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Data Usdot

by io.github.pipeworx-io

Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. The description adds important behavioral details: return fields (source, citation_uri, raw payload), filtering options, and mark_read behavior. No contradictions 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.

Conciseness5/5

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

The description is concise with four sentences, front-loading the core purpose. Every sentence adds value, no redundancy. Well-structured for quick parsing.

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?

Despite no output schema, the description explains what the tool returns (source, citation_uri, raw payload). It also mentions polling suitability and an alternative access method. Combined with rich annotations, the description is self-sufficient.

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% with descriptions. The description adds context beyond schema by explaining the filtering purpose with examples ('e.g. "sec_8k"') and the effect of mark_read. This enhances usability.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Pull fired events from your subscription feed' and lists key fields returned. However, it does not explicitly differentiate from siblings like 'list_subscriptions' or 'subscribe', though the resource and action are distinct enough.

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 mentions 'Polls work fine' and gives an alternative REST endpoint, but does not specify when to use this tool vs. alternatives or when not to use it. The usage guidance is implicit rather than explicit.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping or near-identical purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are one base query flow with different flavors, while entity_profile, compare_entities, and recent_changes all overlap on company information. The Polymarket family and the discovery/onboarding tools (discover_tools, suggest_questions, pipeworx_trending) also create boundary confusion despite good descriptions.

Naming Consistency3/5

The naming is consistently snake_case and mostly readable, but it mixes verb_noun tools (compare_entities, resolve_entity, validate_claim) with noun-phrase tools (entity_profile, polymarket_arbitrage, pipeworx_trending, datasets, metadata). The ask_pipeworx variants use a beta/grounded suffix pattern that is not applied uniformly across the other tool families.

Tool Count2/5

34 tools is well above the 25+ threshold and feels like several servers merged into one: US DOT catalog access, a generic Pipeworx data router, prediction-market tools, memory/subscription management, AI-visibility checks, and meta/discovery utilities. Many tools could be consolidated (the three ask_pipeworx variants, the five Polymarket tools, and the discovery trio).

Completeness3/5

The core data lifecycle is broadly covered: catalog search, metadata, querying, natural-language lookup, grounded verification, entity resolution, entity profiles, comparison, research, subscriptions, and memory all have working paths. However, the server is named around US DOT data but only datasets/metadata/query are DOT-specific, and the rest is an unrelated general-purpose data and prediction-market toolkit, leaving the stated domain feeling incomplete.

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