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by io.github.PugarHuda
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News Verify

news_verify
Read-only

Verify a crypto news claim: count independent domains reporting it (four outlets' RSS headlines plus Tavily or Venice web search), count those whose headline leans the opposite way, and attach the token's RYO analyze_token evidence so the story and the market read sit side by side.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYesThe story to verify, in one sentence
symbolNoToken symbol to attach market evidence for
max_resultsNoSearch results to inspect (default 6, max 20)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
toolYes
as_ofNo
statusYes
requestNo
summaryNo
trace_idNo
warningsNo
data_modeNounknown
availabilityNo
schema_versionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$defs": {
+    "Summary": {
+      "additionalProperties": true,
+      "properties": {
+        "headline": {
+          "default": "",
+          "title": "Headline",
+          "type": "string"
+        },
+        "key_points": {
+          "items": {
+            "type": "string"
+          },
+          "title": "Key Points",
+          "type": "array"
+        }
+      },
+      "title": "Summary",
+      "type": "object"
+    }
+  },
+  "additionalProperties": true,
+  "properties": {
+    "as_of": {
+      "anyOf": [
+        {
+          "type": "string"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "default": null,
+      "title": "As Of"
+    },
+    "availability": {
+      "additionalProperties": true,
+      "title": "Availability",
+      "type": "object"
+    },
+    "data": {
+      "additionalProperties": true,
+      "title": "Data",
+      "type": "object"
+    },
+    "data_mode": {
+      "default": "unknown",
+      "enum": [
+        "live",
+        "mixed",
+        "simulated",
+        "unknown"
+      ],
+      "title": "Data Mode",
+      "type": "string"
+    },
+    "request": {
+      "additionalProperties": true,
+      "title": "Request",
+      "type": "object"
+    },
+    "schema_version": {
+      "anyOf": [
+        {
+          "type": "string"
+        },
+        {
+          "type": "integer"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "default": null,
+      "title": "Schema Version"
+    },
+    "status": {
+      "enum": [
+        "ok",
+        "partial",
+        "unavailable"
+      ],
+      "title": "Status",
+      "type": "string"
+    },
+    "summary": {
+      "$ref": "#/$defs/Summary"
+    },
+    "tool": {
+      "title": "Tool",
+      "type": "string"
+    },
+    "trace_id": {
+      "anyOf": [
+        {
+          "type": "string"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "default": null,
+      "title": "Trace Id"
+    },
+    "warnings": {
+      "items": {
+        "type": "string"
+      },
+      "title": "Warnings",
+      "type": "array"
+    }
+  },
+  "required": [
+    "tool",
+    "status"
+  ],
+  "title": "Envelope",
+  "type": "object"
+}
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark the operation read-only and non-destructive. The description goes further by disclosing the actual process: RSS headlines from four outlets, Tavily or Venice web search, counting conflicting coverage, and attaching market evidence. This gives the agent a useful mental model of what the tool does without contradicting the 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?

A single dense sentence earns its place: it states the purpose, the evidence sources, the counting logic, and the output framing. It is front-loaded with the core action and avoids filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists and annotations carry the safety profile, the description covers the essential inputs, method, and outcome. The only minor ambiguity is the reference to 'RYO analyze_token evidence,' which is not defined, but the overall flow is still 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 each parameter already has a meaningful description. The tool description restates the role of the claim and symbol in context but does not add new parameter-level detail beyond the schema, so the baseline of 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 opens with a specific verb and resource ('Verify a crypto news claim') and expands into the exact method: counting independent domains, counting opposite-leaning headlines, and attaching RYO token evidence. This clearly differentiates it from siblings like price_crosscheck or narrative_convergence, which address different questions.

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 imperative opening ('Verify a crypto news claim') makes the intended use case explicit. It does not name sibling tools or state when not to use it, but the context is clear enough that an agent can infer when this tool is relevant over the market-focused alternatives.

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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