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Glama

Vies Eu

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?

Annotations declare readOnlyHint=true, but the description introduces mark_read:true, which flags events as read and mutates state. This contradicts the read-only annotation, so the description is misleading about the tool's side effects. Annotation contradiction flagged.

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 with no fluff. The primary action is front-loaded, followed by return contents, filtering methods, mark_read behavior, and an alternative access method. Every sentence carries meaningful information.

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?

Covers return contents, filtering, mark_read effect, polling suitability, and an alternative REST endpoint. With no output schema, it sufficiently describes what the caller gets, though it does not explicitly state that results are returned as a list or mention pagination.

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 beyond the schema by giving a concrete type example (sec_8k), clarifying since as ISO timestamp, and explaining that mark_read affects future calls by only returning newer events.

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?

Description clearly states the tool pulls fired events from the subscription feed, with specific details about return contents (source, citation_uri, raw payload). It distinguishes itself from sibling tools by focusing on alerts and the evaluator-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 usage context by noting polling works fine and offering an alternative HTTP endpoint for scripts/dashboards. Does not explicitly name sibling alternatives but implies when the tool is appropriate.

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

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta (explicitly identical to the stable router right now), ask_pipeworx_grounded, and deep_research all route the same class of questions, making mis-selection easy. The six Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) also blur together around edge detection and arbitrage, further muddying tool boundaries.

Naming Consistency4/5

All 33 tools use consistent lowercase snake_case naming, and most follow a clear verb_noun pattern (check_vat, compare_entities, resolve_entity, unsubscribe). A handful of noun-style names (entity_profile, bet_research, polymarket_edges, recent_alerts) deviate from the verb-first pattern but are still predictable and readable.

Tool Count2/5

33 tools is beyond the 25+ threshold for a coherent set, and the scope is sprawling: universal data routing, prediction-market analytics, VAT validation, AI visibility, memory, subscriptions, npm dependency scanning, and feedback. While each sub-domain has reason to exist, bundling them all into one server creates a kitchen-sink feel with too many entry points.

Completeness3/5

The core data-routing domain is well covered: universal router, grounded mode, deep research, entity resolution, profiles, comparisons, change feeds, claim validation, and search-within. VAT has check + status, and memory/subscription lifecycles are complete. However, there is no standalone tool to fetch a raw pipeworx:// record that citations reference, and the extreme breadth means no single domain is exhaustively fleshed out.

Resources