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Glama

Webflow

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?

The description claims that setting mark_read:true flags events as read and affects subsequent calls, implying state mutation, but annotations declare readOnlyHint=true. This is a contradiction, and per instructions, the score must be 1.

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 concise—four sentences front-loading the purpose, with no redundant information. Every sentence adds value.

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?

Tool has 5 optional params, no output schema. Description covers return fields and filtering/polling behavior, but does not detail pagination or unread_only behavior. Overall fairly complete for a read 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 covers 100% of parameters; description adds value by providing an example for type ('sec_8k'), clarifying the use of ISO timestamps for since, and explaining the effect of mark_read. This exceeds the baseline of 3.

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 clearly states the tool retrieves recent alerts from the subscription feed, specifying return fields (source, citation_uri, raw event payload) and filtering options. It is well-distinguished from sibling tools which cover subscriptions, searching, or other actions.

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?

Description provides usage guidance: filtering by type and/or since, setting mark_read, and notes on polling. It also mentions an alternative GET endpoint for scripts/dashboards. However, it does not explicitly state when not to use this tool versus alternatives.

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

A3.5/5.0
Disambiguation2/5

Several tools have blurry boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, polymarket_edges/polymarket_arbitrage/polymarket_edge_tracker/polymarket_fill_risk all target overlapping prediction-market signals, and ai_visibility_check vs scan_competitor_ai_presence plus entity_profile vs recent_changes vs compare_entities partially duplicate each other. The Webflow tools are distinct, but the dominant Pipeworx cluster is hard to navigate.

Naming Consistency2/5

Naming mixes multiple conventions: clean verb_noun for Webflow tools (list_sites, get_collection_item), an ask_pipeworx family, plain single verbs (remember, recall, forget), and long noun-cluster names for prediction markets (polymarket_arbitrage, polymarket_edge_tracker). There is no single predictable pattern across the set.

Tool Count1/5

36 tools is excessive for a server named 'Webflow' — only about six tools actually concern the Webflow CMS (list_sites, get_site, list_collections, list_collection_items, get_collection_item, generate_llms_txt). The remaining ~30 tools form a completely different data-research/prediction-market/memory suite, making the server wildly over-scoped and mislabeled.

Completeness2/5

For the Webflow domain, the surface is read-only: sites and collections can be listed and items fetched, but there are no create, update, delete, or publish operations, leaving obvious lifecycle gaps. The extensive non-Webflow tools do not address the stated server purpose, so the mismatch hurts completeness rather than fixing it.

Resources