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Glama

Shodan

by io.github.pipeworx-io

What Can I Ask Pipeworx?

suggest_questions
Read-onlyIdempotent

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass topic (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional focus area: finance | pharma | economics | real-estate | betting | weather | government | science | news. Omit for a cross-category spread.

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already mark it as read-only, open-world, idempotent, non-destructive. Description adds detail on return structure (category-bucketed examples with tool+argument shape) and call patterns (no args vs topic filter). Adds useful context beyond annotations.

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?

Description is informative but slightly long; front-loaded with common queries. Could be trimmed slightly, but every sentence adds value. Well-structured for quick scanning.

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 no output schema, description fully explains what is returned (category-bucketed examples, tool+argument shape). Also covers optional parameter and usage context. Complete for an onboarding tool.

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

Parameters4/5

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

Schema coverage is 100%, description explains the topic parameter with examples ('finance', 'pharma', 'betting') and clarifies behavior when omitted. Adds meaning beyond the schema's basic description.

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?

Clearly states it is the onboarding entry point to discover what Pipeworx can do, returning category-bucketed example questions. Distinguishes from siblings by specifying it's for learning capabilities and connecting to tools.

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

Usage Guidelines5/5

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

Explicitly says 'Use this FIRST when you do not yet know what Pipeworx can do for you' and mentions alternatives like ask_pipeworx, entity_profile, compare_entities. Provides clear when-to-use and when-not-to 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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TDQS

A3.5/5.0
Disambiguation2/5

The server name 'Shodan' misleadingly implies a narrow focus on network security scanning, yet the tool set includes many unrelated tools for data lookup (ask_pipeworx, deep_research, etc.), memory management, and subscriptions. Within the pipeworx tools, there is overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, which can confuse agents about which to choose.

Naming Consistency2/5

Tool names mix conventions: some use underscores (ai_visibility_check, shodan_host), others use lowercased phrases without clear partitioning (ask_pipeworx, deep_research, entity_profile). Verb-noun patterns are inconsistent (e.g., 'scan_competitor_ai_presence' vs 'compare_entities'). This lack of a predictable naming scheme increases cognitive load.

Tool Count2/5

With 33 tools covering distinct domains (Shodan scanning, pipeworx data, memory, subscriptions), the server feels overloaded and unfocused. While each tool may individually be useful, the bundling contradicts the principle of a single-purpose server. A more appropriate count for a focused Shodan server would be under 10 tools.

Completeness2/5

For the Shodan domain, only three tools are provided (host, host_count, host_search), missing key capabilities like DNS lookups, vulnerability search, or API key management. The pipeworx tool set is extensive but not the server's advertised purpose, leaving gaps in both areas. The addition of memory and subscription tools adds unrelated functionality without completing any single domain.

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