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Glama

Scryfall

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?

Beyond the read-only annotations, the description discloses rich behavior: routing company-financial claims via SEC EDGAR+XBRL fast path, fallback to grounded pipeline for other facts, verdict enumeration, and critical distinction between could_not_verify (internal failure, no evidence) and unsupported (no source coverage). This adds substantial value 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?

Though a single long paragraph, it is front-loaded with trigger phrases and use context. Every sentence adds new information: routing, return structure, error semantics, and efficiency benefit. Nothing is redundant or wasted.

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 no output schema, the description compensates by explaining return values (verdict list, actual value with pipeworx:// citation, reasoning) and clarifying ambiguous verdict meanings. It also explains the two-tier routing for company-financial vs. all other claims, making the tool's behavior fully understandable.

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?

Schema coverage is 100% and the schema descriptions are already detailed (e.g., tolerance_pct has 'Overrides the tolerance implied by the claim wording...'). The main description does not add further parameter semantics beyond what the schema provides, so baseline 3 is appropriate.

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 a specific verb and resource: natural-language claim verification against authoritative sources. It distinguishes itself from siblings like ask_pipeworx and deep_research by framing it as fact-checking and highlighting that it replaces multi-step sequential calls.

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?

It explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct' and provides trigger phrases. It doesn't name specific alternative tools, but it does contrast with sequential calls, so while context is clear, it lacks explicit when-not/alternative tool exclusions.

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

A3.9/5.0
Disambiguation3/5

Most tools have distinct purposes, but the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) plus deep_research creates real boundary confusion, and the six polymarket_* tools overlap enough to require careful reading. The few Scryfall card tools are clearly distinct from the Pipeworx bulk, but the name mismatch adds selection friction.

Naming Consistency4/5

All tool names use snake_case and most follow a verb_noun pattern (get_card, search_cards, resolve_entity, validate_claim). There are deviations like entity_profile, deep_research, and pipeworx_trending, but the nested families (ask_pipeworx*, polymarket_*) are internally consistent and predictable.

Tool Count2/5

35 tools is above the 25+ threshold and is especially mismatched with the server name 'Scryfall', which implies a focused MTG card server. Only 4 of 35 tools relate to Scryfall; the remaining 31 form a sprawling data-research platform that would be more appropriately split into separate servers.

Completeness4/5

The dominant Pipeworx data-research surface is remarkably complete: universal lookup, grounded answers, deep research, entity profiles, comparisons, entity resolution, claim validation, change feeds, subscriptions, memory, and discovery. The Scryfall subset covers core card lookup (search, get by name, random, list sets) but lacks rulings, set details, and card-by-ID lookups, which is a minor gap relative to the server's stated name.

Resources