Currency conversion with real-time rates. Supports 150+ currencies including fiat (USD, EUR, GBP, AED, SAR, INR, PKR, PHP) and crypto (BTC, ETH). Returns rate, converted amount, and inverse rate.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target currency code (default: AED) | |
| from | Yes | Source currency code (default: USD) | |
| amount | No | Amount to convert (default: 1) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that rates are real-time and that it returns rate, converted amount, and inverse rate. However, it does not mention any limitations, such as rate source, potential delays, or whether it requires network access. For a conversion tool, this is adequate but not rich; it could mention that it does not perform actual transactions or that rates are indicative.
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 two sentences, front-loaded with the core purpose, and includes essential details (supported currencies, return values) without any fluff. 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?
Given the tool's simplicity (3 params, no output schema, no annotations), the description is fairly complete. It explains what it does, what it returns, and gives examples of supported currencies. It could mention that the 'amount' is optional and defaults to 1, but the schema already covers that. The description is sufficient for an agent to understand the tool's capabilities.
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?
Schema description coverage is 100%, so the schema already documents all three parameters. The description adds context by listing example currencies and stating that it returns rate, converted amount, and inverse rate, which helps understand the output. However, it does not add details about parameter formats (e.g., currency codes are case-sensitive) or the meaning of the 'amount' parameter beyond what the schema says. Baseline 3 is appropriate.
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's function: 'Currency conversion with real-time rates.' It specifies the resource (currency conversion) and the action (convert), and distinguishes it from siblings by mentioning support for 150+ currencies including fiat and crypto, which is unique among the listed tools.
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 implies usage for converting between currencies but does not explicitly state when to use this tool versus alternatives. It mentions real-time rates and supported currencies, which gives context, but lacks explicit guidance on when not to use it or alternatives. Given the sibling tools include crypto_data and gold_price, which might overlap, more explicit differentiation would be helpful.
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.
Several tools have overlapping functionality, such as domain_infra, company_report, and due_diligence all covering DNS/WHOIS/SSL checks. Similarly, web_scrape and scrape_structured both extract website content, and verify_email overlaps with email_audit on DNS-based email checks. This creates ambiguity in tool selection, especially for agents looking for a specific type of analysis.
All tool names use lowercase with underscores, which provides a consistent style. However, the grammatical pattern varies: some are verb-object (verify_email, currency_convert), some are noun-noun (domain_infra, site_audit), and others are adjective-noun (arabic_sentiment, brand_scout). This is not chaotic, but it lacks a rigid verb_noun convention, making it slightly less predictable.
With 25 tools, this sits at the upper boundary of what is considered 'heavy' but is still usable. The server covers a wide range of domains (Arabic NLP, web scraping, domain/email analysis, finance, faith), so the count is justified to a degree, but agents may be overwhelmed by choice. It is borderline appropriate for such a broad utility server.
The tool surface covers many common operations (scraping, DNS checks, email verification, financial data), but there are notable gaps. For example, no generic translation tool exists, only Arabizi-to-Arabic, and there is no text generation or embedding. While the set is extensive, it is not fully comprehensive for the diverse domains it touches, leaving some obvious missing operations.