Content Intelligence API
Server Details
9 AI content tools: extract, analyze, research, compare. x402 or subscribe for credits.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.5/5 across 9 of 9 tools scored.
Each tool has a distinct purpose (e.g., analyze_text vs. compare_articles, research_topic vs. daily_brief) with no overlapping functionality. Descriptions clearly differentiate them.
Most tools follow a consistent verb_noun pattern (e.g., analyze_text, compare_articles, extract_content). 'competitor_intel' is a minor deviation as it's noun-based, but still clear.
9 tools is well-scoped for a content intelligence API, covering text analysis, comparison, extraction, monitoring, and research without being overwhelming.
Core operations (analysis, extraction, comparison, monitoring) are covered. Minor gap: no explicit tool for unwatching a page, but the surface is largely complete for common workflows.
Available Tools
9 toolsanalyze_textBInspect
Analyze text for summary, sentiment, entities, topics, and classification. Pay per call (0.003 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to analyze (up to 50k chars) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description bears full responsibility. It does not disclose any behavioral traits beyond the basic function and pricing. No mention of idempotency, error handling, rate limits, or permission requirements.
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, front-loaded with the core purpose. The pricing detail is relevant but could be integrated more smoothly. Overall efficient with minimal waste.
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 tool has a single parameter and no output schema, reducing complexity. The description lists the analyses performed, which is helpful, but lacks details on output format or behavior. Adequate but leaves gaps for the agent.
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% (one parameter fully described). The description does not add new meaning beyond the schema; both mention the character limit. Baseline 3 is appropriate as no additional semantic value is contributed.
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 that the tool analyzes text for summary, sentiment, entities, topics, and classification. It provides a specific verb ('analyze') and resource ('text'), and lists distinct capabilities that differentiate it from sibling tools like 'sentiment_over_time' which is narrower.
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?
No guidance on when to use this tool versus alternatives. The description only mentions pricing (pay per call or subscription) but lacks context about prerequisites, ideal use cases, or situations where other tools might be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_articlesAInspect
Compare two sources (URLs or text) for similarities, differences, coverage, and bias. Pay per call (0.01 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| aspect | No | Optional focus aspect (e.g., 'security', 'performance') | |
| source_a | Yes | First source URL or text content | |
| source_b | Yes | Second source URL or text content |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It reveals pricing (pay-per-call) but does not mention any side effects, required permissions, whether data is logged, or the nature of the comparison (e.g., if it fetches external URLs). Minimal 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 one sentence plus a pricing note, with no filler. It is appropriately sized and front-loaded, earning 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?
There is no output schema, so the description should explain the return format. It mentions 'similarities, differences, coverage, and bias' but does not describe the structure, fields, or how results are presented. For a tool with 3 parameters, this is insufficient.
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. The description adds value by clarifying that 'source_a' and 'source_b' can be 'URLs or text', and for 'aspect' gives an example ('e.g., 'security', 'performance''). This supplements the schema 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?
The description clearly states 'Compare two sources (URLs or text) for similarities, differences, coverage, and bias', with a specific verb and resource. It distinguishes itself from sibling tools like 'analyze_text' (single text) and 'competitor_intel' (competitive analysis).
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 mentions pricing ('Pay per call (0.01 USDC) or use subscription') but does not provide explicit guidance on when to use this tool versus alternatives like 'analyze_text' or 'sentiment_over_time'. No prerequisites or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
competitor_intelBInspect
Competitive intelligence analysis comparing two companies/entities. Searches web, extracts content, and provides structured comparison. Pay per call (0.025 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| aspect | No | Optional focus area (e.g., 'market share', 'innovation') | |
| industry | No | Optional industry context | |
| company_a | Yes | First company name | |
| company_b | Yes | Second company name |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description discloses that it searches web, extracts content, and provides structured comparison, plus pricing. But it does not mention any destructive actions, authentication needs, rate limits, or output format details. Partially adequate.
