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Nyt

by io.github.pipeworx-io

Top Stories

top_stories
Read-onlyIdempotent

Get current New York Times top stories for a section (home, world, business, technology, science, health, sports, arts, etc.). Returns titles, abstracts, bylines, and URLs. Example: top_stories({ section: "technology" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyNoOptional — your own NYT API key for higher limits; omit to use the shared Pipeworx key.
sectionNoSection name, e.g. "home", "world", "business", "technology", "science", "health", "sports", "arts". Default "home".

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already provide comprehensive behavioral hints (readOnly, openWorld, idempotent, non-destructive). The description adds the fact that an API key can be optionally overridden, but does not disclose further behaviors like rate limits or pagination. With strong annotation coverage, the description adds modest value.

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?

The description is two sentences with an inline example, front-loading the purpose and key parameters. Every sentence adds value with no filler. The structure is efficient and easy to parse.

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?

Even without an output schema, the description specifies the return fields (titles, abstracts, bylines, URLs), covering essential context. Parameters are fully documented and the example clarifies usage. The tool is simple and the description is complete.

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%, so baseline is 3. The description adds meaningful context beyond the schema: it provides a usage example, notes the default section, and explains the optional API key parameter. This extra semantic depth earns a 4.

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 the verb 'Get', the resource 'New York Times top stories', and the scope 'for a section'. It lists the return fields and provides an example, making the purpose unmistakable. It also implicitly distinguishes from sibling tools like 'search_articles' or 'movie_reviews'.

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

Usage Guidelines3/5

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

The description implies usage for fetching top stories by section but does not explicitly state when to use this tool versus alternatives. It lacks guidance on excluded cases or comparisons to siblings, leaving the agent to infer context from the description alone.

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