Skip to main content
Glama

bulk_import

Import multiple AI agent skills from a directory by scanning subdirectories containing SKILL.md files. Validates, deduplicates, and optionally fills missing frontmatter, infers resources, and syncs profiles.

Instructions

Import every immediate child directory under source_dir that contains a SKILL.md. Each child is validated and deduped like propose_skill; agents fills missing agents frontmatter for migration bundles, resources can be inferred from bundled files, and profile sync runs once at the end. Returns compact sync counts by default; pass verbose: true for full per-profile sync detail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_dirYes
agentsNo
allow_synthesized_frontmatterNo
sync_profilesNo
profile_rootsNo
discover_profile_rootsNo
verboseNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses validation, dedup, agents filling, resource inference, and profile sync. However, it does not mention side effects (e.g., whether source files are modified), authentication needs, or error handling, leaving gaps.

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

Conciseness4/5

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

The description is a single paragraph with no wasted words. It front-loads the core action and adds details sequentially. Could be slightly improved with bullet points for clarity, but overall efficient.

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

Completeness3/5

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

Given the tool complexity (7 params, no output schema, no annotations), the description provides adequate but not complete context. It explains main behavior and a few parameters, but leaves many details about error handling, prerequisites, and return behavior implicit.

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?

With 0% schema description coverage, the description must compensate. It explains source_dir, agents, and verbose, adding meaningful context. However, four parameters (allow_synthesized_frontmatter, sync_profiles, profile_roots, discover_profile_roots) remain unexplained, so coverage is only partial.

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?

The description clearly states the action (import) and resource (immediate child directories containing SKILL.md). It also distinguishes behavior from sibling propose_skill by referencing it, but does not explicitly differentiate from other siblings like add_skill or update_skill.

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

Usage Guidelines2/5

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

The description does not provide explicit guidance on when to use bulk_import versus alternative tools. It mentions 'like propose_skill' but lacks any when-to-use or when-not-to-use instructions, leaving the agent without decision support.

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/autoworks-ai/autovault'

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