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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. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context: it explains that returned events can be marked read to affect subsequent calls, and that the feed is persisted. This goes beyond what annotations provide, earning a high score.

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 a single cohesive paragraph of five sentences, each serving a purpose. It is front-loaded with the primary action. While it lacks structural elements like bullet points, it remains concise and informative 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 lack of output schema, the description thoroughly explains the return fields (source, citation_uri, raw event payload). It covers all five parameters, notes the persistence of the feed, and provides alternative access. For a read-only polling tool with good annotations, this is a complete and self-contained description.

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 input schema has 100% description coverage, but the description adds value by elaborating on parameter semantics: e.g., 'mark_read:true to flag returned events read so the next call only shows newer ones' and 'Filter by type (e.g. "sec_8k")'. This enhances understanding beyond the schema's brief descriptions.

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 starts with 'Pull fired events from your subscription feed', which is a clear verb+resource pairing. It specifies the return fields and filtering options, making the tool's function unambiguous. However, it does not explicitly distinguish this tool from siblings like 'list_subscriptions' or 'subscribe', which could cause confusion.

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 that 'Polls work fine' and that the same feed is available via a direct API endpoint for scripts/dashboards, implying this tool is suitable for conversational polling. However, it does not provide explicit when-to-use guidance relative to sibling tools, nor does it exclude scenarios where other tools might be better.

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 heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same router, with the beta variant currently identical to stable. The five polymarket_* tools plus bet_research also blur boundaries, and discover_tools/suggest_questions both serve discovery. Detailed descriptions help, but an agent could easily select the wrong tool.

Naming Consistency3/5

All names use lower_snake_case and many follow a clear verb_noun pattern (resolve_entity, validate_claim, generate_llms_txt). However, there are notable deviations: entity_profile, pipeworx_feedback, polymarket_edges, recent_changes, and bet_research lead with nouns or adjectives. The style is readable and predictable in clusters, but not uniform.

Tool Count2/5

32 tools is well above the 25+ threshold for 'too many', and the server name Macvendors suggests a narrow MAC-lookup service, yet most tools belong to a much broader Pipeworx data/prediction-market platform. Several tools are near-duplicates or micro-variants (three ask_pipeworx versions, six polymarket tools). The set would be more appropriately split or heavily consolidated.

Completeness4/5

Within the actual broad research platform domain, the surface is fairly complete: discovery, routing, grounded answers, entity profiles, comparisons, recent changes, claim validation, semantic search, prediction-market analysis, subscriptions, memory, and feedback are all covered. Minor gaps exist, such as no subscription update tool and no batch MAC lookup, but agents can generally complete workflows without dead ends.