Amalgix
Server Details
Mixture-of-Agents document intelligence engine. Multiple AI models cross-verify each other for 100% recall across 10 languages. 6 tools (analyze_document, extract_web, summarize, delegate_bulk_translate, estimate_cost, health_check). USDC pay-per-call on Base or Solana via x402. From $0.08/call.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Usage analytics
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Tool Definition Quality
Average 4.2/5 across 6 of 6 tools scored.
Tools generally have distinct purposes: document analysis (analyze_document), quick summaries (summarize), web extraction (extract_web), bulk translation (delegate_bulk_translate), cost estimation (estimate_cost), and health checks (health_check). Some overlap exists between analyze_document and extract_web when analyzing content, but descriptions clearly differentiate use cases (long documents vs. web pages).
Most tool names follow a verb_noun pattern (analyze_document, estimate_cost, extract_web), but 'health_check' starts with a noun and 'delegate_bulk_translate' uses an unusual verb. 'summarize' is a single verb without a noun. The mix of patterns and verb choices reduces consistency.
With 6 tools, the count is appropriate for a focused utility server covering document analysis, translation, web extraction, and service helpers. It is slightly lean but each tool has a clear role, and the number is within the typical 3-15 range.
The server covers core text processing tasks (analysis, summarization, web extraction, structured translation) along with meta tools. Notable gaps include plain text translation without JSON structure and extraction of structured data from documents. The set feels adequate but not fully comprehensive for the implied domain.
Available Tools
6 toolsanalyze_documentAnalyze DocumentARead-onlyIdempotentInspect
Analyze a document using multi-model actor-critic pipeline with chunking, extraction, validation, and synthesis. Best for long documents requiring deep analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Analysis question or focus area | |
| format | No | Optional: Force a specific input format. Default: auto-detect via magic bytes. | |
| content | Yes | Document content to analyze (max 20MB). Accepts: (1) plain text, (2) Base64-encoded file with data URI prefix (e.g., "data:application/pdf;base64,..."), or (3) raw Base64 binary. Supported binary formats: PDF, DOCX, XLSX, CSV. PRIVACY NOTICE: Content is transmitted to third-party LLM providers for processing. Do NOT submit documents containing passwords, private keys, SSNs, or other regulated PII. | |
| fileUrl | No | Optional: HTTPS URL to download the document from. If provided, content field is ignored. Supports: PDF, DOCX, XLSX, CSV, HTML. Max 20MB. |
Output Schema
| Name | Required | Description |
|---|---|---|
| meta | Yes | Processing metadata |
| analysis | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate safe, read-only, idempotent behavior. The description adds value by explaining the internal multi-model pipeline and processing steps, providing context beyond annotations without contradiction.
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?
Two concise sentences: first sentence defines the core functionality and methodology, second sentence provides optimal use-case guidance. No wasted words; information is front-loaded.
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 complexity (multi-model pipeline, chunking) and the presence of output schema and rich annotations, the description covers the high-level process and intent. Minor gaps: no mention of output format or potential errors, but output schema likely addresses this.
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 description adds no additional parameter meaning beyond what the schema already provides. Baseline score of 3 applies.
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 'Analyze a document using multi-model actor-critic pipeline' with specific techniques (chunking, extraction, validation, synthesis), distinguishing it from siblings like summarize or extract_web by emphasizing deep analysis of long documents.
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 phrase 'Best for long documents requiring deep analysis' implies usage context but does not explicitly mention when to avoid this tool or compare with siblings like summarize or extract_web.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delegate_bulk_translateBulk JSON TranslatorARead-onlyIdempotentInspect
Translate all string values in a JSON object or array to any target language. Preserves JSON structure, keys, and non-string values. Auto-chunks large payloads. Ideal for i18n locale files.
| Name | Required | Description | Default |
|---|---|---|---|
| json | Yes | JSON string (object or array) whose string values will be translated | |
| preserve_keys | No | If true (default), object keys are left untranslated. Set false to also translate keys. | |
| source_language | No | Source language (default: auto-detect). E.g. "English", "en" | |
| target_language | Yes | Target language name or ISO 639-1 code (e.g. "Chinese", "zh", "Japanese", "ja", "fr") |
Output Schema
| Name | Required | Description |
|---|---|---|
| meta | No | Translation metadata |
| translated | Yes | Translated JSON with preserved structure |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint=true, idempotentHint=true), description adds key behaviors: preserves structure, keys, and non-string values; auto-chunks large payloads. No contradictions.
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?
Three sentences, front-loaded with action and scope. Every sentence adds value; 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?
Covers purpose, behavior, and ideal use case. Existence of output schema reduces need to describe return values. Could mention limitations like max payload size, but overall complete.
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 baseline is 3. The description does not add significant parameter-specific meaning beyond what the schema already provides.
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?
Clearly states the verb 'Translate', the resource 'JSON object or array', and scope 'all string values'. Differentiates from siblings which are unrelated (e.g., document analysis, cost estimation).
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 context is clear: ideal for i18n locale files. Siblings are not similar, so no explicit when-not is needed. However, no guidance on alternatives or edge cases is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
estimate_costEstimate CostARead-onlyIdempotentInspect
FREE: Estimate the x402 USDC cost of any tool or multi-step workflow before paying. Use this before calling paid tools to check pricing.
| Name | Required | Description | Default |
|---|---|---|---|
| tool | Yes | Tool name to estimate cost for (e.g. "analyze_document", "extract_web", "summarize") | |
| workflow | No | Optional list of tool names for a multi-step workflow. Returns total cost for the full pipeline. | |
| content_length | No | Approximate character count of your input document (used for LLM cost estimation) |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | Yes | Pricing explanation |
| estimates | Yes | Cost estimates per tool |
| available_tools | Yes | List of available paid tools |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that the operation is FREE, which is important behavioral context. No contradiction with annotations.
