OSINT(info): scans several assets for narrative-vs-data discrepancies. INFORMATION ONLY. assets=[bitcoin,ethereum,...]. [x402: 15.0 USDC on Base, pay-per-use]
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | service input |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and it does state two important traits: 'INFORMATION ONLY' signals a read-only operation and the x402 note discloses pay-per-use. It omits deeper behavioral details such as data sources, freshness, auth flow, or output behavior, but the core safety and cost traits are present.
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 compact and front-loads the main function, then adds the mode, asset examples, and payment note without redundant wording. The terse fragments are efficient, though slightly cryptic.
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 and the input schema is a generic string, so the description is the only source of invocation guidance. It fails to clarify what the input string should contain, how the discrepancy output is presented, or what asset list is actually supported, leaving an agent with meaningful uncertainty.
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 baseline of 3 applies even though 'service input' is a generic placeholder. The 'assets=[bitcoin,ethereum,...]' hint in the description adds some meaning about the input value, but it is informal and not mapped to the actual parameter contract.
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 names a specific action ('scans') and a concrete output concept ('narrative-vs-data discrepancies') across assets, so an agent can infer the core function. However, it doesn't differentiate from closely related siblings like osint-signal or fact-check, and 'several assets' is left partially unspecified.
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?
There is no explicit when-to-use guidance, exclusion criteria, or named alternatives among the many OSINT/fact-checking siblings. The 'INFORMATION ONLY' tag and asset list give context but do not tell an agent when to choose this over related tools.
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.
The set contains many trivially indistinct tools: ai-inference/inference, compress/comprimir, count-tokens/contar-tokens, detect-language/language-detect, and multiple overlapping OCR receipt variants. With 160 tools and pairs that differ only by language or suffix, an agent cannot reliably distinguish several capabilities.
Most names are readable lower-hyphen identifiers, but they mix action verbs, noun phrases, domain prefixes, pipeline suffixes, Spanish/English, and arbitrary demo/batch labels. There is a loose convention, but no consistent verb_noun pattern.
160 tools on one server is an extreme count and clearly unwieldy. Even as a marketplace, exposing every variant, demo, and composed bundle as a top-level MCP tool overwhelms agent selection and adds little distinct capability.
The set covers a huge range of text, image, audio, code, market, compliance, and content-workflow tasks, so many intents have some available tool. However, it is a grab-bag rather than a defined service surface, and the arbitrary demo/specialized variants make it unclear whether a needed operation truly exists or is just a duplicate.