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timps_local_rag_builder

Build a fully-local RAG pipeline from a corpus description, emitting ingest, retrieve, generate, evaluate scripts, Dockerfile, and Makefile.

Instructions

Build a fully-local RAG pipeline (Ollama embeddings + Chroma/FAISS + reranker + chat) from a corpus description. Emits ingest, retrieve, generate, evaluate, Dockerfile, Makefile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestNoPlain-English task or context for the agent.
languageNoPrimary programming language (default: python).python
Behavior3/5

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

No annotations are provided, so the description must carry the transparency burden. It does disclose key behavioral output ('Emits ingest, retrieve, generate, evaluate, Dockerfile, Makefile'), but it omits side effects, prerequisites (e.g., Ollama installed), whether files are overwritten, or whether network access is needed.

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 a single dense, front-loaded sentence with no wasted words. It communicates the core action, technical stack, input source, and output artifacts efficiently.

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?

For a scaffold-generation tool with only two simple parameters, the description covers the main purpose and outputs reasonably well. However, with no annotations or output schema, it lacks behavioral caveats and prerequisites, leaving some uncertainty about execution context and side effects.

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% for both parameters, so the baseline is 3. The description adds minor context by suggesting 'request' should contain a corpus description, but it does not elaborate on the 'language' parameter beyond what the schema already provides.

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 uses a specific verb ('Build') with a clear resource ('fully-local RAG pipeline') and names concrete components (Ollama embeddings, Chroma/FAISS, reranker, chat) plus generated artifacts. This makes the tool's function unambiguous and differentiates it from sibling RAG-related tools like timps_rag_designer or timps_vector_db_agent.

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

Usage Guidelines3/5

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

The phrase 'from a corpus description' implies the intended use case, and 'fully-local' hints at a specific scenario. However, there is no explicit guidance on when to prefer this tool over alternatives, no exclusions, and no mention of when it should not be used.

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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