Jeremyosih Pi Executor Pi Executor

Executor Usage

Use this skill before any execute call.

This skill exists to prevent trial-and-error inside the Executor sandbox. The runtime is a lazy proxy over Executor tools, not a normal JS object, so naive probing (Object.keys, globalThis, random namespace guesses, tools()) is misleading.

Source of truth

Before calling execute, read the execute tool definition in the current prompt/context. That definition is the session-specific source of truth.

This skill summarizes the current Executor calling model exposed by the execute tool definition in your session. Avoid baking in repository-specific file paths or local implementation details.

Mental model

Inside execute:

• Pi exposes Executor's sandbox, not arbitrary top-level JS globals.
• The tools object is a lazy proxy.
• You discover tools with helper functions first.
• You then call the real tool by its full path as nested properties:
  • tools.mcp_linear_app.list_issues({...})
  • not tools.linear(...)
  • not tools()
• Built-in helper paths are:
  • tools.search({ query, namespace?, limit? })
  • tools.describe.tool({ path })
  • tools.executor.sources.list({ query?, limit? })

Non-negotiable workflow

Follow this order inside every execute snippet unless you already know the exact tool path with high confidence.

1. Search for the tool.
2. Pick the best path from the search results.
3. Describe the tool to get compact TypeScript shapes.
4. Call the tool using the full namespace path.
5. Normalize the result before returning it when the tool returns MCP-style content blocks.

Canonical pattern

const matches = await tools.search({ query: "linear issues", limit: 5 });
const path = matches[0]?.path;
if (!path) return "No matching tools found.";

const details = await tools.describe.tool({ path });
console.log(details.inputTypeScript);
console.log(details.outputTypeScript);

const result = await tools.mcp_linear_app.list_issues({
  project: "<project-id>",
  limit: 5,
});

return result;

Result normalization pattern

Many MCP-backed tools return an MCP payload like:

{
  content: [{ type: "text", text: "{...json...}" }],
  structuredContent?: {...}
}

Prefer structuredContent when present. Otherwise, parse the first text block if it looks like JSON.

const unwrap = (value: any) => {
  if (value?.structuredContent) return value.structuredContent;

  const text = value?.content?.find?.((item: any) => item?.type === "text")?.text;
  if (typeof text !== "string") return value;

  try {
    return JSON.parse(text);
  } catch {
    return value;
  }
};

Use it like:

const raw = await tools.mcp_linear_app.list_projects({ query: "gitinspect", limit: 10 });
return unwrap(raw);

Hard rules

Required

• Always start with tools.search({ ... }) for unknown integrations.
• Always pass an object to helper tools.
• Always use the full namespace prefix when invoking the real tool.
• Use tools.describe.tool({ path }) before invoking unfamiliar tools.
• Use tools.executor.sources.list({}) when you need source inventory or namespace confirmation.
• Let execute handle inline elicitation in Pi UI sessions.

Forbidden

• Do not call tools().
• Do not probe with Object.keys(tools) or rely on globalThis for discovery.
• Do not guess namespaces from property names like tools.linear or tools.mcp.
• Do not pass string args to tools.search; pass an object.
• Do not use includeSchemas with tools.describe.tool(); that parameter is no longer accepted.
• Do not assume tool results are already plain JSON objects.
• Do not use fetch when Executor already has the integration you need.

Good search patterns

Use short intent phrases with key nouns:

• linear issues
• github pull requests
• calendar event
• slack channel messages

When you know the namespace, narrow it:

await tools.search({ namespace: "mcp_linear_app", query: "issues", limit: 10 });

Decision rule

Use Executor when the task is mostly outside the repo:

• SaaS APIs
• remote systems
• configured MCP / OpenAPI / GraphQL integrations
• auth- or approval-managed actions

Use Pi's native file tools when the task is mostly inside the repo:

• reading files
• editing code
• refactors
• local tests and builds

Interaction rule

In Pi UI sessions, let execute handle Executor interaction inline. Do not call resume unless execute explicitly cannot finish inline and gives you an execution ID to resume.

Quick recovery checklist

If an execute snippet behaves strangely, check these first:

1. Did you forget to load this skill before using execute?
2. Did you call tools.search({ ... }) instead of guessing?
3. Did you pass an object to helper tools?
4. Did you use tools.describe.tool({ path }) before calling an unfamiliar tool?
5. Did you invoke the real tool with its full namespace path?
6. Did you unwrap structuredContent / JSON text if the result looked nested?

Source: jeremyosih/pi-executor — distributed by TomeVault.