AgentFeed

Tokenized stock rankings

get_peg_universe

Read-onlyIdempotent

Tokenized stocks ranked by off-hours peg risk: every tokenized US equity we track, with p95 and max deviation bps, market-open deviation as the control, and median liquidity. Dead pools are excluded rather than reported as perfect pegs. Costs 0.05 USDC per call (x402, USDC on Solana or Base).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`days`	No	lookback 1-30, default 7
`min_liquidity_usd`	No	filter out thinner pools

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes	the get_peg_universe payload; a real captured example is free at https://x402.ochinimus.app/api/sample/get_peg_universe
`tool`	Yes	the tool that produced this payload

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 25, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "data": {
+      "additionalProperties": {},
+      "description": "the get_peg_universe payload; a real captured example is free at https://x402.ochinimus.app/api/sample/get_peg_universe",
+      "propertyNames": {
+        "type": "string"
+      },
+      "type": "object"
+    },
+    "tool": {
+      "const": "get_peg_universe",
+      "description": "the tool that produced this payload",
+      "type": "string"
+    }
+  },
+  "required": [
+    "tool",
+    "data"
+  ],
+  "type": "object"
+}

First observedSep 6, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already establish this as read-only, idempotent, and non-destructive. The description adds meaningful context by disclosing the per-call cost (0.05 USDC via x402) and the important exclusion rule that dead pools are not reported as perfect pegs. These are behavioral details beyond what the annotations express.

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?

Three sentences with no filler: the core ranking and metric set is front-loaded, the dead-pool exclusion is a critical caveat, and the payment requirement is included. Every sentence earns its place.

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?

For a read-only universe listing with zero required parameters, an output schema, and complete annotations, the description covers what the tool returns, how it is priced, and an edge-case behavior. Nothing essential for calling it correctly is missing.

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 description coverage is 100%, with both parameters (days, min_liquidity_usd) already documented in the input schema. The description adds context around liquidity and lookback, but it does not need to compensate for any schema gap. 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 states precisely what the tool does: it returns every tracked tokenized US equity ranked by off-hours peg risk, with specific metrics (p95/max deviation bps, market-open control, median liquidity). This is a specific resource and operation, clearly distinct in scope from single-asset sibling tools like get_peg_deviation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The usage context is implied by the title and first sentence: use this when you want a broad universe-level ranking of tokenized stocks by off-hours peg risk. However, there is no explicit guidance about when not to use it or which sibling alternative to prefer, such as get_peg_deviation for a specific asset.

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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