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Glama

Aviationstack

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / tolerance_pct
      Added value: +{
+  "description": "Max 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.",
+  "type": "number"
+}
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already indicate read-only, open-world, idempotent, non-destructive. The description goes well beyond by defining the special semantics of could_not_verify (not evidence, carries verification_error{stage,detail}) and unsupported, plus the routing behavior and citation/reasoning return fields. No contradiction.

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 longer than average but every sentence adds value: examples, usage rule, pipeline routing, return value semantics, and an IMPORTANT caller warning. It is front-loaded and well-structured, with no redundant filler.

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 there is no output schema, the description compensates well by enumerating the six verdicts, the citation+reasoning payload, the verification_error subfield, and the difference between could_not_verify and unsupported. It also covers both financial and non-financial paths, making the tool operative for an agent.

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?

Both parameters have detailed schema descriptions (100% coverage), and the tool description doesn't add further parameter-specific details beyond the schema. It does mention 'exact percent-delta math' which relates to tolerance, but that's marginal; baseline 3 applies.

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 opens with natural-language triggers and states 'natural-language claim verification against authoritative sources,' clearly distinguishing it as a fact-check tool. It also splits financial vs non-financial pipelines, further specifying the tool's unique role among sibling research/query tools.

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?

Explicitly instructs 'Use whenever the agent needs to check whether something a user said is factually correct.' It describes the financial fast path vs grounded fallback but does not name alternative siblings or give when-not-to-use exclusions, so 4.

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 have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, and deep_research all routing queries, and the polymarket family (arbitrage, edges, edge_tracker, fill_risk) covering similar ground. While descriptions are detailed, an agent could easily select the wrong tool.

Naming Consistency2/5

Tool names mix bare nouns (airlines, airports, flights) with verb phrases (compare_entities, resolve_entity) and standalone verbs (remember, forget), with no consistent verb_noun pattern. Names like ask_pipeworx_beta and scan_competitor_ai_presence are internally inconsistent with the rest.

Tool Count2/5

37 tools is far beyond the typical scope for a single server, and many are unrelated to the aviation theme, suggesting a lack of focus. The core aviation functionality only accounts for 6 of the tools.

Completeness3/5

The aviation tools (airlines, airports, flights, routes, cities, countries) cover basic lookups, but advanced operations like delay statistics or aircraft data are absent. The unrelated tools do not fill these gaps, and the overall surface feels shallow for a server claiming to be an Aviationstack.

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