-ins (read, bash, edit, write, grep, find, ls) works by registering the same name; interactive mode warns. Renderer inheritance is per slot, so omitting renderCall/renderResult keeps the built-in UI. promptSnippet/promptGuidelines are not inherited. The result shape, including details, must match exactly.

Remote execution: built-in tool factories accept pluggable operations (ReadOperations, WriteOperations, EditOperations, BashOperations, LsOperations, GrepOperations, FindOperations). createBashTool(cwd, { spawnHook, exposeSessionEnvironment }) can rewrite command/cwd/env; session variables are injected before spawnHook (references/environment-variables.md).

Dynamic Tool Loading

Register tools first; pi.setActiveTools(names) can activate known tools and ignores unknown names. Pi persists initial prompt/tool declarations and later changes as system messages; a provider unable to represent the transition receives a checkpoint and may lose its cache prefix. Do not assume additive changes are always cache-free.

exposure controls reachability: direct (default, declared/callable while active), model-only (declared while active, never callable from another tool), codemode (callable while registered), deferred (callable but discovered instead of listed), or hidden (unreachable). There is no public tool unregister API in Pi 0.99.2; re-register hidden to withdraw a tool. namespace groups tools and annotations carry unverified MCP-style hints. prepareLoadout(loadout) can change declarations/descriptions while preserving callable tools. Prefer model-only for user interaction and orchestrator tools. See mcp.md for native MCP exposure (the default server codemode exposure deliberately uses deferred discovery).

State Management

Store state in tool result details so branching works, and rebuild it in session_start by walking ctx.sessionManager.getBranch(). pi.appendEntry(customType, data) persists extension state that does not enter LLM context.

Custom UI

Dialogs: ctx.ui.select(title, options), confirm(title, message), input(prompt, placeholder), editor(title, prefill), notify(message, "info" | "warning" | "error"). Dialogs accept { timeout } (live countdown; select/input return undefined, confirm returns false) or { signal } when you need to distinguish timeout from user cancel.

Chrome: setStatus(key, text), setWidget(key, lines | factory, { placement: "aboveEditor" | "belowEditor" }), setFooter(factory), setHeader(...), setTitle(text), setEditorText / getEditorText / pasteToEditor, setWorkingMessage, setWorkingVisible, setWorkingIndicator({ frames, intervalMs }), setToolsExpanded / getToolsExpanded, setEditorComponent(factory) / getEditorComponent(), addAutocompleteProvider(current => provider), getAllThemes / getTheme / setTheme / theme, and custom(factory, { overlay, overlayOptions, onHandle }).

Custom-component details, overlays, built-in components, and copy-paste patterns are in references/tui.md. Syntax highlighting helpers: highlightCode(code, lang, theme), getLanguageFromPath(path). Keybinding hints: keyHint(id, description), keyText(id), rawKeyHint(key, description) with namespaced ids (app.* for the coding agent, tui.* for shared TUI).

Error Handling and Mode Behavior

Extension errors are logged and the agent continues; tool_call errors block the tool (fail-safe); tool execute failures may throw or return isError: true. user_bash exceptions and invalid defined results fail closed; only undefined continues to later handlers/local execution.

Modectx.modectx.hasUINotes
Interactive"tui"trueFull TUI
RPC"rpc"trueDialogs/notifications over the JSON protocol; custom() returns undefined
JSON"json"falseUI methods are no-ops
Print (-p)"print"falseExtensions run but cannot prompt

Guard TUI-only features with ctx.mode === "tui"; guard dialogs and notifications with ctx.hasUI.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs network access, Needs an API key, Needs Node.js

The author says: Requires Node.js >= 22.19 and npm for Pi CLI and SDK usage. Pi package name is @earendil-works/pi-coding-agent.

Security

What our scanner noticed· Medium risk

  • References to credential files
  • Instructions that use the network
  • Downloads piped into a shell

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
K-Dense Inc.
Publisher
K-Dense (Community)
Source
K-Dense-AI/scientific-agent-skills · skills/pi-agent · commit a25cf9e
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE.md)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

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