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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

A3.8/5.0
Behavior1/5

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

The description discloses that setting 'mark_read:true' flags returned events as read, modifying state. This contradicts the annotation 'readOnlyHint: true', which implies no state changes. The contradiction is a serious inconsistency.

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?

The description is somewhat lengthy but well-structured, front-loading the purpose and covering return fields, parameters, and usage notes. Each sentence adds information, though some detail could be trimmed.

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 specifies return fields (source, citation_uri, raw event payload) and covers all parameters, polling behavior, and an alternative access method. No obvious gaps exist for this list-type tool.

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 for all 5 parameters. The description adds value by explaining 'since' requires ISO timestamp and elaborating on 'mark_read' behavior, enriching the schema's default explanations.

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 retrieves fired events from a subscription feed, using specific verb 'Pull' and resource 'fired events'. It distinguishes itself from siblings like 'list_subscriptions' by focusing on events rather than subscriptions.

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 mentions polling works and points to an alternative endpoint (alerts.json) for scripts/dashboards, providing some usage context. However, it does not explicitly contrast with sibling tools or state when not to use this tool.

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
Disambiguation5/5

Each tool has a clearly defined, distinct purpose. Even closely related tools like ask_pipeworx and ask_pipeworx_grounded are differentiated by use case (casual vs. high-stakes), and the prediction market tools each cover a specific function (research, edge detection, arbitrage, fill risk, tracking, cross-venue spreads). Detailed descriptions eliminate ambiguity.

Naming Consistency4/5

Tool names predominantly follow a verb_noun pattern (e.g., ask_pipeworx, compare_entities, resolve_entity), but a few use noun_noun or adjective_noun forms (e.g., entity_profile, recent_alerts). The naming is generally predictable and readable, with minor deviations from a strict pattern.

Tool Count3/5

The server offers 32 tools, which is above the typical 3-15 range for a well-scoped server. However, the vast domain (financials, prediction markets, news, memory, subscriptions, etc.) justifies the count. It is on the heavy side but still manageable with clear organization.

Completeness5/5

The tool surface is remarkably complete for the apparent domain: exploration (discover_tools, suggest_questions), identifier resolution (resolve_entity), data retrieval (ask_pipeworx, deep_research, entity_profile, compare_entities, recent_changes, validate_claim), prediction market analysis (full suite), memory (remember/recall/forget), subscriptions (subscribe/unsubscribe/list/recent_alerts), and extras (ENS, dependency scan, AI visibility). No obvious gaps exist.

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