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Glama

exchangerate

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

A4.5/5.0
Behavior5/5

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

Annotations already indicate readOnly/openWorld/idempotent, but the description adds critical behavioral details: the two processing paths (SEC EDGAR vs grounded), the verdict enum, and the crucial distinction between could_not_verify and unsupported, including the requirement not to present could_not_verify as evidence. This far exceeds the annotation baseline.

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 ideal but every section — query patterns, usage, paths, return values, failure-mode warning — earns its place. It is front-loaded with purpose and ends with the critical caller note, maintaining a logical structure without 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?

Without an output schema, the description fully explains return values and the meaning of each verdict, especially the tricky could_not_verify case. It also covers the two routing paths and the tolerance behavior, making it self-sufficient for a complex tool.

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?

Input schema covers 100% of parameters with detailed descriptions, so the baseline is 3. The tool description does not add meaning beyond the schema; it mentions 'exact percent-delta math' but that is already implied by the tolerance_pct schema text.

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 function: 'natural-language claim verification against authoritative sources' with explicit trigger phrases. It distinguishes from siblings by noting it replaces 4–6 sequential calls and handles both financial and non-financial claims.

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,' providing clear when-to-use guidance. However, it does not name alternative tools or provide explicit when-not-to-use conditions, though the grounded pipeline description implies coverage for all factual claims.

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

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicates, while deep_research, validate_claim, and bet_research blur the same routing/grounding line. The polymarket_* family also has five tools covering edges, arbitrage, fill risk, and edge decay with significant functional overlap, making misselection likely despite very detailed descriptions.

Naming Consistency2/5

Naming mixes verb_noun tools (get_pair, compare_entities, suggest_questions) with noun-style tools (entity_profile, recent_changes, bet_research) and bare verbs (remember, recall, forget). The polymarket_ and pipeworx_ prefixes add some structure, but overall the naming is inconsistent and doesn't follow a predictable pattern.

Tool Count1/5

The server is named 'exchangerate' but exposes 33 tools, only two of which (get_pair, get_rates) relate to exchange rates. Even as a general data platform 33 tools is at the extreme high end, and for the stated server purpose the count is wildly inappropriate.

Completeness1/5

For an exchange-rate server, the surface is severely incomplete: there is no historical rate lookup, no amount conversion, no supported-currency listing, and no rate-change monitoring. The actual tool content covers a broad research platform, but that is entirely mismatched with the server name, leaving the implied exchange-rate domain almost completely uncovered.

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