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uooks

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).

Schema Changelog

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

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial context beyond annotations: describes the payload structure ('source, citation_uri... raw event payload'), explicitly discloses that mark_read:true flags events read and affects subsequent calls, and notes the feed is persisted and also available via HTTP. This goes well beyond the readOnlyHint/idempotentHint 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?

Three compact sentences: purpose, return contents, filtering, mark_read effect, and polling/alternative access. Every sentence earns its place, with no fluff or redundancy. Front-loaded with the core action.

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?

Given no output schema, the description adequately explains what events carry and how filters work. It also covers side effects and alternative access. Missing details like pagination or default limit are already in the schema, so the overall context is sufficient for a read 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 covers all parameters (100%), but the description adds value with a concrete type example ('sec_8k'), clarifies that 'since' is an ISO timestamp, and explains the real-world consequence of mark_read (next call only shows newer ones). This enriches the schema descriptions, though limit and unread_only are not mentioned.

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 starts with a specific verb+resource: 'Pull fired events from your subscription feed.' It clearly distinguishes this tool from siblings like list_subscriptions or recent_changes by focusing on the persisted alert feed and the evaluator's events.

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?

Provides clear usage context: 'Filter by type (e.g. "sec_8k") and/or since (ISO timestamp)' and explains mark_read behavior for polling. It also mentions an alternative endpoint for scripts/dashboards, effectively indicating when to use this tool vs. an HTTP feed, though it doesn't explicitly name sibling alternatives.

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

A4.1/5.0
Disambiguation3/5

Several tool families overlap at the boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to the same 5,724 tools, and ask_pipeworx_beta is currently functionally identical to ask_pipeworx. The Polymarket family is large but each member has a fairly distinct role (research vs. edge scan vs. fill risk vs. tracking); the memory trio and book tools are clear.

Naming Consistency3/5

Most tools follow a snake_case verb_noun pattern (get_book, create, search_books, resolve_entity, list_subscriptions), but there are notable exceptions: recall/remember/forget are bare verbs without a domain prefix, ask_pipeworx begins with a verb but doesn't follow the noun-object structure, and ai_visibility_check/generate_llms_txt break the pattern. It's readable and mostly predictable, but not uniform.

Tool Count3/5

35 tools is heavy and exceeds the typical well-scoped range, but the server is a meta-platform exposing a universal data router plus prediction-market analysis, book lookup, memory, subscriptions, and several composite research tools. Each tool appears to earn its place, though the set feels sprawling and would benefit from consolidation of the ask_pipeworx variants.

Completeness4/5

Coverage is thorough within the apparent domains: data lookup has multiple tiers (casual, grounded, deep research, claim validation), the Polymarket workflow is complete from research to edge discovery to fill-risk verification, memory has save/retrieve/delete, and subscriptions have create/list/cancel/pull. Minor gaps exist (e.g., book author search by name only via Open Library key, no direct tool for invoking a specific raw data pack), but nothing that would strand an agent.

Resources