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goosefly99

profile-project

by goosefly99

pp_vectorstore_check

Diagnose vectorstore reachability and embedding dimension via read-only probes for Ollama and Pinecone. Detects conflicts without writing or creating any store.

Instructions

Diagnose vectorstore reachability + dimension (read-only; never writes).

This tool is inherently a dry-run diagnostic: it NEVER constructs the store client and NEVER writes to disk. It runs the §6.5 conflict matrix with two bounded, fail-closed live probes wired in:

  • C3 (ollama unreachable): a GET to the configured ollama base_url within embed_timeout_seconds; any error/timeout warns + disables.

  • C4 (Pinecone dimension): a describe_index lookup compared against the effective embedding dimension; a mismatch or any probe failure warns + disables (no index is ever created).

reachable reflects whether the vectorstore survives the conflict matrix (with the above probes folded in): chromadb-local is always reachable; remote/probe-gated backends are reachable only when no disabling conflict fired. dimension is the embedder's effective dimension when it can be built, else None.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully discloses behavior: read-only, no writes, two live probes (C3 and C4), conflict matrix usage, and effect on reachable/dimension outputs. It is highly transparent.

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 front-loaded with a concise summary, then details probes, and finally defines outputs. Every sentence serves a purpose without redundancy.

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 zero parameters and an existing output schema (implied), the description thoroughly explains all behavioral aspects, probe details, and output meaning, making it complete.

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?

The tool has zero parameters, and schema coverage is 100%. The description adds value by explaining the output fields, which is beyond the minimum baseline of 3, hence 4.

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 diagnoses vectorstore reachability and dimension, and explicitly notes it is read-only. This distinguishes it from other sibling tools like pp_index_status or pp_query.

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 explains the tool is a dry-run diagnostic and never writes, providing clear context. However, it does not explicitly exclude alternative tools or state when not to use it.

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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