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Glama

Alienvault Otx

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. Added

TDQS

A4.6/5.0
Behavior5/5

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

Beyond annotations (read-only, idempotent), the description discloses significant behavioral details: routing logic (SEC EDGAR vs grounded pipeline), verdict types, the crucial caveat that 'could_not_verify' means the check did not happen and must not be shown as evidence, and error reporting with verification_error. This is rich, actionable context.

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 well-structured, starting with examples and then covering routing, return values, and caveats. While longer than minimal, every sentence earns its place given the tool's complexity; slightly less concise than ideal but highly informative.

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?

Despite no output schema, the description explains return verdicts, grounded/structured values, citations, and error semantics. It covers edge cases (could_not_verify vs unsupported) and efficiency benefits, making it complete for invocation decisions.

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 covers 100% of parameters with descriptions. The description adds extra operational meaning, e.g., setting tolerance_pct to 1–2 for hallucination detection and noting default behavior. This goes beyond the schema's baseline.

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's purpose: natural-language claim verification against authoritative sources. It uses specific verbs like 'fact check', 'verify', and 'confirm or refute', and distinguishes itself by describing the fast path for company-financial claims and fallback for other claims, differentiating it from sibling tools like ask_pipeworx_grounded and lookup_indicator.

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 explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct' and explains routing for different claim types. It does not name alternative tools explicitly or state when not to use, but it implies it replaces sequential calls, giving strong contextual guidance.

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

A3.6/5.0
Disambiguation1/5

Several tools are nearly indistinguishable, particularly ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded, plus a cluster of overlapping Polymarket tools. The three OTX-specific tools are buried among 31 unrelated utilities, making correct selection highly error-prone.

Naming Consistency3/5

Tool names are consistently snake_case and mostly readable, but the pattern is mixed: imperative verbs like ask_, get_, lookup_, and validate_ coexist with noun-first names like entity_profile, polymarket_edges, and recent_alerts. It is not chaotic, but the style is not predictable enough for a 5.

Tool Count2/5

34 tools is excessive for a server purportedly about Alienvault OTX, with only 3 tools actually serving that domain. The bulk are unrelated data-retrieval, prediction-market, memory, and utility tools, making the set feel unfocused and overstuffed.

Completeness1/5

For a server named Alienvault OTX, the surface is severely incomplete: search_pulses, get_pulse, and lookup_indicator cover only basic threat-intel lookup. There is no coverage of OTX events, malware details, passive DNS, indicator enrichment, or OTX subscription workflows, while most of the 34 tools address entirely different domains.

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