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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

A3.8/5.0
Behavior1/5

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

The description states that setting mark_read:true flags events as read, a state change. This directly contradicts the readOnlyHint=true annotation, which asserts no state changes. The contradiction is significant and could mislead agents relying on the annotation.

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?

Three dense sentences with no filler. Front-loads the purpose, then describes payload, filtering, mark_read, and polling. Every sentence earns its place and the structure is logical.

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?

With no output schema, the description compensates by explaining return payload contents (source, citation_uri, raw event payload). It also covers filtering, mark_read, and polling. A minor gap is lack of explicit pagination behavior, but the limit parameter in the schema addresses that.

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%, and the description goes beyond: it gives a concrete type example ('sec_8k'), explains mark_read semantics ('flag returned events read so the next call only shows newer ones'), and mentions the return payload structure. This adds real 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?

Clear verb+resource: 'Pull fired events from your subscription feed.' It distinguishes from siblings like list_subscriptions (manage feeds) and recent_changes (system changes). The name and description are aligned and specific.

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 context: filtering by type and since, polling suitability, and an alternative HTTP endpoint for scripts/dashboards. Does not explicitly name alternative tools or exclusions, but the intended use case is evident from the description.

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
Disambiguation3/5

Most tools are clearly distinct, but there are several overlapping clusters: ask_pipeworx and ask_pipeworx_beta are near-duplicates today, the Polymarket tools (edges, arbitrage, fill_risk, bet_research) have partially overlapping discovery purposes, and ai_visibility_check vs scan_competitor_ai_presence overlap on single vs multi-entity checks. These overlaps create real misselection risk, though the rest of the set splits cleanly.

Naming Consistency3/5

All names are snake_case and readable, but conventions vary noticeably: verb_noun for actions (check_ip, report_ip, list_subscriptions), domain-prefixed nouns for the Polymarket cluster (polymarket_edges, polymarket_arbitrage), and brand-prefixed meta tools (ask_pipeworx, pipeworx_feedback). Subfamilies are internally consistent, but the overall set mixes patterns.

Tool Count2/5

34 tools is already past the heavy threshold, but the bigger issue is the server name: Abuseipdb should have a handful of IP-abuse tools, yet only 3 of 34 actually relate to AbuseIPDB. The remaining 31 tools form an unrelated Pipeworx/Polymarket/memory suite, making the count wildly inappropriate for the apparent purpose.

Completeness2/5

For the declared AbuseIPDB domain, only check, report, and blacklist are covered; obvious gaps remain like removing/clearing a false report, bulk IP checks, or category metadata. The broader set is a grab bag of unrelated capabilities, so no single domain gets complete lifecycle coverage, and the nominal AbuseIPDB surface is thin and diluted.