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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

A4.2/5.0
Behavior4/5

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

The description enriches the read-only annotation by describing the persistent feed, the evaluator's role, and the mark_read side effect that affects subsequent calls. It also mentions polling suitability, adding operational context beyond the 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?

The description is concise and well-structured, with each sentence covering a distinct aspect: core function, return payload, filters, mark_read behavior, and alternative endpoint. There is no redundant or vague language.

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?

The description fully covers return values, filtering, mark_read behavior, and polling suitability, which compensates well for the lack of an output schema. Remaining parameters are documented in the schema, making the overall guidance 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?

The schema already covers all five parameters with 100% coverage, so the baseline is 3. The description adds value by explaining the effect of mark_read on the next call and highlighting the type and since filters, going beyond the schema descriptions.

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 pulls fired events from the user's subscription feed and returns the most recent alerts with source, citation_uri, and raw payload. It is specific about the resource and action, but it does not explicitly distinguish itself from sibling tools like recent_changes.

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 gives clear context: it says polling works fine and notes an alternative GET endpoint for scripts/dashboards. However, it does not provide explicit exclusions or compare against sibling tools with overlapping functionality.

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

A3.8/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve queries, with ask_pipeworx_beta explicitly identical to ask_pipeworx. Prediction-market tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, bet_research, etc.) also have unclear boundaries, making tool selection tricky for an agent.

Naming Consistency4/5

Tool names are consistently lowercase snake_case with a mostly verb-first pattern (get_work, search_works, list_subscriptions, validate_claim). Minor deviations exist: some names are noun-first (entity_profile, recent_changes) and prefixes vary (get/search/list/ask/scan), but the overall convention is predictable and readable.

Tool Count2/5

34 tools is far too many for a server named 'crossref', and only three tools actually relate to Crossref. The rest form a sprawling utility belt covering data routing, memory, subscriptions, prediction markets, AI visibility, and npm scanning — a scope mismatch that makes the server feel like a kitchen sink rather than a focused offering.

Completeness2/5

The Crossref-specific surface is thin: search_works, get_work, and get_journal cover discovery and metadata but lack citation lookup, author search, and funder information. The broader Pipeworx surface is extensive but has no unifying domain, so it's impossible to consider the overall toolset complete for any coherent purpose.