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Glama

Spdx License

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

A4.7/5.0
Behavior5/5

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

Annotations already mark it readOnly/openWorld/idempotent, and the description adds high-value behavior: the distinction between could_not_verify (check didn't happen, not evidence) and unsupported, the pipeworx:// citation, and the automatic fall-through from SEC EDGAR/XBRL to the grounded pipeline. 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?

Despite length, the description is front-loaded with trigger phrases and each clause earns its place: routing, verdict semantics, error meaning, and call-replacement value. The 'IMPORTANT for callers' clause is essential because it prevents misreading could_not_verify as evidence.

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 fully covers the return contract: verdict options, grounded/structured actual value with citation, reasoning, and the error payload distinction. It gives enough context for an agent to invoke and interpret results without additional lookup.

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 coverage is 100%, so baseline is 3; the description adds useful context by clarifying the claim type scope ('Company-financial claims… verifies via SEC EDGAR + XBRL fast path') and 'exact percent-delta math,' which interact with tolerance_pct. The schema already carries tolerance semantics, so the description's incremental parameter meaning is good but not exhaustive.

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 concrete trigger phrases ('Is it true that…', 'fact check') and states a specific verb-resource pair: 'natural-language claim verification against authoritative sources.' It also distinguishes itself from siblings by claiming to replace 4–6 sequential pipelined calls and by routing company-financial versus other 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 gives an explicit when-to-use: 'Use whenever the agent needs to check whether something a user said is factually correct,' and internally routes claim types. However, it does not name alternative sibling tools or state clear when-not-to-use exclusions, so it stops short of the fully explicit 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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as multiple 'ask_pipeworx' variants, several company analysis tools, and multiple prediction market tools. The set is large and not well-disambiguated, leading to potential confusion.

Naming Consistency2/5

Naming conventions are mixed, with snake_case ('get_license'), camelCase ('ai_visibility_check'), and prefix-based ('pipeworx_*', 'polymarket_*'). No consistent pattern across the tool set.

Tool Count2/5

35 tools is excessive for a server named 'Spdx License', which implies a focused license management tool. The actual number is more appropriate for a general data platform, but mismatched with the server name.

Completeness1/5

For the implied SPDX license domain, only a few basic tools exist (list, get, search). Missing crucial features like create, update, delete, or compare licenses. The surface is severely incomplete for the stated purpose.

Resources