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Bis

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).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A3.8/5.0
Behavior1/5

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

Annotation Contradiction: Annotations declare readOnlyHint=true, but the description states 'Set mark_read:true to flag returned events read so the next call only shows newer ones,' which mutates state. This directly contradicts the read-only annotation. idempotentHint is also questionable with mark_read side effects.

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 sentences, front-loaded with the main purpose, and every sentence provides useful information: function, return shape, filters, mark_read behavior, and alternative access. No fluff.

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?

Description covers what the tool returns (source, citation_uri, raw payload), how to filter, the read-flagging behavior, and provides an external endpoint for scripting. No output schema exists, so returning payload details is essential and handled 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 covers all 5 parameters with descriptions (100% coverage). The description adds value with a concrete type example ('sec_8k'), clarifies `since` as ISO timestamp, and explains the behavioral effect of `mark_read` on subsequent calls.

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 starts with a specific verb+resource: 'Pull fired events from your subscription feed.' It clearly distinguishes this from sibling tools like subscribe or list_subscriptions by focusing on retrieval of alert events from a persisted feed.

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: 'Polls work fine' and notes the same feed is available at an HTTP endpoint for scripts/dashboards. It doesn't explicitly name sibling alternatives or exclusions, but the context is sufficient for typical use.

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

A3.9/5.0
Disambiguation3/5

Most tools have carefully written distinctions, but several overlap in purpose: ask_pipeworx versus ask_pipeworx_beta are currently functionally identical, and ask_pipeworx, deep_research, validate_claim, and the Polymarket research tools all sit on the same factual-question axis. The long descriptions help an agent choose, but the set still has multiple ambiguous boundaries.

Naming Consistency3/5

Names are uniformly snake_case and mostly readable, with clear prefix families like pipeworx_*, polymarket_*, and ask_pipeworx*. However, the verb-noun pattern is inconsistent: many tools are noun phrases (entity_profile, recent_alerts, polymarket_edges) and some are bare verbs (remember, recall, forget), so the naming is not predictable across the full set.

Tool Count2/5

35 tools is well above the 25-tool threshold and feels like an organic platform dump rather than a curated server. The broad data-platform scope partly justifies the number, but the presence of near-duplicate entry points and one-off utilities (generate_llms_txt, ai_visibility_check, scan_dependency) makes the set feel bloated rather than cohesive.

Completeness4/5

For a read-heavy data/research platform the surface is unusually complete: discovery, single-lookup, grounded-answer, deep-research, entity resolution, comparison, change-tracking, subscriptions, memory, and feedback are all covered. Missing write/execution capabilities like placing trades or modifying BIS flows are reasonable absences for this kind of server; the main gap is a dedicated historical/trend utility beyond the general router.

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