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Legislation Uk

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?

The description discloses the embedding model (BGE-base-en), windowing (500-char overlapping windows), character offset and similarity score in results, and a 200K char limit (with truncation and flagging). These details go well beyond the annotations (readOnly, idempotent, openWorld, non-destructive), fully informing the agent of the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose and usage. It contains some technical details that are valuable but could be slightly more concise. Still, it is efficient and every sentence contributes.

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 the absence of an output schema, the description thoroughly explains the return value (top-N passages with offsets and similarity scores), constraints (200K char cap, truncation flag), and internal mechanics. This is complete for an agent to select and invoke the tool correctly.

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 coverage is 100%, so baseline is 3. The tool description does not add significant new meaning beyond the schema's parameter descriptions (e.g., it reiterates the max char limit for text). The natural-language query example is helpful but not essential. No score above baseline warranted.

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 performs semantic search inside a fetched record. It uses specific verbs ('search', 'pass', 'get back'), specifies the resource ('a fetched record'), and distinguishes from siblings by mentioning that it saves context compared to cramming the full record into the prompt, and explicitly pairs 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 Guidelines5/5

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

The description explicitly states when to use: 'Use when the record is too big to cram into the prompt.' It explains the benefit ('saves context, returns only the passages that matter') and provides a pairing strategy with another tool. This gives clear guidance on when and how 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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TDQS

A3.8/5.0
Disambiguation2/5

The legislation-specific tools are distinct, but the server bundles dozens of unrelated Pipeworx/prediction-market/AI-visibility tools, making the set's purpose unclear. Several near-identical pairs exist: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and ai_visibility_check overlaps heavily with scan_competitor_ai_presence. An agent would struggle to know which tool is the right entry point.

Naming Consistency2/5

Naming is mixed: snake_case dominates, but camelCase appears in ask_pipeworx, ask_pipeworx_grounded, generate_llms_txt, and pipeworx_feedback. There is also inconsistency in verb style — get_/search_/list_ coexist with bare verbs like remember, recall, forget, and subscribe. The legislation tools themselves follow a clean get_legislation* pattern, but the wider set does not.

Tool Count2/5

35 tools is too many for a server named 'Legislation Uk' where only 4 tools actually relate to UK legislation. The remaining 31 tools appear to belong to a broader data/prediction-market platform, which suggests severe scope creep or a mislabeled assembly. This bloats the surface area and makes the server harder for an agent to navigate.

Completeness4/5

For the stated UK-legislation purpose, the core read-and-search workflow is covered: search_legislation, get_legislation, get_legislation_section, and get_legislation_text together support discovery, metadata, targeted section lookup, and full-text retrieval with version selection. Obvious gaps remain, such as full-text content search and amendment/change history, but agents can complete the primary task of finding and reading legislation. The unrelated tools neither help nor complete this domain.

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