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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

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description adds critical behavioral detail: setting mark_read=true flags events as read, affecting subsequent calls. It also notes that the same feed exists for scripts/dashboards.

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?

Five sentences, each serving a distinct purpose: purpose, return fields, filters, mark_read detail, and alternatives. No wasted words.

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 covers return fields (source, citation_uri, payload), all parameters, side effects, and alternate access. No output schema exists, but the description compensates well.

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% with descriptions for all 5 parameters. The description adds value by explaining the mark_read side effect and the unread_only filter, going beyond the schema's basic definitions.

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 verb 'Pull' and the resource 'fired events from your subscription feed'. It distinguishes from sibling tools like list_subscriptions by focusing on alerts/events rather than subscriptions.

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 explains filtering by type/since, the mark_read behavior, and mentions polling and an alternative API endpoint. However, it does not explicitly state when not to use this tool versus siblings.

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
Disambiguation3/5

Most tools have distinct purposes, but there are overlapping tools like the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and ai_visibility_check/scan_competitor_ai_presence. A few pairs could cause confusion, but overall differentiation is moderate.

Naming Consistency2/5

Tool names follow no consistent pattern: some are imperative verbs (remember, forget), some are compound nouns (entity_profile, polymarket_arbitrage), some are descriptive phrases (recent_alerts, scan_dependency). The verb_noun pattern is absent, leading to inconsistency.

Tool Count1/5

33 tools is far too many for a server named 'Jisho' (a Japanese dictionary), especially since only 2 tools (lookup, search_words) are dictionary-related. The majority of tools belong to an unrelated data platform, making the count wildly inappropriate for the server's apparent purpose.

Completeness3/5

For the dictionary domain, the server lacks common features like example sentences or kanji details. However, the extended tool set covers many data retrieval and analysis tasks, though it is read-heavy with no update/delete capabilities for most resources.