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ecosystem_data_source_create

Create a single DataSource configuration for the current project by specifying the source kind (e.g., github, pypi) and a display name.

Instructions

[DEPRECATED v1.6.1: 多源已否决(用户确认仅 GitHub 单源)。data_source 表已废弃。 此工具仅向后兼容保留,所有写入被忽略。 请改用 ecosystem 设置 API/UI(PUT /api/ecosystem/projects/{id}/settings)修改 settings 表。]

Create a single DataSource configuration for the current project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesDataSourceKind enum value — one of github / huggingface / npm / pypi / hackernews / producthunt / arxiv / custom.
nameYesFriendly display name shown in the dashboard.
configNoSource-specific config dict. Empty dict allowed.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Despite no annotations, the description clearly discloses that writes are ignored and the tool only exists for backward compatibility. This fully covers the behavioral traits an agent needs to know.

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

Conciseness3/5

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

The description includes a lengthy deprecation notice in both Chinese and English, which is somewhat redundant for an agent. The core purpose statement is short, but the overall structure could be more concise.

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?

For a deprecated backward-compatibility tool, the description adequately covers its usage context, behavior (ignored writes), and alternative. The presence of an output schema partially compensates for not describing return values. It is complete enough for an agent to make an informed decision.

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 100%, so the input schema already documents all three parameters. The description does not add any extra meaning or context beyond what the schema provides.

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

Purpose2/5

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

The description states 'Create a single DataSource configuration' but the deprecation notice says 'all writes are ignored', creating a contradiction about the tool's actual purpose. The agent cannot reliably determine what the tool does in practice.

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 explicitly states the tool is deprecated, advises against use, and provides a clear alternative ('Please use ecosystem setting API/UI'). This is excellent guidance for when and when not to use the tool.

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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