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Uk Contracts

by io.github.pipeworx-io

Ask Pipeworx — Grounded

ask_pipeworx_grounded
Read-onlyIdempotent

Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 5,743 across 1500 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for question.
textNoAlias for question.
inputNoAlias for question.
queryNoAlias for question.
promptNoAlias for question.
questionYesYour question in natural language. Accepts query, q, prompt, text, input as aliases.

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the readOnly/openWorld/idempotent annotations by describing exact success and refusal response shapes, named refusal reasons, the guarantee to use only tool-result content, and the additional LLM-call cost. No contradiction with annotations.

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 dense but front-loaded: core purpose first, then return contract, then usage policy and cost tradeoff. Every sentence contributes useful decision-making information, though the length is near the upper bound of what is needed.

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?

With no output schema present, the description fully specifies both success and refusal return shapes, enumerates refusal reasons, explains when to prefer this tool over ask_pipeworx, and notes the extra cost. An agent has enough context to select and invoke it 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 the schema already fully documents the single question parameter and its aliases. The description adds no new parameter-level meaning beyond characterizing the tool as question-driven, which is the expected baseline for full schema coverage.

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?

Describes a specific behavior: a hallucination-resistant answer mode that extracts answers only from tool results and emits structured success/refusal responses. It is clearly differentiated from its sibling ask_pipeworx by the grounded-extraction and refusal semantics.

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 states when to use this tool — when answers will be quoted, cited, or acted on and facts must not be invented — and explicitly directs casual lookups to ask_pipeworx. It also discloses the cost tradeoff of one extra LLM call.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Uk Contracts toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Several tools occupy nearly identical roles (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools), and ask_pipeworx_beta is explicitly the same router as ask_pipeworx. Company-data tools (entity_profile, compare_entities, recent_changes, validate_claim) and the Polymarket family also overlap heavily, making selection error-prone despite detailed descriptions.

Naming Consistency5/5

Tool names are consistently lowercase snake_case with a verb_noun pattern (search_notices, get_notice, find_a_tender_recent, validate_claim). Even longer names like polymarket_edge_tracker and ask_pipeworx_grounded follow a predictable style with no camelCase or mixed conventions.

Tool Count2/5

36 tools is already excessive for a focused server, and the 'Uk Contracts' name covers only five of them (search_notices, recent_notices, get_notice, find_a_tender_recent, find_a_tender_notice). The remaining 31 are unrelated Pipeworx/Polymarket/AI-marketing utilities, so the count badly mismatches the apparent scope.

Completeness4/5

For UK public procurement, the five relevant tools provide search, recent listing, and full-detail retrieval for both Contracts Finder and Find a Tender Service, covering the core workflows well. Minor gaps include no tender-specific alert/subscription support and no server-side keyword search for the high-value FTS feed.

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