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Recent Alerts

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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?

The description goes beyond annotations by detailing that returned events include source, citation_uri, and raw payload. It also explicitly discloses the side effect of the 'mark_read' parameter (flags events as read, affecting future calls). This provides crucial behavioral context beyond the readOnlyHint and other 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 four sentences, each serving a distinct purpose: purpose, payload contents, filtering/mark_read behavior, and alternative usage. It is front-loaded with the most critical information and contains no redundant 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?

Given the tool has 5 optional parameters, no output schema, and read-only annotations, the description covers all necessary aspects: what is returned (source, citation_uri, raw payload), how to filter (type, since), the side effect of mark_read, and an alternative access method. This provides a complete mental model for an AI agent.

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?

With 100% schema description coverage, the baseline is 3. The description adds value by explaining the effect of 'mark_read' (flagging events so next call only shows newer ones) and providing an example for 'type' ('sec_8k'). It also clarifies that 'since' expects an ISO timestamp, which reinforces the schema description. However, it doesn't add much to 'limit' or 'unread_only' 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 a clear verb-resource pair: 'Pull fired events from your subscription feed.' It immediately specifies the resource and action, distinguishing it from sibling tools like 'list_subscriptions' which lists subscriptions rather than events.

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 mentions that polling works fine and provides an alternative REST endpoint for scripts/dashboards, which gives guidance on when to use this tool versus an HTTP alternative. However, it doesn't explicitly state when not to use this tool or compare it to other sibling tools.

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
Disambiguation2/5

Many tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants (beta currently identical), and the set includes five-plus prediction-market tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread, bet_research) with fuzzy boundaries. Long descriptions help, but an agent selecting among them would frequently struggle to pick the right one.

Naming Consistency3/5

Names are uniformly lowercase snake_case, but the pattern is inconsistent: verb_first names (search_samples, validate_claim, resolve_entity) mix with noun-style names (entity_profile, pipeworx_trending, polymarket_arbitrage) and bare imperatives (remember, recall, forget, subscribe). It is readable, but there is no predictable verb_noun convention across the set.

Tool Count2/5

33 tools is well over the coherent range, and the count is especially inflated because the server is named Biosamples yet only two tools (search_samples, get_sample) actually belong to that domain. The remaining 31 tools are an unrelated mix of Pipeworx research, prediction-market, memory, and subscription utilities, including redundant variants.

Completeness2/5

For the stated Biosamples purpose, only search and retrieve exist—no submission, update, or batch operations—so the domain surface is a read-only fragment. For the broader accidental scope of the other tools, the set is a grab bag with no coherent lifecycle, leaving significant gaps regardless of which domain is considered primary.