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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

A5/5.0
Behavior5/5

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

Annotations already indicate read-only, open-world, idempotent, non-destructive. Description adds details about embeddings (BGE-base-en), window size (500-char), char cap (200K), and that longer inputs are truncated and flagged. 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?

Description is focused and well-organized: purpose, usage, internal details, pairing, constraints. Every sentence adds value; no wasted words.

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?

Despite no output schema, description fully explains what is returned (passages with offsets and similarity scores). Covers all input constraints and pairs with a sibling for grounding context.

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

Parameters5/5

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

Schema coverage is 100%, so baseline 3. Description adds examples for query, explains text is the document, and states limit default (5). Provides meaningful context beyond schema.

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?

Clearly states it performs semantic search inside a fetched record, returning relevant passages with offsets and scores. Distinguishes from siblings by mentioning pairing with ask_pipeworx_grounded and the use case of large records.

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?

Explicitly advises when to use: 'when the record is too big to cram into the prompt.' Also explains pairing with ask_pipeworx_grounded and notes the 200K char cap with truncation.

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
Disambiguation2/5

The tool set includes many similar Pipeworx query tools (ask_pipeworx, ask_pipeworx_grounded, ask_pipeworx_beta, deep_research) that all serve overlapping purposes, causing confusion. The Twitch-specific tools are distinct but are buried among many unrelated tools.

Naming Consistency3/5

Most tools use snake_case (e.g., get_streams, ask_pipeworx), but there is variation in patterns: some are verb_ noun (get_streams), some are just verbs (remember), and some are adjective_noun (recent_changes). No strong pattern across the whole set.

Tool Count2/5

With 35 tools, the server is bloated for its stated purpose as a 'Twitch' server. Only about 4-5 tools are Twitch-related; the rest are from a data platform (Pipeworx) and generic utilities, making the count feel excessive and unfocused.

Completeness2/5

For a Twitch server, the tool surface is severely incomplete. It lacks essential Twitch features like clips, follows, chat, or channel management. The few Twitch tools present cover only basic stream and user lookup.