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Semrush

by io.github.pipeworx-io

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

A4.8/5.0
Behavior5/5

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

The description adds significant behavioral context beyond annotations: it explains the side-effect of mark_read, confirmsa idempotency through polling advice, and details return fields. No contradiction with 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 a single efficient paragraph, front-loaded with purpose, then return fields, filters, side-effect, and finally alternative access. Every sentence adds value, no fluff.

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?

For a read-only query tool with 5 optional parameters and no output schema, the description covers return fields, all parameter behaviors, polling safety, and an alternative endpoint. This is complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds meaningful context for each parameter: gives examples for type ('sec_8k'), explains ISO format for since, clarifies mark_read effect and unread_only behavior, plus default values for limit.

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 clearly states the tool pulls fired events from the user's subscription feed, using specific verb+resource. It distinguishes from sibling tools like 'list_subscriptions' by focusing on events/alerts 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 provides good usage context, including polling suitability and an alternative URL for scripts/dashboards. However, it doesn't explicitly compare to other sibling tools or state when not to use this tool, leaving some gaps.

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

A4.1/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there is some overlap: ask_pipeworx and ask_pipeworx_grounded are very similar, and the multiple Polymarket tools could be confused. The memory tools (remember, recall, forget) are distinct.

Naming Consistency3/5

Tool names consistently use snake_case, but the pattern is not strictly verb_noun. Some names are descriptive phrases (e.g., scan_competitor_ai_presence), while others are straightforward (e.g., keyword_overview). Overall readable but not highly consistent.

Tool Count3/5

32 tools is on the high side for a single server, but the scope is broad (SEO, finance, FDA, betting, memory). The tool count feels slightly excessive, yet each tool appears justified by its specific use case.

Completeness4/5

The tool set covers a wide range of business research needs: SEO, SEC filings, FDA data, betting analytics, and memory. Minor gaps exist (e.g., no direct social media or HR data), but the coverage is impressive for a general-purpose data server.

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