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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

A4.4/5.0
Behavior4/5

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

Annotations provide strong behavioral hints (readOnly, idempotent, openWorld). The description adds important context: the mark_read parameter causes side effects by flagging events as read, and that polling is acceptable. It does not contradict 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 three sentences long, front-loaded with the core purpose, and each sentence adds a distinct piece of information (what it returns, how to filter, mark_read behavior, alternative access). No extraneous content.

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

Completeness4/5

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

For a tool with 5 optional parameters, no required fields, and no output schema, the description covers the return format, filtering options, mark_read behavior, and alternative access. It lacks an explicit mention of ordering (e.g., most recent first), which would enhance completeness.

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 individual parameter descriptions. The description adds value by providing examples (e.g., type 'sec_8k') and clarifying the effect of mark_read and since filters, which goes beyond the schema descriptions.

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 it pulls fired events from a subscription feed and returns recent alerts with source, citation URI, and payload. This verb+resource specification is distinct from sibling tools like list_subscriptions or subscribe, which serve different purposes.

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 notes that polling works fine and points to an alternative API endpoint for scripts/dashboards, giving context on when to use this tool vs an HTTP request. However, it does not explicitly exclude cases or compare with other tools like search_within.

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
Disambiguation3/5

The three ask_pipeworx variants plus deep_research and validate_claim overlap heavily on the same routing capability — ask_pipeworx_beta is even explicitly identical to ask_pipeworx right now. The polymarket tools (arbitrage/edges/edge_tracker/fill_risk/kalshi_spread) form a second cluster with fuzzy boundaries, and ai_visibility_check vs scan_competitor_ai_presence overlap. However, most other tools (w3c_search, spec, remember/recall/forget, subscribe/unsubscribe) have clear distinct roles.

Naming Consistency3/5

Names are generally descriptive snake_case with recognizable prefix families (ask_pipeworx_*, polymarket_*, w3c_*), but verb usage is inconsistent: passive labels like ai_visibility_check and entity_profile sit alongside imperatives like recall, forget, subscribe, and resolve_. There's no uniform verb_noun or noun_pattern convention across the set.

Tool Count2/5

33 tools is over the heavy threshold, and the count is wildly mismatched to the server's claimed identity: the server is named 'W3c' yet only 2 of 33 tools (w3c_search, w3c_spec) relate to W3C. The remaining 31 form a sprawling Pipeworx data/prediction-market service that would justify its own server, making this aggregation incoherent.

Completeness3/5

For its actual purpose (broad data research + prediction markets), the surface is fairly complete: search, grounded answers, deep research, comparison, entity profiles, entity resolution, memory, subscriptions, and feedback cover the main workflows. But for the server's stated W3C purpose, only search and spec-detail exist with no broader standards tooling. The domain mismatch makes completeness hard to credit.