Skip to main content
Glama

origin_search_templates

Retrieve ranked templates from your library by specifying plot type, data shape, tags, or keywords to reuse matching plot styles before creating a new one.

Instructions

Search the user template library for templates matching an intended plot.

Ranks saved templates by plot type, data shape, tags, and keywords. Call this before plotting to reuse a matching style; each result carries a score and match_reasons. Returns an empty list when nothing matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
plot_typeNo
n_columnsNo
tagsNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description discloses ranking criteria, return structure (score, match_reasons), and empty list behavior. However, it does not address permissions, side effects (though likely none), or detailed behavior like whether it modifies state.

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?

Three sentences covering purpose, ranking, return format, and empty case. Front-loaded with key action. Slightly redundant but efficient.

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?

Given 5 optional parameters, no schema descriptions, and an output schema (not shown), the description explains return values (score, match_reasons) and emptiness. It could elaborate on how to apply the template, but the sibling tools fill that gap.

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?

Schema description coverage is 0%, so the description adds meaning by linking parameters to ranking criteria: 'plot type' (plot_type), 'data shape' (n_columns inferred), 'tags' (tags), 'keywords' (query). However, limit is not explained, and query format is not clarified.

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 the tool searches the user template library for matching templates, ranks them, and returns scores. It specifies the context ('before plotting') and distinguishes from siblings like origin_list_user_templates and origin_save_graph_template.

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 says 'Call this before plotting to reuse a matching style', providing clear usage context. However, it does not explicitly mention when not to use it or provide alternatives, which would improve guidance.

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/wxxuan2000-gif/origin-mcp-kimi'

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