Skip to main content
Glama

Tokenized Stocks & Agent Data (x402)

ai_progress_as_of

Use this when you need AI progress as it stood on a past date: the reading of the same 129 series (benchmarks, compute, AGI prediction-market odds, model pricing, AI stocks, energy, space, robotics, research output) taken on YYYY-MM-DD. Dated ids are listed free at /. Same per-series shape as /ai-progress/latest, so you can diff dates yourself; /ai-progress/what-changed does the diff for you. Unknown id -> 404. Costs $0.005 (USDC on Base or Solana, x402). HTTP twin: https://x402-accelerometer-feed.fly.dev/ai-progress/as-of/{id}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesreading date YYYY-MM-DD, from the free menu

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so thoroughly: it discloses the fixed data scope, cost ($0.005 via x402), payment rails, unknown-id 404 behavior, and that output shape matches /ai-progress/latest. This goes well beyond what annotations alone would have provided.

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?

Dense but every clause earns its place: front-loaded purpose, sibling differentiation, return-shape comparison, error behavior, cost, and HTTP twin. No filler or tautology; the length is justified by the amount of essential operational context.

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?

Despite having no output schema, the description compensates by linking the return shape to /ai-progress/latest, specifying the series count, and covering errors and cost. For a single-parameter dated-lookup tool, an agent has enough information to invoke it 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% and the parameter already has a clear description ('reading date YYYY-MM-DD, from the free menu'). The prose repeats the free-menu source and adds error behavior, but does not meaningfully extend the schema's parameter semantics.

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 a precise purpose: retrieving AI progress 'as it stood on a past date' and enumerates the 129-series composition. It also names /ai-progress/latest and /ai-progress/what-changed, making it easy to distinguish this tool from siblings.

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

Usage Guidelines5/5

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

Explicitly says 'Use this when you need AI progress as it stood on a past date' and points to /ai-progress/what-changed for diffing instead. The guidance is directly actionable and gives the agent a clear decision rule among the sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources