Skip to main content
Glama

bundle_import

Import a task bundle into an agentpack pack. By default, returns a read-only import plan so you can inspect untrusted bundles; set write to true to apply the import.

Instructions

Import a task bundle into this pack. By default it only returns the read-only import plan; nothing is written unless write is true. A write import runs under a pack lock, creates a parked task with local verification reset to unknown, retains the bundle and an import manifest, and never changes the current-task pointer. Inspect or plan untrusted bundles first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonNoReturn structured JSON instead of formatted text.
pathYesPath to the bundle JSON file to import.
asNewNoResolve a task-id collision by importing under a deterministic new id.
writeNoApply the import. When false or omitted, only the read-only plan is returned.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes far beyond the annotations by detailing that the default is a read-only plan, a write import runs under pack lock, creates a parked task, resets verification to unknown, retains bundle and manifest, and never changes the current-task pointer. This is rich behavioral context not captured in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four well-structured sentences, front-loaded with the purpose, followed by default behavior, write side effects, and a safety note. Every sentence earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no output schema, the description adequately explains the return (read-only plan) and fully discloses the side-effect profile of write mode. It also includes safety guidance, making it complete for agent decision-making.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers all four parameters with clear descriptions, including the write param. The description reinforces the write behavior but does not add new parameter-level meaning beyond what the schema provides, so a baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Import a task bundle into this pack' with a specific verb and resource, and distinguishes itself from siblings by explaining the default read-only plan mode and the write behavior, making it distinct from bundle_inspect and bundle_import_plan.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises to 'Inspect or plan untrusted bundles first', pointing to alternatives for inspection/planning. It also clarifies when to use write=true for actual import, providing clear context on usage, though it does not name sibling tools directly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ihorponom/agentpack'

If you have feedback or need assistance with the MCP directory API, please join our Discord server