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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).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A3.9/5.0
Behavior1/5

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

The description discloses a state-changing side effect: 'Set mark_read:true to flag returned events read so the next call only shows newer ones.' This contradicts the annotations' readOnlyHint: true, which claims the operation is read-only. As a result, the description directly contradicts the provided annotation.

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 three sentences, front-loaded with the purpose, followed by return details/filtering and an alternative access point. Every sentence contributes essential information without redundancy.

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?

Given the five optional parameters are fully described in the schema and annotations cover safety hints, the description adds the remaining needed context: return payload structure, side-effect behavior of mark_read, and external access for scripts/dashboards. It is complete for an agent to select and invoke the tool correctly.

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%, but the description adds meaning beyond the schema by explaining the effect of mark_read (future calls return only newer events) and providing a concrete type example ('sec_8k'). This enriches the understanding of the type and mark_read parameters.

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 opens with 'Pull fired events from your subscription feed,' a specific verb+resource that clearly identifies the tool's function. It also lists return fields (source, citation_uri, payload) and filtering options, which distinguishes it from siblings like list_subscriptions (which manage subscriptions) and recent_changes (which may show changes to other resources).

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 frames the tool for polling alerts and provides an explicit alternative access method ('the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards'). However, it does not contrast this tool with sibling read tools like recent_changes, so it gives context but no exclusions.

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

A3.9/5.0
Disambiguation2/5

Several tool groups have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, polymarket_edges/arbitrage/bet_research overlap heavily, and scan_competitor_ai_presence merely wraps ai_visibility_check. An agent would frequently have to guess which of several overlapping tools to call.

Naming Consistency3/5

Most tools use lowercase snake_case, but the set mixes verb-first names (resolve_entity, validate_claim) with noun/service-first compounds (polymarket_edges, pipeworx_trending, ai_visibility_check) and inconsistent suffix semantics (ask_pipeworx_beta vs ask_pipeworx_grounded). The pattern is readable but not predictable.

Tool Count2/5

33 tools is far too many for a server named iplookup; only 2 of 33 relate to IP geolocation. The rest form a sprawling data/prediction-market/memory platform that would be better split into multiple focused servers.

Completeness4/5

Within the actual described scope (a Pipeworx data platform), coverage is strong: routed lookups, grounded verification, deep research, entity identity/profile/comparison, claim validation, discovery, subscriptions, memory, feedback, trending, and a full prediction-market arbitrage suite. Minor gaps exist (no direct pack-listing tool, no update for memory values), but there are no critical dead ends.