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, first sentence clearly states purpose and method, second addresses pricing. No wasted words, but could be more front-loaded with key constraints.
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?
Complexity is moderate (4 params, no output schema). Description covers core function and pricing but lacks details on output format, expected behavior, and differentiation from 8 sibling tools. Leaves 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%; all parameters have descriptions. The description adds minimal extra meaning beyond the schema (e.g., 'focus area' example). 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 states 'Competitive intelligence analysis comparing two companies/entities' with clear verb (analyzes, compares) and resource (companies). It distinguishes from siblings like compare_articles and research_topic by specifying web search and structured comparison of specific companies.
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?
No explicit guidance on when to use this tool vs alternatives. Only mentions pricing ('Pay per call or use subscription'), but lacks when-to-use or when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
daily_briefBInspect
Generate a briefing from multiple URLs or topics. Supports executive, bullet, and detailed formats. Pay per call (0.015 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | No | Array of URLs to include in the brief | |
| focus | No | Optional focus area for the briefing | |
| format | No | Briefing format style | executive |
| topics | No | Array of topics to search and include in the brief |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only mentions pricing (pay-per-call or subscription), which is a behavioral trait. However, it omits other important aspects like whether the tool is read-only (likely write, as it generates), auth needs, rate limits, or what happens on error. This is insufficient for a tool that creates content.
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: first sentence states purpose and formats, second mentions pricing. It is front-loaded and concise with no unnecessary 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 tool has 4 optional parameters and no output schema. The description explains input and pricing but does not describe the output structure (e.g., format of the briefing). For a simple tool, this is adequate but missing key information about what the agent can expect as a response.
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 parameters. The description adds little new meaning beyond 'from multiple URLs or topics' and format mention. Baseline is 3, and the description does not add significant parameter semantics (e.g., format length or focus details).
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 'Generate a briefing from multiple URLs or topics' and lists supported formats. While it doesn't explicitly differentiate from sibling tools like research_topic or competitor_intel, the combination of name and description makes its purpose clear. A 5 would require explicit differentiation.
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 context on when to use the tool (generating briefings from URLs/topics) and mentions pricing, but does not give any when-not guidance or alternative tools. The sibling list is provided externally, but the description itself lacks such guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_contentAInspect
Extract clean readable content from a URL. Removes ads, clutter, navigation. Pay per call (0.005 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to extract content from |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose all behavioral aspects. It mentions removal of ads, clutter, navigation, and cost per call, but lacks details on idempotency, error handling, or any side effects. Adequate but not thorough.
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 short, front-loaded sentences with no fluff. Every word serves a purpose: action, effect, cost model.
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 (1 param, no output schema), the description covers purpose and cost. Could mention behavior on invalid URLs or content types, but overall adequate.
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?
Only one parameter (url) with schema description already covering it. Description adds minimal extra meaning beyond the schema. Since schema coverage is 100%, baseline is 3.
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 tool extracts clean readable content from a URL, removing ads, clutter, navigation. The verb 'extract' and resource 'content from a URL' are specific, and it distinguishes from siblings like analyze_text or extract_structured.
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?
Provides cost information (pay per call or subscription) which helps in decision-making, but does not explicitly state when to use this tool versus alternatives like extract_structured. No when-not or context exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_structuredAInspect
Extract structured JSON data from a URL. Define a schema or let AI infer the structure. Pay per call (0.008 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to extract structured data from | |
| schema | No | Optional JSON schema definition for extraction fields |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It correctly describes the core action (extract structured JSON) and adds cost details. No misleading or missing behavioral traits.
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 concise sentences with front-loaded purpose. No redundancy, each 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?
Adequate for a simple 2-parameter tool, but lacks information about return format (beyond 'JSON'), error handling, or behavior with invalid URLs. Could be more 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 coverage is 100%, but the description adds value beyond the schema by explaining the optional schema parameter allows AI inference, which is not clear from the schema alone.
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?
