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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

A3.7/5.0
Behavior1/5

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

The description discloses a side effect: 'Set mark_read:true to flag returned events read so the next call only shows newer ones,' which changes persistent feed state. This directly contradicts the annotations' readOnlyHint=true. The contradiction is a serious inconsistency, so the score is 1.

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 front-loaded with the core purpose and then covers return items, filtering, mark_read, polling, and an alternate endpoint. It is about five sentences and each adds useful information, though the external URL could be considered slightly tangential. No bloat, so 4.

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 return contents (source, citation_uri, raw payload), filter options (type/since), the mark_read side effect, and polling suitability. It also points to a public feed URL. While it doesn't explicitly describe the exact response shape, no output schema exists, and the listed info is sufficient for practical use. Minor gaps like unread_only/limit are covered by the schema, so 4.

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 input schema already covers all parameters with descriptions, so baseline is 3. The tool's description adds value by giving a concrete type example ("sec_8k"), clarifying that 'since' takes an ISO timestamp, and explaining the behavior of mark_read. These enrich the parameter semantics 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 opens with 'Pull fired events from your subscription feed,' which clearly states the tool's specific action and resource. It also distinguishes itself from siblings like list_subscriptions and recent_changes by focusing on fired alerts and the evaluator's feed.

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 when to use the tool: for polling the feed, filtering by type/since, and marking events read. It also mentions an alternative URL for scripts/dashboards. However, it does not explicitly name alternatives among sibling tools or specify when not to use it, stopping 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

A3.5/5.0
Disambiguation1/5

Several tools are effectively indistinguishable or near-duplicates: ask_pipeworx_beta is explicitly an identical copy of ask_pipeworx with no active experimental changes, and ask_pipeworx_grounded is a variant of the same router. discover_tools, suggest_questions, deep_research, and the ask_pipeworx family also heavily overlap as discovery/answer surfaces, while bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_fill_risk create a dense prediction-market cluster with fuzzy boundaries.

Naming Consistency3/5

Everything is snake_case and many names follow a readable verb_noun pattern (search_works, resolve_entity, validate_claim, suggest_questions), but conventions are mixed: noun-first domain-prefixed names (polymarket_edges, pipeworx_feedback, pipeworx_trending), bare verbs (remember, forget, recall), and adjective_noun names (deep_research, recent_changes) coexist. The inconsistency is not chaotic, but it is not a unified scheme.

Tool Count2/5

36 tools is well over the 25-tool threshold for a heavy toolset, and the count is inflated by many tangential concerns: memory, subscriptions, feedback, trending, npm dependency scanning, AI visibility, and llms.txt generation. Only a small subset actually serves the stated OpenAlex/scholarly purpose, so the size feels bloated rather than well-scoped.

Completeness2/5

For a server named openalex, the scholarly surface is incomplete: works support search and fetch, but authors and institutions only support search with no get-by-ID, concepts support get but no search, and major OpenAlex resource types like sources, publishers, funders, and topics are absent. The many non-OpenAlex tools do not fill these gaps and instead dilute the domain coverage.