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Nist Standards

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

A4.9/5.0
Behavior5/5

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

Annotations show it is read-only, open-world, idempotent, and non-destructive. The description adds that it returns dynamically drawn example questions from a live catalog, which is consistent and provides extra behavioral context.

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 front-loaded with the core purpose and well-structured, but slightly verbose with examples. Could be trimmed without losing clarity, but still effective.

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 tool's simple purpose as an onboarding helper, the description covers everything: when to use, how to use, what it returns (category-bucketed examples). No output schema, but the description sufficiently explains the return value.

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?

Only one optional parameter with 100% schema coverage. The description adds a list of valid topics (finance, pharma, etc.) that are not in the schema as enums, and explains the effect of omitting the parameter.

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 clearly states it is the onboarding entry point for an agent wanting to know what it can ask. It lists example queries and specifies it returns category-bucketed example questions with tool calls. This distinguishes it from sibling tools like ask_pipeworx.

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?

The description explicitly says to use this tool FIRST when you do not know what Pipeworx can do, and to learn meta-tools. It also explains how to use it: no arguments for full spread, or with topic for focus.

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

A4/5.0
Disambiguation3/5

Most tools have distinct purposes, but several clusters overlap: ask_pipeworx_beta is currently identical to ask_pipeworx, polymarket_arbitrage and polymarket_edges both surface arbitrage opportunities, and validate_claim overlaps with ask_pipeworx_grounded. Descriptions mitigate some confusion, but selection errors are still likely.

Naming Consistency4/5

Names are overwhelmingly lowercase snake_case and descriptive, such as nist_control_family, polymarket_fill_risk, and list_subscriptions. Minor deviations exist with single-word memory verbs like remember/recall/forget and the ask_pipeworx_* variants, but the overall pattern is predictable and readable.

Tool Count2/5

34 tools is well above the comfortable range and includes many tools unrelated to the server's NIST Standards name, such as Polymarket betting, npm dependency scanning, AI visibility checks, and llms.txt generation. The set feels like a broad general-purpose data platform rather than a scoped NIST reference server.

Completeness3/5

For the NIST domain, the three control tools provide id lookup, family listing, and keyword search, but there is no catalog overview or family enumeration, and no comparison, revision, or export capability. The other 31 tools do not fill those gaps, so the NIST surface is functional but not fully complete for compliance workflows.

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