Skip to main content
Glama

bear_context_import

Import external content like Jira tickets or Slack threads into a curated context library with YAML metadata for organization.

Instructions

Import external content into the context library. Content is written to the external/ directory with YAML front matter (source, group, summary, date). Use this to add non-Bear content like Jira tickets, Slack threads, API docs, or any markdown. The content is passed via stdin and a filename must be provided.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameYesTarget filename in external/ (e.g., 'jira-ticket-123.md')
contentYesMarkdown content to import
groupNoGroup label for organizing (e.g., 'jira', 'slack', 'docs')
sourceNoSource description (e.g., URL, tool name)
summaryNoShort summary of the content
Behavior4/5

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

Adds behavioral context beyond annotations: writes to external/ directory, adds YAML front matter with specific fields. Discloses input method but slight inconsistency with 'stdin' mention versus schema parameter.

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?

Four concise sentences, each adding value. Front-loaded with core purpose, then details. No wasted words.

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

Completeness4/5

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

Fairly complete for a write tool: covers purpose, location, structure, and examples. Missing return value info (no output schema) and error behavior, but sufficient for agent use.

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

Parameters4/5

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

Schema has 100% coverage, but description adds meaning by explaining how parameters (source, group, summary) become front matter fields, and that date is auto-generated. Provides context beyond schema.

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

Purpose4/5

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

Clearly states verb 'Import' and resource 'external content into the context library', with examples of what to import. However, it does not explicitly differentiate from sibling tools like bear_context_add.

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

Usage Guidelines3/5

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

Provides guidance to use for non-Bear content, but lacks when-not-to-use or alternative tool references. No explicit exclusions.

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/mreider/better-bear'

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