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Recreation Gov

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

A4.5/5.0
Behavior5/5

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

The description discloses critical behaviors beyond the annotations, especially the distinction between 'could_not_verify' (pipeline failure) and 'unsupported' (no source coverage), and instructs callers never to treat 'could_not_verify' as evidence. This is highly valuable operational context that annotations (readOnlyHint, openWorldHint, idempotentHint) already hint at but do not fully explain. 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.

Conciseness5/5

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

The description is dense but every sentence earns its place: key usage triggers, pipeline routing, return contract, and crucial error-semantics warning. It is front-loaded with the essential purpose and usage, then details the special case. 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?

With no output schema, the description must explain the return contract, and it does: verdict enum, actual value plus citation, reasoning, and the distinct meanings of 'could_not_verify' vs 'unsupported'. It also covers the two major routing paths and the tolerance override. This is a complete and self-sufficient description for a tool with this complexity.

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?

The input schema already covers 100% of parameters with detailed descriptions, including tolerance_pct's override semantics and default behavior. The description adds some flavor about 'exact percent-delta math' but does not materially improve on the schema's parameter documentation. Baseline 3 is appropriate here.

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?

Description states a specific verb+resource: 'natural-language claim verification against authoritative sources'. It clearly distinguishes from sibling tools by framing as a one-shot fact-checking entry point and explicitly mentioning that it replaces 4–6 sequential calls, which sets it apart from lower-level lookup tools like ask_pipeworx_grounded or resolve_entity.

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?

The description gives an explicit when-to-use: 'Use whenever the agent needs to check whether something a user said is factually correct.' It also explains routing behavior for company-financial versus other claims. However, it does not explicitly name alternative tools to consider or provide a 'do not use when' exclusion, so it falls just short of a 5.

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

Many tools cluster around the same purpose: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route questions to similar data sources, and the polymarket_* family has several overlapping edge/arbitrage scanners. The four Recreation.gov tools are distinct but are buried among unrelated Pipeworx tools, making selection ambiguous.

Naming Consistency3/5

Names are all snake_case and readable, with recognizable prefix families like ask_pipeworx*, polymarket_*, and pipeworx_* plus verb_noun names like search_facilities and list_campsites. However, the conventions are mixed: bare verbs, brand prefixes, and composite names coexist, and nothing in the naming signals that this is a Recreation.gov server.

Tool Count1/5

This server is named Recreation Gov but only 4 of 35 tools relate to recreation facilities; the other 31 are a general-purpose data, research, and prediction-market platform. That is an extreme scope mismatch for the server's stated purpose.

Completeness2/5

For the Recreation.gov surface, basic search and detail retrieval exist, but key operations like campsite availability, reservations, and permits are missing. The dominant Pipeworx functionality is unrelated to Recreation.gov, so the tool set as a whole has no coherent domain coverage.

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