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Rss2json

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, open-world, and idempotent annotations, the description discloses the two-path routing (SEC EDGAR/XBRL vs. grounded pipeline), the verdict set, and critical semantics for could_not_verify vs. unsupported, explicitly warning that could_not_verify is not evidence. This provides substantial behavioral context beyond what annotations convey.

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 efficiently organized: trigger phrases and purpose upfront, then routing, return values, and caller warnings in separate paragraphs. Every sentence contributes essential information without fluff, making it concise for the tool's complexity.

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 the tool's complexity and lack of an output schema, the description thoroughly covers return values (verdict, actual value, citation, reasoning), explains the special verdicts could_not_verify and unsupported, and describes the two processing paths. This gives an agent enough information to invoke the tool and interpret results correctly.

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%, with both claim and tolerance_pct fully described in the schema, including tolerance_pct's default and override behavior. The main description adds routing context but does not materially enhance parameter-specific meaning beyond what the schema already provides, so it meets the baseline for high schema coverage.

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 and explicitly states 'natural-language claim verification against authoritative sources.' It distinguishes two processing paths (company-financial vs. other factual claims) and lists the verdict types, making the tool's scope unmistakable. This clearly separates it from sibling research or analysis 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?

It explicitly states 'Use whenever the agent needs to check whether something a user said is factually correct' and adds that it replaces 4–6 sequential calls, giving a clear preference rationale. However, it does not explicitly name alternate tools or provide when-not-to-use conditions, so it falls short of a full 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

B3.3/5.0
Disambiguation2/5

Many tools serve overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all query Pipeworx data in similar ways. Polymarket tools also heavily overlap. This leads to ambiguity for an agent trying to select the right tool.

Naming Consistency2/5

Tool names are inconsistent, mixing snake_case (ai_visibility_check), all lowercase (feed, forget), and underscore-separated verbs (ask_pipeworx_grounded, list_subscriptions). No consistent pattern is followed.

Tool Count2/5

With 32 tools, the server feels overloaded for its stated purpose of RSS-to-JSON conversion. Many tools are unrelated (e.g., prediction markets, entity profiles, memory) making the scope too broad for a focused server.

Completeness2/5

The tool set has notable gaps: only one RSS-related tool (feed), and missing basic operations like creating or updating entities. The heavy focus on Pipeworx and Polymarket leaves the core domain underserved.

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