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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. First observed

TDQS

A3.7/5.0
Behavior1/5

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

The annotations declare readOnlyHint=true and idempotentHint=true, but the description states 'Set mark_read:true to flag returned events read so the next call only shows newer ones,' which is a state-changing side effect. This directly contradicts the read-only hint, making the behavioral guidance misleading for an agent.

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 moderately concise; it front-loads the purpose and packs useful behavior into a few sentences. The final sentence about the alternative URL is slightly tangential but still valuable for scripts/dashboards.

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 5 optional parameters and no output schema, the description covers return fields, filtering, and polling semantics. The mark_read behavior and persistent feed context give an agent enough to invoke correctly, though the annotation contradiction undermines full reliability.

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 5 parameters with descriptions, so the baseline is 3. The description adds meaningful nuance: an example type ('sec_8k'), the combination of type and since filters, and the side-effect explanation for mark_read. It does not mention limit or unread_only, but those are adequately covered in 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,' a specific verb+resource statement that clearly identifies the tool's function. It further details what is returned (source, citation_uri, raw payload) and distinguishes it 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 gives clear usage context: it explains filtering by type/since, the mark_read behavior, and that polling works fine. It also notes an alternative HTTP endpoint for scripts/dashboards, which is a form of alternative, but does not explicitly contrast with sibling tools or state when not to use this tool.

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 tool set mixes general-purpose Pipeworx tools (ask_pipeworx, ai_visibility_check, bet_research) with only three paleontology-specific tools (find_fossils, get_taxon, list_subtaxa). Multiple similar 'ask_pipeworx' variants further blur distinctions, making it difficult for an agent to select the right tool without deep domain knowledge.

Naming Consistency3/5

Tool names are mostly in snake_case and somewhat descriptive, but the naming conventions vary widely: imperative verbs (find_fossils), interrogative (suggest_questions), and nouns (recent_alerts). The presence of multiple 'ask_pipeworx' variants with inconsistent suffixes (beta, grounded) adds confusion.

Tool Count2/5

With 34 tools, the server is oversized for its claimed paleontology focus. The vast majority of tools are unrelated to Paleobiology, making the server feel more like a general-purpose data API than a specialized paleontology tool. A focused server should have a smaller, targeted set.

Completeness2/5

For the Paleobiology Database purpose, the coverage is severely lacking: only three tools are directly relevant (find_fossils, get_taxon, list_subtaxa). Missing essential operations like searching taxa by name, retrieving occurrences by location, or accessing collections data. The tool set is not a coherent interface for the domain.