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Hdx

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

A4.7/5.0
Behavior5/5

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

Discloses technical details beyond annotations: BGE-base-en embeddings, cosine similarity, 500-char overlapping windows, 200K char cap with truncation flag. Annotations already mark as read-only/idempotent, but description adds implementation behavior.

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?

Every sentence contributes: purpose, use case, pairing advice, technical details, limits. Front-loaded with main action and use. No redundant or vague statements.

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 return format (passages, offsets, similarity scores) and edge case (truncation). Covers input, output, usage pattern, and technical constraints completely.

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 has 100% coverage with descriptions. Description adds value with examples for query field and clarifies limits in prose (1-20, default 5). This goes beyond schema but schema already good, so slight added value.

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 the tool performs semantic search inside a fetched record, with specific examples (SEC 10-K, article) and output details (passages, offsets, scores). Differentiates from sibling tools by mentioning pairing with ask_pipeworx_grounded.

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?

Explicitly says to use when the record is too large for the prompt and suggests pairing with ask_pipeworx_grounded. Provides clear context for when it's beneficial, though no explicit when-not cases.

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

A3.8/5.0
Disambiguation2/5

Multiple tools have overlapping purposes (e.g., three variants of ask_pipeworx, several polymarket tools, and multiple discovery/entity tools). Despite detailed descriptions, the similiar functionalities create confusion for an agent selecting among them.

Naming Consistency3/5

Tool names are consistently in snake_case but the verb/noun pattern is mixed: some start with verbs (ask_, list_, remember_), others with nouns (entity_profile, polymarket_edges). This inconsistency reduces predictability.

Tool Count2/5

35 tools is high for a single server, especially when the scope spans two disparate domains (HDX humanitarian data and Pipeworx data platform). Many tools could be logically split into separate, more focused servers.

Completeness3/5

The tool set covers a wide range of functionality (data retrieval, comparison, monitoring, memory) but has notable gaps: no direct data download tool for HDX resources, no account management, and no exploration of Pipeworx packs beyond discover_tools.

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