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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).

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, openWorldHint, etc.), the description discloses that mark_read mutates read state, the feed is persisted, and the same data is available via a URL. This adds significant context about side effects and external access.

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?

Four sentences, front-loaded with the core purpose, and each sentence earns its place by adding return details, filtering options, side effects, or alternative access. No waste.

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

Completeness5/5

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

Given no output schema, the description covers return fields (source, citation_uri, payload), filtering, side effects, and alternate access. With all parameters already described in the schema, this is a complete and self-sufficient description for an agent.

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 parameters are already documented. The description enhances this with a concrete type example ('sec_8k'), explains ISO timestamps for since, and clarifies the effect of mark_read, adding meaning beyond the schema.

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 uses a specific verb ('Pull') and clearly identifies the resource ('fired events from your subscription feed'). It distinguishes from sibling tools like list_subscriptions by focusing on event alerts, not 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?

Provides clear usage guidance: explains filtering by type and since, describes mark_read behavior, and notes polling is fine. However, it does not explicitly compare to alternative MCP tools or state when not to use it.

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

Multiple tools have overlapping purposes, notably ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded which are near-identical in function. The polymarket_* family also has several members with closely related scopes, and the large number of data-query tools makes it hard to choose the right one without careful reading.

Naming Consistency3/5

All names use snake_case, but the pattern is inconsistent: some are verb-first (list_subscriptions, validate_claim), others are noun-first (entity_profile, bet_research), and proper-noun prefixes like pipeworx_ and polymarket_ are used liberally. The gitlab_* tools follow a clear verb_noun pattern, but the rest of the set is mixed.

Tool Count2/5

With 36 tools, the server is overloaded, especially given that only 5 are GitLab-related while the rest are a sprawling data-access toolkit. Many tools could be consolidated (e.g., the ask_pipeworx variants), and the count exceeds what is reasonable for a focused GitLab server.

Completeness2/5

For a server named Gitlab, the coverage is severely incomplete: only list/get operations exist for projects, issues, and MRs, with no create, update, or delete capabilities. The broader data tools are more complete, but the nominal purpose of the server is clearly not fulfilled.