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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

B3.4/5.0
Behavior1/5

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

The description explicitly states that setting mark_read:true 'flags returned events read' and affects subsequent calls, implying a state mutation. This directly contradicts the annotation readOnlyHint=true. Although the description adds useful return-format details, the contradiction is a serious inconsistency, warranting a 1 per the rubric. No other disclosure can mitigate this mismatch.

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 four sentences, front-loaded with the main purpose. It includes necessary examples and the alternative endpoint without excessive verbosity. It earns a 4 rather than 5 because the last sentence about the feed URL could be seen as slightly tangential for an agent using the tool, but it is still useful.

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 read-oriented tool with no output schema, the description adequately explains the return format (source, citation_uri, payload) and includes operational guidance (polling, endpoint). The lack of pagination details is minor given the schema's limit/default, and the contradiction with annotations lowers the overall completeness slightly, but the description alone is fairly comprehensive.

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%, so the baseline is 3. The description adds value beyond the schema by explaining the semantics of mark_read ('so the next call only shows newer ones') and giving an example type filter. It does not cover all params (e.g., unread_only), but the additional context for key parameters justifies a 4.

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 clearly states the tool's verb and resource: 'Pull fired events from your subscription feed.' It specifies the scope (recent alerts, persisted feed) and gives examples of filters. However, it does not explicitly differentiate from sibling tools like list_subscriptions, so it misses the 'distinguishes from siblings' bar for a 5.

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 clear context for use, including filtering options and the polling behavior ('Polls work fine'). It also offers an alternative for scripts/dashboards via the direct endpoint, giving the agent a decision point. However, it doesn't explicitly mention when not to use this tool or name sibling alternatives, so it falls short of a 5.

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

A3.6/5.0
Disambiguation2/5

The server name 'Dropbox' leads agents to expect file storage operations, but only 5 of 35 tools are Dropbox-specific. The majority are Pipeworx data lookup and prediction market tools, creating a confusing mismatch between server identity and toolset.

Naming Consistency2/5

Dropbox tools consistently use 'dropbox_verb_noun', but Pipeworx tools mix naming styles: some use 'verb_noun' like 'validate_claim', others use descriptive phrases like 'entity_profile' or 'recent_changes'. The overall set lacks a unified naming convention.

Tool Count2/5

35 tools is high, and the majority are unrelated to the server's name. The Dropbox subset alone is appropriately scoped with 5 tools, but the inclusion of 30 misc data tools makes the set feel bloated and unfocused for a server purportedly dedicated to Dropbox.

Completeness2/5

For the Dropbox domain, the tools cover only basic operations (create folder, download, list, search, metadata) missing update, delete, share. For the Pipeworx domain, the toolset is extensive, but the overall combination lacks completeness for any single coherent purpose.