Syftly
Server Details
Ranks the best AI tool or API per task: transcription, TTS, web search, scraping and OCR.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.4/5 across 1 of 1 tools scored.
With only one tool, there is no potential for confusion between tools. The tool's purpose is clearly distinct.
The single tool name 'find_best_tool' follows a clear verb_noun pattern, consistent with good naming practices.
The server has only one tool, which feels thin for a domain covering multiple tasks like transcription, TTS, etc. The scope suggests more tools might be expected, but the single tool may suffice for its focused recommendation purpose.
The tool covers recommendation for multiple domains, but there is no indication of additional tools for detailed provider info or data updates, leaving some potential gaps in workflow.
Available Tools
1 toolfind_best_toolAInspect
Given a natural-language question about which AI tool or API is best for a task (currently transcription, text-to-speech, web search, scraping & browser and ocr & document extraction), return Syftly's ranked recommendation: a citeable summary, a provider table with prices and trade-offs, dated sources, and a confidence label. Optionally pass "category" to disambiguate; otherwise it is detected from the question.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The question in natural language, e.g. 'best transcription API for Dutch'. | |
| category | No | Optional category id to disambiguate the question; omit to let Syftly detect it. |
Output Schema
| Name | Required | Description |
|---|---|---|
| slug | Yes | |
| query | Yes | The human question (page H1). |
| routing | Yes | Honest routing outcome: 'matched' = answered from a real category; 'none' = no category matched (out-of-scope/gibberish) — an honest no-match, not a fabricated answer; 'ambiguous' = fit 2+ categories. 'none'/'ambiguous' carry `categories` and no real recommendation/providers. |
| sources | Yes | |
| summary | Yes | Citeable summary, 40-80 words, reused verbatim across all views. On a no-match, the plain-language message. |
| updated | Yes | ISO date. |
| category | Yes | e.g. 'transcription'; '' on a no-match. |
| providers | Yes | |
| categories | No | Present only when routing !== 'matched': the supported categories so the caller can re-ask in scope. |
| confidence | Yes | Confidence/depth label. |
| recommendation | Yes |
Tool Definition Quality
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 the tool returns a citeable summary, provider table with prices and trade-offs, dated sources, and a confidence label. It also mentions automatic category detection. This gives a good picture of the tool's behavior, though it doesn't specify side effects, rate limits, or auth requirements (assumed read-only).
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, but the first sentence is long and dense, listing multiple components of the return value. It is clear and front-loaded but could be slightly more concise. Nevertheless, it is well-structured with no wasted words.
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 that the tool has an output schema (not shown), the description does not need to detail the return format. It already summarizes what is returned effectively. It covers the tool's purpose, usage context, and optional parameter, making it complete for a tool with 2 parameters and clear behavior.
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 coverage is 100%, so the description adds value beyond the schema. For the category parameter, it explains that omitting it will trigger automatic detection, which is not in the schema description. For the query parameter, it reiterates the purpose but doesn't add new details. Overall, the description enhances understanding of parameter usage.
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 returns ranked recommendations for AI tools/APIs for specific tasks (transcription, TTS, etc.). It uses specific verbs ('return Syftly's ranked recommendation') and lists the supported categories, making the purpose unambiguous. No sibling tools exist, but the description is specific enough to distinguish from hypothetical alternatives.
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 explicitly says to use this tool when a natural-language question asks about the best AI tool for a task within the listed categories. It also explains the optional category parameter and automatic detection. While it doesn't explicitly state when not to use or mention alternatives, the context is clear and provides actionable guidance.
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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{
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