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Glama

Politics Feeds

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. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare safe read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral details: returns most recent alerts, each carries specific fields, filter options, mark_read effect, and polling suitability. No contradictions with 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 three sentences, each earning its place: purpose, payload details with filtering, and mark_read/polling guidance. No redundant words, well-structured, and front-loaded with the core action. Ideal conciseness.

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?

Given no output schema, the description explains return values and filter behavior adequately. It mentions polling and REST endpoint. Minor gaps: the limit parameter maximum (200) is only in the schema, and pagination is not discussed. However, for a simple read tool with 100% schema coverage, this is nearly complete.

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 concise descriptions for all 5 optional parameters. The description adds value by providing examples (e.g., 'sec_8k' for type), explaining the effect of mark_read ('flag returned events read so the next call only shows newer ones'), and clarifying the since parameter as ISO timestamp. This goes beyond the schema's brief descriptions.

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 clear verb-resource pair ('Pull fired events from your subscription feed'), specifies what each event carries (source, citation_uri, payload), and distinguishes the tool by mentioning filtering and mark_read behavior. It implicitly contrasts with siblings by noting the feed is also available via a REST endpoint, making the purpose highly 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?

The description clarifies when to use this tool (for recent alerts, with optional filters and mark_read), states that polling works fine, and mentions an alternative REST endpoint for scripts/dashboards. It does not explicitly list when not to use it or contrast with sibling tools like read_feed, 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

A4/5.0
Disambiguation3/5

Most tools have distinct jobs and the descriptions are unusually explicit about routing, but there are overlapping entry points: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all sit in the same query/research space. ask_pipeworx_beta even states it currently matches ask_pipeworx exactly, which makes some boundaries genuinely ambiguous despite strong descriptions.

Naming Consistency3/5

The set is uniformly snake_case and has useful families like polymarket_* and pipeworx_*, plus many clear verb_noun names (list_feeds, read_feed, resolve_entity, validate_claim). However, roughly a third of tools use noun-led or adjective-led names (entity_profile, deep_research, recent_alerts, polymarket_arbitrage), so the pattern is readable but mixed.

Tool Count2/5

34 tools is far beyond what a 'Politics Feeds' server needs, and a large portion of the surface (npm dependency scanning, AI visibility, memory, prediction markets, LLM text generation) is unrelated to the stated purpose. This feels like a kitchen-sink monolith rather than a scoped feed server.

Completeness4/5

Within its actual implied purpose as a broad Pipeworx data-research platform, the lifecycle is well covered: discover, resolve, ask, ground, research, compare, validate, monitor, subscribe, and remember are all present. The gaps are minor—no update-subscription operation and no direct cross-feed search for the feeds named by the server—so agents can work around them.

Resources