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Nist Standards

by io.github.pipeworx-io

Search Within a Source

search_within
Read-onlyIdempotent

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe document text to search inside (max ~200K chars).
limitNoMax passages to return (1-20, default 5).
queryYesNatural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".

TDQS

A4.9/5.0
Behavior5/5

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

Despite annotations already indicating safe and idempotent behavior, description adds rich details: returns top-N passages with offsets and scores, embedding model (BGE-base-en), cosine similarity, overlapping 500-char windows, 200K char cap with truncation flag. No contradiction with 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?

Well-structured and front-loaded with purpose, then usage, then technical details. Every sentence is informative, though slightly lengthy; could be tightened slightly without losing value.

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 sufficiently explains return format (passages with offsets and scores). Covers behavior, constraints, and pairing with another tool. Complete for an agent to decide and invoke.

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 100%, but description adds value by explaining 'text' with examples (SEC 10-K body), 'query' as natural-language with examples, and 'limit' default 5. Goes beyond schema descriptions.

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?

Description clearly states 'semantic search INSIDE a fetched record' with specific verb and resource. Provides concrete examples (SEC 10-K, article) and distinguishes itself from siblings by emphasizing internal search and pairing with ask_pipeworx_grounded.

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 when to use: 'Use when the record is too big to cram into the prompt.' Also explains alternative: 'Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document.'

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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