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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).

Schema Changelog

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

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds vital behavioral context: it explains the mark_read side effect (flags events read so future calls return only newer ones), the source of events (evaluator-written persisted feed), and the inclusion of raw payloads. It does not contradict any annotation and substantially enriches the behavioral model.

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, and every sentence earns its place: core purpose, return payload details, filtering and mark_read behavior, and the alternative HTTP endpoint. The key action is front-loaded, and there is no redundancy or filler.

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 five optional parameters, no output schema, and helpful annotations, the description covers the essential aspects: what events are returned, how to filter, the mark_read state change, polling suitability, and an alternative access path. It is sufficiently complete for an agent to decide when and how to invoke the tool.

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%, so the baseline is 3. The description adds value by giving an example for type (e.g., 'sec_8k'), clarifying 'since' as ISO timestamp, and explaining the interaction between mark_read and subsequent polling. This goes slightly beyond the schema's per-parameter 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 opens with 'Pull fired events from your subscription feed,' which clearly states the verb, resource, and scope. It further specifies what each event carries and distinguishes itself from sibling tools by focusing on alerts/events rather than subscriptions or changes.

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 provides clear context by stating that polling works fine and offers an explicit alternative: the same feed is available via HTTP for scripts/dashboards. However, it does not explicitly name alternative tools or give exclusions, so it falls just short of a 5.

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

A3.6/5.0
Disambiguation2/5

The StackExchange tools are distinct, but the dominating data-lookup cluster is highly ambiguous: ask_pipeworx, ask_pipeworx_beta (explicitly identical today), ask_pipeworx_grounded, deep_research, and validate_claim all route into the same underlying tool catalog. The polymorpharket tools also overlap heavily, making selection between bet_research, polymarket_edges, polymarket_arbitrage, and fill-risk checks genuinely hard.

Naming Consistency2/5

The names are all snake_case but otherwise follow no consistent pattern: bare verbs (remember, forget, subscribe), prefixed names (pipeworx_feedback, stack_get_user), composite domain names (ask_pipeworx, generate_llms_txt), and generic verbs (resolve_entity, validate_claim, search_within). The StackExchange subset itself is split between stack_get_user/stack_tags and search_questions/get_answers.

Tool Count2/5

36 tools is already in the 'too many' range for one server, and the mismatch with the server name is severe: only 5 of 36 tools relate to StackExchange. The rest form a broad Pipeworx/prediction-market data platform that would itself be oversized for a focused purpose.

Completeness2/5

For a StackExchange-focused server, the surface has core read operations but lacks question-detail-by-ID, comments, related questions, or any write/community actions, and the 31 unrelated tools do not fill that gap. For the broader apparent Pipeworx platform coverage is broad, but the set has no single coherent domain against which completeness can be meaningfully judged.