GET endpoint that returns confirmed USDC purchases (tx_hash, amount_usd, credits_added, block_number, confirmed_at) plus current balance and totals for the bearer token. Requires Authorization: Bearer tf_live_<64-char-hex>. Costs 0 credits. Tokens minted before the ledger existed return current_balance with purchases: [].
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states it is a GET endpoint that returns data, implying a read-only operation. However, the readOnlyHint annotation is false, indicating the tool is not read-only. This contradiction—description implying read-only while annotation says otherwise—warrants a score of 1 and constitutes an annotation contradiction. The description also fails to disclose any potential side effects that the annotation hints at.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose. It packs in the return fields, auth requirements, credit cost, and an edge case without any wasted words. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential aspects: purpose, auth, cost, and an edge case for old tokens. It lists return fields, which compensates somewhat for missing output schema. However, the contradiction with annotations undermines completeness—if the tool is not read-only, the description fails to mention any side effects. Also, no error handling or pagination details are given, though for a simple history endpoint this is acceptable. Overall, it's functional but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the schema coverage is trivially 100%. With 0 params, the baseline is 4. The description adds no parameter info because none exist, which is appropriate. The mention of Authorization header is authentication, not a parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a GET endpoint that returns confirmed USDC purchases with specific fields, plus balance and totals. This specific verb+resource definition distinguishes it from siblings like tf_payment_balance (which likely only returns balance) and tf_payment_confirm (which confirms payments).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context: requires Authorization Bearer header with a specific token format, costs 0 credits, and describes behavior for old tokens. Though it doesn't explicitly name alternatives, the description implies its role as a payment history endpoint. A minor gap is the lack of explicit 'use this when you need purchase history vs. other tools'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes (e.g., tf_btc_price vs tf_fear_greed), but there is some overlap between free and premium aggregated tools (e.g., tf_briefing, tf_premium_briefing, tf_premium_agent_context). However, descriptions explicitly differentiate them by content and cost.
All tools follow a consistent pattern: 'tf_' prefix (with 'tf_premium_' for premium ones) and snake_case. Names are descriptive and predictable, e.g., tf_btc_price, tf_earthquakes, tf_premium_macro.
27 tools is on the high side, but the server covers a broad domain (crypto, finance, earthquakes, AI trends, payment system, etc.). Each tool serves a specific purpose, so the count is borderline acceptable but feels slightly heavy.
The tool surface covers a wide range of data feeds: crypto, forex, macro indicators, earthquakes, HN, HuggingFace, prediction markets, payment system, and service status. Minor gaps exist (e.g., no dedicated stock prices tool beyond premium macro, no weather), but overall it's comprehensive for a terminal feed.
