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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

A4.3/5.0
Behavior4/5

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

Annotations indicate read-only and idempotent, but the description adds behavioral detail: marking events as read via mark_read parameter, and suitability for polling. 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.

Conciseness5/5

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

The description is concise with four sentences, front-loading the main purpose and covering key details without redundancy. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers return fields, filtering, mark_read, and polling advice. However, it omits the limit and unread_only parameters, which are present in the schema but not mentioned in the description, leaving some gaps for a tool with no output schema.

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?

The description adds meaning beyond the schema by explaining the mark_read behavior, giving an example for type filtering, and specifying ISO timestamp for since. Limit and unread_only are covered in schema but not reiterated.

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 tool pulls fired events from the subscription feed and returns most recent alerts. It specifies the resource and action, and distinguishes from sibling tools which cover different domains.

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 provides clear context on when to use the tool (polling) and mentions an alternative endpoint for scripts/dashboards. However, it does not explicitly compare to other tools like list_subscriptions.

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

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, though the three ask_pipeworx variants (standard, beta, grounded) are very similar, potentially causing confusion. The Polymarket and memory tool families are well-differentiated.

Naming Consistency5/5

All tool names use snake_case consistently, with a clear verb_noun pattern (e.g., resolve_entity, search_datasets, subscribe). No mixing of conventions.

Tool Count4/5

34 tools is high but justified given the breadth of the Pipeworx platform and Ukraine Open Data integration. The set covers a wide range of data sources and operations without feeling bloated.

Completeness4/5

The tool surface is thorough, covering querying, comparison, profiling, subscriptions, and memory. Minor redundancy in ask_pipeworx variants, but no significant gaps for the stated data-access purpose.