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Shodan Internetdb

by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

TDQS

A4.8/5.0
Behavior5/5

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

Adds behavioral details beyond annotations: scoping by identifier, persistence for authenticated users vs 24-hour retention for anonymous sessions. Consistent with annotations (write, non-destructive, idempotent).

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

Conciseness5/5

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

Single concise paragraph that front-loads the main purpose, then provides usage guidance and behavioral details. Every sentence adds value without redundancy.

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

Completeness4/5

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

Given the simplicity of a key-value write tool and the presence of idempotentHint, the description covers the essential aspects (scope, persistence, companions). Does not specify return value, but that is acceptable for a write operation without output schema.

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 covers both parameters with descriptions. Description adds value by providing example keys (subject_property, target_ticker, user_preference) that clarify naming conventions, enhancing meaning beyond the 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?

Clearly states the tool saves data for reuse across conversations or sessions, with specific examples. Distinguishes from sibling tools recall and forget by naming them as complementary actions.

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 when you discover something worth carrying forward' and explains the benefit of not having to look it up again. Names recall and forget as partners, providing clear context for when to use this tool.

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

All Shodan Internetdb toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, ask_pipeworx_grounded and deep_research both answer grounded research questions, and bet_research, polymarket_edges, and polymarket_arbitrage all surface prediction-market opportunities. Long descriptions help, but the overlap creates real misselection risk, especially between the ask_pipeworx variants.

Naming Consistency4/5

Most tools follow a clear lowercase snake_case verb_noun or domain_verb pattern (lookup_ip, resolve_entity, validate_claim, list_subscriptions, generate_llms_txt). There are minor deviations like noun-first names (entity_profile, polymarket_edges, pipeworx_trending) and product-branded verbs (ask_pipeworx), but the overall style is consistent enough to predict behavior.

Tool Count2/5

32 tools is well over the 25-tool threshold where a tool set becomes hard to navigate, and the server named 'Shodan Internetdb' carries only one Shodan-related tool among dozens of Pipeworx, Polymarket, memory, and utility tools. The count reflects scope sprawl rather than a focused, coherent surface.

Completeness3/5

The broader inferred domain (structured data lookup, entity research, prediction markets, memory, subscriptions) is covered surprisingly well, with lifecycle tools for subscriptions and memory. However, there are notable gaps: no tool to fetch a pipeworx:// citation URI directly, no equivalent scan coverage for non-NPM ecosystems despite mentioning them, and the Shodan surface is minimal relative to the server name.

Resources