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?
Two sentences, no wasted words, front-loaded with 'FREE' to immediately convey key benefit. 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 presence of an output schema (unseen but stated) and annotations, the description sufficiently covers purpose and usage. Could mention that it safely queries without side effects, but overall adequate for a simple estimation tool.
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 baseline is 3. Description only restates what schema already provides for each parameter, adding no new meaning beyond the schema field descriptions.
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?
Description clearly states it estimates x402 USDC cost for any tool or multi-step workflow, with verb 'estimate' and resource 'cost'. Clearly distinct from sibling tools which perform analysis, translation, extraction, health check, or summarization.
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?
Explicitly says 'Use this before calling paid tools to check pricing', giving clear context. Does not explicitly state when not to use, but the description strongly implies it's only for cost estimation prior to payment.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_webExtract Web ContentARead-onlyInspect
Extract content from a web page URL, optionally analyzing it with the actor-critic pipeline. Works with static and server-rendered HTML pages.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Web page URL to extract content from | |
| query | No | Optional analysis question to apply after extraction |
Output Schema
| Name | Required | Description |
|---|---|---|
| meta | No | Extraction metadata |
| content | Yes | Extracted page content in markdown format |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, etc. The description adds 'optionally analyzing it with the actor-critic pipeline', but does not elaborate on behavioral traits like rate limits, error handling, or internal mechanics. It neither contradicts nor significantly enhances the annotation-provided transparency.
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 long, front-loaded with the primary action ('Extract content from a web page URL'). Every word serves a purpose, with no redundant or vague phrasing.
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 presence of a clear output schema and annotations (readOnlyHint, openWorldHint), the description covers the tool's core functionality well. It mentions the optional analysis pipeline, which adds depth. However, it omits potential error conditions (e.g., invalid URL, non-HTML responses), leaving minor gaps.
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 schema already documents both parameters. The description adds modest value by explaining the 'query' parameter is for optional analysis via the actor-critic pipeline, but for 'url' it merely restates the schema. Baseline with high coverage is 3, and the description provides slight improvement.
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 uses a specific verb 'Extract' and resource 'web page content', clearly stating the tool's function. It also mentions optional analysis via 'actor-critic pipeline', distinguishing it from sibling tools like 'analyze_document' and 'summarize'.
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 notes it works with 'static and server-rendered HTML pages', providing basic context. However, it lacks explicit guidance on when not to use this tool or what alternatives might be better for non-HTML content (e.g., PDFs via 'analyze_document').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_checkHealth CheckARead-onlyInspect
FREE: Check service health, engine availability, and uptime. Use before dispatching paid calls to confirm the service is operational.
| Name | Required | Description | Default |
|---|---|---|---|
| verbose | No | If true, include detailed per-engine diagnostics (default: false) |
Output Schema
| Name | Required | Description |
|---|---|---|
| status | Yes | Overall service status |
| timestamp | Yes | ISO 8601 timestamp |
| engines_ok | Yes | Whether all engines are operational |
| uptime_seconds | Yes | Server uptime in seconds |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive behavior. The description adds value by noting the tool is free and checks multiple aspects (health, availability, uptime) without contradicting annotations.
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?
Single, front-loaded sentence with no superfluous words. Efficiently conveys purpose and cost.
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 a simple boolean parameter and existing annotations/output schema, the description fully addresses purpose, usage, and cost. No missing information for effective agent invocation.
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% and the parameter 'verbose' is well-described in the schema. The description does not add extra meaning beyond the schema, achieving the baseline for high coverage.
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 verb 'Check' and the resource 'service health, engine availability, and uptime'. It distinguishes from sibling tools which have different functions like analyzing, delegating, estimating, extracting, and summarizing.
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?
Explicitly instructs to use 'before dispatching paid calls to confirm the service is operational'. Provides clear context but does not explicitly mention alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
summarizeSummarize DocumentARead-onlyIdempotentInspect
Generate a concise summary with key points. Faster and cheaper than analyze_document — best for shorter documents.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Document text to summarize | |
| max_length | No | Optional maximum summary length in words (default: 500) |
Output Schema
| Name | Required | Description |
|---|---|---|
| meta | No | Processing metadata |
| summary | Yes | Concise summary text |
| keyPoints | No | Bullet-point key takeaways |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint, so the tool's safety profile is clear. Description adds performance context ('faster, cheaper') but doesn't address potential truncation or determinism. Still, good complement.
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?
Two sentences, no fluff. Could benefit from slight structural separation (e.g., bullet points), but current format is efficient and front-loads the primary purpose.
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?
Has an output schema (not shown but present) to cover return values. Two parameters are fully documented. Description covers when to use and distinguishes sibling. Adequate for a simple tool.
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 baseline is 3. Description does not add meaning beyond schema parameters (content, max_length). The 'faster/cheaper' note is about performance, not parameter semantics.
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 it 'generate[s] a concise summary with key points', identifying the verb (generate) and resource (summary). It also differentiates from sibling 'analyze_document' by noting it's faster/cheaper.
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?
Explicitly states 'Faster and cheaper than analyze_document — best for shorter documents', providing clear when-to-use guidance and a named alternative.
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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