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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?

The description describes a mutation (mark_read:true flags events as read) while annotations declare readOnlyHint=true. This is a direct contradiction, as the tool modifies state via mark_read. The description adds other behavioral details (return payload structure) but the contradiction severely undermines transparency.

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 concise (three sentences) and front-loaded with the main action. Every sentence adds value, and there is no wasted text. The structure is efficient and easy to parse.

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?

The description explains what returned events contain (source, citation_uri, payload) and mentions mark_read behavior. It covers filtering and polling. However, it omits mention of the 'limit' and 'unread_only' parameters, though they are in the schema. With 5 parameters and no output schema, some missing context is acceptable but not fully complete.

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%, providing baseline 3. The description adds value by giving examples (e.g., 'sec_8k' for type, ISO timestamp for since) and explaining the effect of mark_read on subsequent calls, 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 the tool pulls fired events from the subscription feed, specifying the resource ('fired events') and the action ('pull'). It distinguishes itself from siblings like 'list_subscriptions' by focusing on alerts/events rather than subscription management.

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 about usage (polling works fine, alternative endpoint) but does not explicitly state when not to use this tool or compare it to siblings like 'list_subscriptions' or 'recent_changes'. However, the clarity of its purpose implies appropriate use cases.

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

B3.2/5.0
Disambiguation2/5

Many tools overlap in purpose (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research all route queries to structured data), and the set mixes Deezer music tools with an unrelated Pipeworx/Polymarket suite. An agent would struggle to pick the right tool for a given request.

Naming Consistency2/5

Naming is mixed: single-word nouns (album, artist, track, chart), verb_noun snake_case (list_subscriptions, resolve_entity), and verbose multi-concept names (scan_competitor_ai_presence, polymarket_kalshi_spread). No consistent pattern across the set.

Tool Count1/5

37 tools for a server named 'Deezer' is far beyond a music API scope; the overwhelming majority are unrelated data-research, prediction-market, and utility tools. This is an extreme mismatch between the server name and the tool surface.

Completeness2/5

For the Deezer music domain, the surface is incomplete (no playlists, user library, lyrics, or radio), while the many unrelated tools each cover only fragments of their domains. The overall set lacks coherent coverage of any single purpose.