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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

A3.8/5.0
Behavior1/5

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

Annotations declare readOnlyHint=true and idempotentHint=true, but the description explicitly says setting mark_read:true will mark events as read, indicating a state change. This contradicts the readOnlyHint annotation. The description also mentions mark_read as a parameter but does not resolve the 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 efficient and front-loaded with the core purpose. Each sentence adds meaningful information (e.g., what events carry, filtering options, mark_read behavior, alternative endpoint). It is not overly verbose, but could be slightly tighter.

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 no output schema, the description tells the agent what fields to expect (source, citation_uri, raw event payload). It explains filtering, mark_read behavior, and even provides an alternative REST endpoint. This is comprehensive for a read-focused 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?

All parameters have schema descriptions, and the tool description adds extra context for 'type' (example value 'sec_8k'), 'since' (ISO timestamp format), and 'mark_read' (explains its effect). The explanation of 'mark_read' and 'since' goes beyond the schema. However, 'limit' and 'unread_only' are not elaborated further.

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 begins with a specific verb and resource: 'Pull fired events from your subscription feed.' It clearly states the tool retrieves recent alerts and explains what each event carries (source, citation_uri, payload). This differentiates it from sibling tools like list_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 fine and points to an external alternative endpoint for scripts and dashboards. However, it does not explicitly state when to use this tool versus other PipeWorx tools or when not to use it.

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

A3.7/5.0
Disambiguation3/5

Most tools have distinct, well-documented roles, but the set includes two effectively identical routers (ask_pipeworx and ask_pipeworx_beta, with the latter explicitly matching the former right now) and a dense cluster of six Polymarket tools that an agent must read carefully to choose among. This is more than a minor overlap, though the detailed descriptions prevent it from being complete chaos.

Naming Consistency3/5

Everything is snake_case, which is a plus, but the patterns are inconsistent: some tools are verb_noun (resolve_entity, validate_claim, list_subscriptions), some are noun phrases (entity_profile, bet_research, recent_alerts), some use brand prefixes (ask_pipeworx*, polymarket_*, pipeworx_*), and take_the_meeting_evaluate is a sentence-like outlier. The prefixes do provide grouping, but the naming doesn't give a predictable action structure.

Tool Count2/5

32 top-level tools is above the 25+ threshold and will bloat an agent's tool-selection surface, especially because the server name 'Take The Meeting' suggests a narrow meeting tool while 31 of the tools are unrelated Pipeworx/data features. Even as a broad data-research server, several tools could be collapsed (the ask variants, the Polymarket family), so the count feels inflated.

Completeness2/5

For the purpose implied by the server name and the lone meeting tool, the surface is severely incomplete: there is no way to list or fetch meetings, access calendar/attendee context, or do anything beyond evaluating one set of supplied parameters. For the broad data-research domain that most tools actually serve, the read/research side is rich, but that is a completely different purpose from 'Take The Meeting', leaving the meeting feature as a disconnected dead end.