GET endpoint that returns remaining credits for the bearer token in the Authorization header. Requires Authorization: Bearer tf_live_<64-char-hex>. Costs 0 credits. Use to monitor agent budget.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly calls this a 'GET endpoint' that 'returns remaining credits,' indicating a read-only operation. However, the annotations declare readOnlyHint: false, which means the tool is not marked as read-only. This directly contradicts the description's implied behavior, so the transparency score is 1 and an annotation contradiction is flagged.
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 compact and front-loaded: it immediately states what the tool does, then supplies authentication and cost details, and ends with the primary use case. Every sentence adds value with no redundant information.
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?
For a zero-parameter tool, the description is quite complete: it specifies the endpoint, auth requirement, cost, and intended use. The only gap is that it does not describe the response format, but the absence of an output schema and the simplicity of the resource make this a minor omission.
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 tool has zero parameters, so schema coverage is trivially 100%. The description adds meaningful context about the required Authorization header format (Bearer tf_live_<64-char-hex>) and that the operation costs 0 credits, which goes beyond the empty schema.
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 states the tool is a GET endpoint that returns remaining credits for the bearer token, with a specific verb and resource. It distinguishes itself from sibling payment tools like tf_payment_buy_credits and tf_payment_history by focusing specifically on balance retrieval.
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?
The description provides clear context for when to use the tool ('Use to monitor agent budget') and implies it is a lightweight operation by noting it costs 0 credits. However, it does not explicitly name alternative tools or state when not to use it, which prevents a perfect score.
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.