Explicitly states it extracts structured JSON data from a URL. Differentiates from sibling 'extract_content' by targeting structured output. Mentions optional schema definition or AI inference, clearly defining the scope.
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?
Implies usage for extracting structured data from any URL, but does not specify when to prefer over alternatives like 'extract_content' or 'research_topic'. Cost info is useful but not a usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
monitor_pageAInspect
Extract a page with a content hash for change detection. Use action 'watch' to register for ongoing monitoring. Pay per call (0.005 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to monitor | |
| action | No | 'check' returns content + hash; 'watch' registers for ongoing change detection | check |
| page_id | No | Optional custom ID for the monitored page |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adds behavioral context: pricing (cost per call) and the two distinct actions. It could mention rate limits or side effects of 'watch', but it adequately explains the core behavior beyond the schema.
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?
Extremely concise: two sentences. First sentence defines purpose, second gives usage and pricing. No fluff, every word earned 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?
For a tool with 3 parameters and no output schema, the description covers the main use cases and pricing. Could be more complete by describing return format or error conditions, but it is sufficient for an agent to use correctly.
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 substantial meaning to parameters beyond what the schema already provides. It repeats action descriptions but adds context about content hash for the return value, not parameters.
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 extracts a page with a content hash for change detection, distinguishing it from siblings like extract_content. It also explains the two actions (check and watch), making the purpose specific and unambiguous.
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?
Provides explicit guidance on when to use the 'watch' action vs 'check'. However, it does not compare to sibling tools or state when not to use this tool. Pricing info is included but not directly usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
research_topicBInspect
Multi-source research synthesis on any topic. Searches the web and synthesizes findings with AI. Pay per call (0.02 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| depth | No | standard | |
| query | Yes | Research query or topic |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'synthesizes findings with AI' and pricing, but fails to state whether the tool is read-only, destructive, or requires authentication, leaving behavioral traits ambiguous.
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 exceptionally concise, consisting of two short sentences that front-load the core purpose. Every sentence adds value, with no unnecessary words or repetition.
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 (2 params, no output schema) and lack of annotations, the description provides minimal context. It does not explain return values, synthesis process, or limitations, leaving key usage aspects unaddressed.
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 50%. The description adds no information about the 'depth' parameter beyond the schema's enum, and the 'query' description merely repeats the schema. The description does not compensate for the missing schema description for 'depth'.
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 performs 'multi-source research synthesis' on any topic, which is a specific verb-resource pair. It distinguishes from siblings like 'analyze_text' or 'compare_articles' by focusing on web search and AI synthesis.
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?
No explicit guidance on when to use this tool versus alternatives. The description does not mention when not to use it or recommend sibling tools for specific scenarios, leaving the agent without decision context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sentiment_over_timeBInspect
Analyze sentiment trends across multiple sources (URLs or texts). Compares and synthesizes sentiment. Pay per call (0.008 USDC) or use subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | No | Array of URLs to analyze for sentiment | |
| texts | No | Array of text contents to analyze for sentiment | |
| topic | No | Optional topic context for analysis |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should reveal behavioral traits. It mentions the pay-per-call cost model, which is useful. However, it does not disclose whether both 'urls' and 'texts' can be combined, any limits, or authentication requirements.
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 primary action, and no unnecessary words. It efficiently conveys purpose and pricing.
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?
Despite having no output schema and parameter descriptions, the tool name emphasizes 'over time' but the description never mentions time intervals, trends calculation, or output format. This leaves a critical gap for an agent to understand what the tool returns.
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 describes each parameter. The description adds minimal semantic value beyond summarizing the tool's purpose, and does not explain how parameters interact or constraints like formats.
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 states 'Analyze sentiment trends across multiple sources', specifying the verb and resource. It distinguishes from siblings like 'analyze_text' by mentioning comparison and synthesis, but does not explicitly clarify the 'over time' component in the tool name.
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?
No guidance is provided on when to use this tool versus siblings like 'compare_articles' or 'analyze_text'. The description only mentions pricing, which is not usage 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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