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rag_generate_pipeline

Generate a RAG retrieval pipeline from a project directory to enable knowledge retrieval and AI-powered answers over your codebase.

Instructions

Generate RAG retrieval pipeline

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
directoryYesProject directory
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavior and side effects. It does not state whether files are created, whether the directory must already contain source code, whether api_key is consumed at generation time, or whether any existing files are modified. 'Generate' implies scaffolding but leaves the side-effect profile undisclosed.

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 is a single, front-loaded sentence with no wasted words, which is structurally clean. However, it is so terse that it omits essential context, making the brevity feel like under-specification rather than effective conciseness.

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

Completeness2/5

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

For a generation tool with no output schema and no annotations, the description should explain what is produced, where it is written, and what inputs are required. It only names the deliverable and a required directory, leaving the agent without enough context to call the tool correctly or anticipate results.

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

Parameters2/5

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

Schema description coverage is only 50%; directory is documented as 'Project directory', but api_key has no description. The tool description does not explain the role of api_key or how directory is used in the RAG pipeline generation, so it fails to compensate for the schema gap.

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 uses a specific verb ('Generate') and a specific deliverable ('RAG retrieval pipeline'), which distinguishes it from related siblings like rag_add_chunking and rag_optimize_retrieval. However, it lacks any detail about what the pipeline includes or how it relates to those siblings, so it falls short of a 5.

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?

No guidance is given for when to use this tool versus alternatives such as rag_add_chunking or rag_optimize_retrieval. There are also no prerequisites, expected directory state, or exclusions mentioned, so an agent must infer the appropriate invocation context.

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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