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Uk Parliament

by io.github.pipeworx-io

Validate Claim

validate_claim
Read-onlyIdempotent

"Is it true that…" / "fact check" / "verify the claim that…" / "did X really…" / "was Y actually…" / "confirm or refute" / "true or false" — natural-language claim verification against authoritative sources. Use whenever the agent needs to check whether something a user said is factually correct. Company-financial claims (revenue, net income, cash for public US companies) verify via the structured SEC EDGAR + XBRL fast path with exact percent-delta math; ANY OTHER factual claim (macro statistics, rates, prices, drug data, records) automatically falls through to the grounded pipeline — routed to the right live source, answered with verbatim evidence, then judged. Returns a verdict (confirmed / approximately_correct / refuted / inconclusive / unsupported / could_not_verify), the grounded or structured actual value with pipeworx:// citation, and reasoning. IMPORTANT for callers: could_not_verify means the check did not happen (our LLM or source failed) and carries verification_error{stage,detail} — it is NOT evidence for or against the claim, and must not be shown as one. unsupported means we looked and cover no source for it. Replaces 4–6 sequential calls (NL parsing → entity resolution → data lookup → comparison).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYesNatural-language factual claim, e.g., "Apple's FY2024 revenue was $400 billion" or "Microsoft made about $100B in profit last year".
tolerance_pctNoMax percent deviation still graded approximately_correct (0.5–50). Overrides the tolerance implied by the claim wording — set 1–2 for hallucination detection where any material error must be refuted. Default: implied by wording, capped at 5.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations declare read-only, open-world, idempotent, and non-destructive. The description goes beyond this by disclosing internal routing (SEC vs grounded), the meaning of each verdict, the presence of verification_error on could_not_verify, and the explicit warning that could_not_verify is not evidence. This adds significant behavioral context beyond annotations.

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 long but every sentence contributes unique value: trigger phrases, usage directives, routing behavior, output contract, and caveats. It is front-loaded with user intent examples and uses colons/dashes to organize dense information efficiently. No filler or redundancy.

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?

The description covers purpose, usage, behavior, output format (verdicts, actual value, citation, reasoning), and error semantics (could_not_verify with verification_error). Since there is no output schema, the description successfully carries the burden of explaining return values, making it highly complete for a tool of this complexity.

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 coverage is 100% and includes detailed parameter descriptions, so baseline is 3. The description adds value by explaining 'exact percent-delta math' for financial claims and how tolerance grading works, which enriches the meaning of tolerance_pct and claim without repeating the 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?

The description clearly identifies the tool as a claim verifier with specific verbs ('verify', 'fact check') and a resource ('natural-language claim verification against authoritative sources'). It distinguishes itself from siblings like ask_pipeworx by focusing on claims and offering a structured fast path for company financials, plus a grounded pipeline for other facts.

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 provides explicit when-to-use guidance ('Use whenever the agent needs to check whether something a user said is factually correct') and the two paths (SEC vs grounded) based on claim type. It also gives important caller guidance on how to interpret could_not_verify vs unsupported, which is essential for safe usage.

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

B3.4/5.0
Disambiguation2/5

Several tools are near-duplicates (ask_pipeworx and ask_pipeworx_beta are currently identical; ai_visibility_check vs scan_competitor_ai_presence overlap), and the massive mix of unrelated domains (Polymarket betting, general data lookup, AI visibility) alongside UK Parliament tools makes selection confusing. An agent would struggle to know whether to use ask_pipeworx, ask_pipeworx_beta, or ask_pipeworx_grounded, or which of the five polymarket tools fits.

Naming Consistency3/5

Most tools use snake_case with readable names, but the action placement varies (verb_noun like get_bill vs noun_verb like bet_research, entity_profile), and there are compound names like generate_llms_txt and scan_competitor_ai_presence. The style is mostly consistent but the verb_noun pattern is not uniform across the set.

Tool Count2/5

38 tools is heavy, and the overwhelming majority are unrelated to the server's stated UK Parliament purpose. Only 7 tools (get_bill, search_bills, bill_stages, get_member, search_members, search_hansard, recent_divisions) have anything to do with Parliament, making the count wildly inappropriate for the apparent scope.

Completeness2/5

The Parliament-specific surface is thin: basic bill/member/Hansard lookups exist, but there are no tools for specific divisions/votes, committees, publications, or detailed procedural information. The vast non-Parliament tooling is irrelevant, creating a dead end for any real Parliament research beyond the basics.

Resources