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
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/k-dense-ai/pi-agent/downloadUnzip 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 intent | Read |
|---|---|
| What Pi is, docs map, install methods | references/overview.md |
| Install, authenticate, first run | references/quickstart.md |
| Day-to-day CLI usage, commands, modes, flags, project trust | references/usage.md |
| Provider auth, API keys, cloud provider setup | references/providers.md |
| Custom model entries, local models, proxies, compat flags | references/models.md |
Local llama.cpp router, /llama, model download/load | references/llama-cpp.md |
| Settings keys and defaults | references/settings.md |
PI_* and other environment variables | references/environment-variables.md |
| Extension development, custom tools, events, commands | references/extensions.md |
| Custom provider implementation, OAuth, custom streaming | references/custom-provider.md |
| Embed Pi in Node/TypeScript | references/sdk.md |
| Integrate from another process/language | references/rpc.md |
| Consume JSONL event output | references/json.md |
| Build terminal UI components | references/tui.md |
| Package extensions/skills/prompts/themes | references/packages.md |
| Delegate to subagents, chains, parallel runs, orchestration | references/pi-subagents.md |
| Connect MCP servers, codemode, MCP tool discovery/config | references/mcp.md (built-in), references/pi-mcp-adapter.md (optional adapter) |
| Interactive interview forms, structured user input | references/pi-interview.md |
| Web search, URL/PDF/repo fetching, video understanding | references/pi-web-access.md |
| Author Pi skills | references/skills.md |
| Prompt templates or themes | references/prompt-templates.md, references/themes.md |
| Sessions, branching, compaction, parsing JSONL | references/sessions.md, references/compaction.md, references/session-format.md |
| Security, sandboxing, trust | references/security.md, references/containerization.md |
| Keyboard or terminal issues | references/keybindings.md, references/terminal-setup.md, references/tmux.md, references/windows.md, references/termux.md, references/shell-aliases.md |
| Working on Pi itself | references/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 --allSource 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
- ATTRIBUTION.mdAdded by AutoGineer910 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md8.1 KiB
- references/compaction.md5.7 KiB
- references/containerization.md3.8 KiB
- references/custom-provider.md9.0 KiB
- references/development.md1.9 KiB
- references/environment-variables.md4.0 KiB
- references/extensions.md19.7 KiB
- references/json.md3.6 KiB
- references/keybindings.md5.6 KiB
- references/llama-cpp.md3.4 KiB
- references/mcp.md5.9 KiB
- references/models.md9.4 KiB
- references/overview.md2.1 KiB
- references/packages.md6.2 KiB
- references/pi-interview.md7.9 KiB
- references/pi-mcp-adapter.md23.9 KiB
- references/pi-subagents.md44.8 KiB
- references/pi-web-access.md15.0 KiB
- references/prompt-templates.md1.8 KiB
- references/providers.md9.1 KiB
- references/quickstart.md2.7 KiB
- references/rpc.md9.4 KiB
- references/sdk.md13.1 KiB
- references/security.md4.7 KiB
- references/session-format.md6.1 KiB
- references/sessions.md3.0 KiB
- references/settings.md8.4 KiB
- references/shell-aliases.md772 B
- references/skills.md4.1 KiB
- references/terminal-setup.md4.3 KiB
- references/termux.md1.3 KiB
- references/themes.md2.2 KiB
- references/tmux.md1.7 KiB
- references/tui.md7.7 KiB
- references/usage.md8.6 KiB
- references/windows.md1.1 KiB
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/*.tsand~/.pi/agent/extensions/*/index.ts(global).pi/extensions/*.tsand.pi/extensions/*/index.ts(project-local, loaded only after project trust)Paths from
settings.jsonextensions/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.ctxis 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 }orforceSystemPromptforces the leading provider prompt for this run.event.systemPromptOptionsexposes 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. Usecontext_with_systemonly 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 proposecustom,custom_message,context_edit, orcompactionentries and request one continuation withcontinue: true; guard against unconditional loops.before_provider_headers— mutateevent.headersin place; a string adds/overrides,nulldeletes. Fires once per request; retries reuse the headers.before_provider_request— inspect or replaceevent.payload; handlers run in load order andundefinedkeeps it unchanged. Payload-level system-instruction rewrites are not reflected byctx.getSystemPrompt().after_provider_response—event.statusand normalizedevent.headersbefore the stream body is consumed.tool_call—event.inputis mutable and mutations affect execution (no re-validation); return{ block: true, reason?, terminate? }to block.terminateapplies only to a blocked call, and the agent stops early only when every finalized result in the batch is terminating. Narrow withisToolCallEventType("bash", event), orisToolCallEventType<"my_tool", MyToolInput>(...)for custom tools.tool_result— middleware-style chain; return partial patches (content,details,isError,usage). UseisBashToolResult(event)for typed bash details andctx.signalfor nested async work.message_end— return{ message }to replace the finalized message; the replacement must keep the samerole.user_bash— intercept!/!!: return{ operations }(optionally wrappingcreateLocalBashOperations()) or{ result }.input— sees raw text before skill/template expansion. Return{ action: "continue" | "transform" | "handled" };event.sourceis"interactive" | "rpc" | "extension"andevent.streamingBehavioris"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
StringEnumfrom@earendil-works/pi-aifor string enums;Type.Union/Type.Literalbreaks Google's API.promptGuidelinesbullets are appended flat with no tool-name prefix — always name the tool ("Use my_tool when…"), never "this tool".prepareArgumentsruns before schema validation; use it to fold legacy argument shapes from resumed sessions instead of looseningparameters.Throw to fail a tool, or return
isError: truewhen a structured failure result should remain available to script callers. WithoutputSchema, return matchingstructuredContent; ordinary model callers still receivecontent.terminate: truehints that the follow-up LLM call should be skipped, and only applies when every finalized result in the batch terminates.Return
usagefor 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 inwithFileMutationQueue(absolutePath, fn)so the tool shares the per-file queue with built-inedit/write— tools run in parallel by default. Resolve to an absolute path first; the helper canonicalizes existing files throughrealpath().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.
| Mode | ctx.mode | ctx.hasUI | Notes |
|---|---|---|---|
| Interactive | "tui" | true | Full TUI |
| RPC | "rpc" | true | Dialogs/notifications over the JSON protocol; custom() returns undefined |
| JSON | "json" | false | UI methods are no-ops |
Print (-p) | "print" | false | Extensions 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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