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Nyt

by io.github.pipeworx-io

Search Articles

search_articles
Read-onlyIdempotent

Full-text search of New York Times news articles. Returns headlines, abstracts, sections, bylines, and URLs. Example: search_articles({ query: "artificial intelligence", sort: "newest" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoResult page (0-indexed, 10 results per page). Default 0.
sortNoSort order for results. Default "newest".
queryYesSearch query — keywords or phrase to search New York Times articles for.
_apiKeyNoOptional — your own NYT API key for higher limits; omit to use the shared Pipeworx key.
begin_dateNoEarliest article date in YYYYMMDD format, e.g. "20240101" (optional).

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is clear. The description adds value by specifying what fields are returned (headlines, abstracts, etc.) and providing an example call, but does not disclose rate limits or pagination limits beyond what the schema provides.

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?

Description is extremely concise with one sentence and one example. It is front-loaded with the core purpose, and every element is informative. No wasted words.

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 tool has comprehensive annotations and a fully described schema, the description is complete enough for a search tool. It covers what the tool does and what it returns, though it does not explain pagination or result limits beyond what is in the schema.

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

Parameters3/5

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

Schema description coverage is 100%, so baseline is 3. The description does not add additional meaning to parameters beyond what is in the schema; the example merely illustrates usage but does not clarify semantics further.

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 explicitly states 'Full-text search of New York Times news articles', providing a specific verb and resource. It distinguishes from siblings like top_stories and movie_reviews by focusing on full-text search rather than curated lists or reviews.

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

Usage Guidelines4/5

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

The description clearly implies when to use: when a full-text search across NYT articles is needed. An example is provided, but no explicit when-not-to-use or alternatives are stated, though the tool's purpose is sufficiently clear for an AI agent.

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

A3.6/5.0
Disambiguation2/5

ask_pipeworx and ask_pipeworx_beta are explicitly identical today, and ask_pipeworx_grounded, deep_research, and validate_claim all route to the same underlying sources with overlapping question-answering purposes. Entity-focused tools like entity_profile, compare_entities, recent_changes, and resolve_entity also have fuzzy boundaries that make selection error-prone.

Naming Consistency2/5

Names mix conventions: verb_noun (list_subscriptions, search_articles, generate_llms_txt), bare verbs (remember, recall, forget), noun phrases (polymarket_arbitrage, pipeworx_trending, entity_profile), and an ask_* family with beta/grounded variants. There is no consistent verb or noun pattern across the set.

Tool Count2/5

With 35 tools, the surface is well above the 15-tool threshold for a focused server, and most tools are unrelated to the NYT domain implied by the server name. The breadth reflects a broad data-platform grab bag rather than a scoped, intentional tool set.

Completeness4/5

The query side is unusually complete: single-lookup, grounded lookup, deep research, claim validation, entity resolution, comparison, profile, change-feed, discovery, memory, and subscription lifecycle tools are all present. Minor gaps remain, such as no direct NYT article fetch by URL and no update path for stored memories, but agents can work around them.

Resources