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Odoo

by io.github.pipeworx-io

Search Within a Source

search_within
Read-onlyIdempotent

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe document text to search inside (max ~200K chars).
limitNoMax passages to return (1-20, default 5).
queryYesNatural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already indicate read-only, open-world, idempotent, and non-destructive behavior. The description adds valuable technical details: BGE-base-en embeddings, cosine similarity, 500-char overlapping windows, 200K char cap with truncation flagging, and character offsets in results. No contradictions.

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 paragraph that efficiently front-loads the main purpose, then covers usage context, technical details, and pairing advice. Every sentence is necessary and no redundancy.

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?

Without an output schema, the description adequately outlines return content (top-N passages, offsets, similarity scores) and explains truncation behavior. It also addresses pairing with a sibling tool. Minor omission: no mention of error handling or pagination, but these are not critical for a search tool.

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 covers all 3 parameters with descriptions (100% coverage). The description adds extra value by providing example queries for the query parameter, stating the default for limit, and clarifying the 200K char constraint for text. Baseline is 3; the additional context justifies a 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 it performs semantic search inside a fetched record, provides concrete examples (SEC 10-K, article), and distinguishes itself from the sibling tool ask_pipeworx_grounded by explaining how they pair together.

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 explicitly advises use when the record is too large for the prompt and explains the benefits. It also suggests pairing with ask_pipeworx_grounded. While it doesn't list explicit when-not-to-use scenarios, the condition is clearly implied.

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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TDQS

A3.7/5.0
Disambiguation3/5

Some tools have overlapping purposes (e.g., ask_pipeworx and ask_pipeworx_grounded; multiple Polymarket analysis tools) but descriptions help differentiate. Odoo-specific tools are distinct among themselves but muddled with many general-purpose tools.

Naming Consistency2/5

Naming is heavily inconsistent: Odoo tools follow 'odoo_list_*' pattern while others use varied structures like verb-first (forget, remember) or noun-first (entity_profile, recent_alerts). No unified verb_noun pattern across the set.

Tool Count3/5

At 32 tools, the server exceeds the typical well-scoped range (3–15) but is not excessively large. Many tools are generic and could be trimmed, making the set feel heavier than necessary.

Completeness2/5

Despite many tools, the server lacks essential CRUD operations for Odoo (e.g., create/update/delete leads) and the 'Odoo' name misrepresents the actual focus. Gaps in Odoo functionality and mixed domains create a sense of incompleteness.

Resources