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deepghs_get_repo_info

Read-onlyIdempotent

Retrieve detailed metadata for DeepGHS datasets, models, or spaces to examine file contents, sizes, tags, and download information before downloading.

Instructions

Get detailed metadata for a specific DeepGHS dataset, model, or space by repo ID.

Returns the full file tree with sizes, all tags, README card metadata, download counts, creation/modification dates, and gating status. Use this before deciding to download — the file tree shows you exactly what tar/parquet files are inside and how large they are.

Args: params (GetRepoInfoInput): - repo_id (str): Full HF repo ID (e.g. 'deepghs/danbooru2024') - repo_type (str): 'dataset', 'model', or 'space' (default: 'dataset') - response_format (ResponseFormat): 'markdown' or 'json'

Returns: str: Full repo metadata including file tree with sizes, tags, card data, and a generated cheesechaser download command if applicable.

Schema (JSON mode): { "id": str, "sha": str, "lastModified": str, "tags": list[str], "downloads": int, "likes": int, "cardData": dict, # README metadata "siblings": [ # File tree {"rfilename": str, "size": int, "blobId": str} ], "gated": bool | str }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds valuable context beyond annotations: it explains the tool's purpose for pre-download evaluation and mentions the generated download command, which enhances behavioral understanding without contradicting 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 well-structured and front-loaded with the core purpose, followed by usage guidance and parameter/return details. Every sentence adds value without redundancy, and the inclusion of a schema example is concise and informative, making it efficient for an AI agent to parse.

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's complexity (metadata retrieval with file trees), the description is complete: it covers purpose, usage, parameters, and returns, with an output schema provided. Annotations handle safety and idempotency, and the description adds practical context like the download command, making it fully adequate 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 description coverage is 0%, so the description must compensate. It provides meaningful context for parameters: repo_id is explained with an example, repo_type lists valid values, and response_format specifies options. However, it doesn't detail default values or constraints beyond what's implied, leaving some gaps compared to full schema documentation.

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's purpose with specific verbs ('Get detailed metadata') and resources ('DeepGHS dataset, model, or space'), distinguishing it from sibling tools like list_datasets or search_tags which have different scopes. It explicitly mentions what information is returned, making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('Use this before deciding to download') and distinguishes it from alternatives by highlighting its unique file tree feature. It also implies when not to use it (e.g., for listing or searching instead of getting detailed info), making usage context clear.

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

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