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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 already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, but the description adds crucial behavioral context: it defines 'could_not_verify' as a failed check with verification_error, explicitly says it is NOT evidence, and distinguishes 'unsupported' from 'could_not_verify'. It also reveals the two internal routes (SEC EDGAR/XBRL vs. grounded pipeline), which goes beyond the 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 densely packed with useful information: trigger phrases, routing rules, return types, and critical caller warnings. It front-loads the core purpose with concrete examples, and every sentence contributes. The structure leads from usage to mechanics to caveats, making it easy to parse.

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, the description fully documents return values (six verdicts, actual value with citation, reasoning), explains error handling, and clarifies edge cases (could_not_verify vs. unsupported). It also describes the end-to-end pipeline and why it's efficient (replaces 4–6 calls). Nothing critical is missing for a caller.

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?

The schema already provides full descriptions and examples for both parameters (100% coverage). The description adds value by explaining the strategic use of tolerance_pct (e.g., 'set 1–2 for hallucination detection') and clarifies the default/cap behavior. It does not repeat the schema verbatim but enriches the semantics.

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 natural-language claim verification, with concrete trigger phrases like 'is it true that' and 'fact check'. It specifies the resource (authoritative sources) and the outcome (verdict + evidence), and distinguishes it from other tools by describing the fast path and grounded pipeline. This goes well beyond a mere verb+resource pairing.

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?

Explicit guidance is given: 'Use whenever the agent needs to check whether something a user said is factually correct.' It also explains when the fast path applies (company-financial claims) versus the automatic fallback (any other claim), and notes that it replaces multiple sequential calls. This is clear, actionable, and differentiates from sibling tools.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all serve similar query routing). Tools from unrelated domains (UK Gazette, Polymarket betting, AI visibility checks) are mixed together, making it hard for an agent to distinguish which tool to use for a given task.

Naming Consistency1/5

Naming is chaotic: some tools use descriptive phrases with underscores (gazette_deceased_estates, polymarket_arbitrage), others use generic verbs (remember, recall, forget), and some include version or mode indicators (ask_pipeworx_beta, scan_competitor_ai_presence). No consistent pattern across the set.

Tool Count2/5

With 36 tools, the server is overstuffed for its purported focus on the UK Gazette. The majority of tools (Polymarket, Pipeworx general, AI visibility, etc.) are unrelated to the server's name, making it feel like a bundling of many services into one, which is excessive for a coherent tool set.

Completeness2/5

For a server named 'Uk Gazette', there are only a handful of Gazette-specific tools (gazette_search_notices, gazette_insolvency_notices, etc.), while the rest cover unrelated domains. This leaves obvious gaps for Gazette-related tasks (e.g., no tool for searching particular notice types or filtering by edition), despite the large tool count.