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Glama

Skiddle

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. First observed

TDQS

A3.8/5.0
Behavior1/5

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

The description contradicts the readOnlyHint annotation by describing the mark_read parameter, which modifies state (flags events as read). While the description is transparent about this behavior, the contradiction reduces reliability. Score 1 per rubric for contradiction.

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 four sentences, front-loaded with the main purpose, and every sentence adds distinct value (return format, filtering, mark_read effect, alternative access). No redundant or wasted words.

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 five parameters, no output schema, and good annotations, the description covers return format, filtering, mark_read behavior, and an alternative endpoint. However, the contradiction with readOnlyHint slightly undermines completeness for agents interpreting the tool's safety profile.

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 schema has 100% coverage with descriptions for each parameter. The description adds value by providing examples (e.g., 'sec_8k' for type), specifying ISO timestamps, and explaining the effect of mark_read (next call shows newer events). This is more than the baseline of 3.

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 the tool pulls fired events from a subscription feed, specifies what each alert carries (source, citation_uri, payload), and outlines filtering options (type, since). It is a specific verb-resource pair with concrete details, distinguishing it from generic tools.

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 provides context for usage, mentioning that polls work fine and that the same feed is accessible via HTTP for scripts/dashboards. It does not explicitly differentiate from sibling tools like search_events, but the filtering and mark_read behavior imply typical use cases for recent alerts.

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

Most tools have clearly distinct roles, but the ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded / deep_research cluster overlaps heavily as question-answering and research entry points, with ask_pipeworx_beta currently being an exact duplicate of ask_pipeworx. The prediction-market tools are individually differentiated but numerous enough that selecting the right one requires careful reading.

Naming Consistency4/5

The set is predominantly snake_case and mostly readable, with sensible prefixes like ask_, search_, polymarket_, and scan_. However, conventions mix verb-first names (remember, subscribe, validate_claim), noun-style names (categories, event, entity_profile), and adjective-noun names (recent_alerts, recent_changes), so the pattern is not fully uniform.

Tool Count2/5

34 tools is well above the 25-tool threshold where a server starts to feel heavy, and many could be consolidated (7+ prediction-market tools, 4+ overlapping ask/research tools, plus memory and subscription helpers). The breadth is somewhat justified by the Pipeworx data platform, but the surface is still overloaded for a single server.

Completeness4/5

For the broad data/research domain, coverage is strong: lookup, grounded verification, deep research, entity profiles, comparisons, change feeds, tool discovery, memory, and subscription lifecycle all have coherent coverage. Minor gaps exist, such as no explicit tool to read a pipeworx:// citation URI directly and a fairly thin Skiddle events side beyond search/detail/categories.

Resources