Skip to main content
Glama

batch_analyze

Analyze up to 10 URLs or texts in parallel to get structured competitive intelligence including positioning, pain points, and market angles for a flat fee of $0.20 USDC.

Instructions

Analyzes up to 10 competitors in parallel in a single call.

Cost: $0.20 USDC flat for the entire batch (regardless of item count), paid automatically via x402 on Base mainnet. More efficient than calling analyze_competitor 10 times ($0.50 USDC).

Each item in the batch is processed in parallel, so total time is similar to a single analysis (2-5 seconds) regardless of batch size.

Returns a JSON object with:

  • results (list): Array of analysis results, one per item

    • id (str): The id you provided, or the item index as string

    • source (str): The url or "provided_text"

    • analysis (object): Same structure as analyze_competitor output

    • cached (bool): Whether this result was served from cache

  • total (int): Number of items processed

  • cached (int): Number of items served from cache

  • response_ms (int): Total processing time in milliseconds

  • price_paid_usdc (str): Total price paid ("0.20")

Parameters:

  • items (list[dict]): List of up to 10 analysis requests. Each item can have:

    • url (str, optional): URL to analyze

    • text (str, optional): Text description to analyze

    • context (str, optional): Your product context for relevance

    • id (str, optional): Identifier to track items in the response

Example usage: batch_analyze(items=[ {"url": "https://notion.so", "id": "notion"}, {"url": "https://coda.io", "id": "coda"}, {"text": "Obsidian is a local-first note-taking app", "id": "obsidian"}, ])

Best for:

  • Due diligence: analyze all competitors in a market in one call

  • Weekly monitoring: check 5-10 competitors every Monday

  • Market mapping: build a full competitive landscape in seconds

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses behavioral traits: parallelism, flat cost ($0.20), payment method (x402 on Base mainnet), caching behavior, and return structure. It covers performance (2-5 seconds), item limits, and cost comparison, leaving no ambiguity about how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is lengthy but well-structured with clear sections (cost, performance, returns, parameters, example, best for). The core purpose is front-loaded. Minor redundancy (e.g., repeated cost mention) prevents a 5, but it earns its length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low parameter count (1), rich output schema, and absence of annotations, the description covers all necessary context: inputs, outputs, behavior, cost, timing, and use cases. No gaps are apparent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description thoroughly documents each parameter in 'items': url, text, context, id, with types, optionality, and an example. This adds full semantic meaning beyond the bare-bones schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with 'Analyzes up to 10 competitors in parallel in a single call,' which provides a specific verb (analyzes), resource (competitors), and scope (up to 10, parallel, single call). It distinguishes from sibling 'analyze_competitor' by highlighting efficiency and cost benefits, making the purpose crystal clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly compares to 'analyze_competitor' and includes a 'Best for' section listing scenarios like due diligence and weekly monitoring. It lacks explicit when-not-to-use or alternatives beyond the sibling, but the comparison and use cases provide strong guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/teodorofodocrispin-cmyk/intelica-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server