Skip to main content
Glama

Expression Atlas

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).

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnly, openWorld, idempotent, non-destructive. The description adds context about the mark_read flag's effect on future calls and notes the feed is persisted, which goes beyond 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 four sentences, front-loaded with the core purpose, and every sentence adds value (filtering, mark_read, alternative endpoint). No redundant phrases.

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?

Despite no output schema, the description specifies key return fields and behavior. It also covers parameter usage and provides an alternative access method. Given the tool's simplicity and rich annotations, this is fully 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?

With 100% schema coverage, the baseline is 3. The description explains the effect of mark_read and mentions filtering by type and since, adding meaning beyond the schema's property 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 clearly states the tool pulls fired events from the user's subscription feed, specifying key fields (source, citation_uri, payload) and filtering options. It distinguishes itself from siblings like list_subscriptions by focusing on recent events.

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 guidance on when to use (polls work fine) and even mentions an alternative HTTP endpoint for scripts/dashboards. However, it could more explicitly differentiate from similar tools like search_within.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Expression Atlas toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.7/5.0
Disambiguation3/5

Many tools have overlapping purposes (e.g., multiple Polymarket tools, multiple company information tools), but descriptions help distinguish them. However, the variety of domains (brand monitoring, betting, package scanning, memory, etc.) can confuse an agent.

Naming Consistency2/5

Tool names have no consistent naming pattern: some are verb_noun (validate_claim), some are noun_verb (bet_research), some are compound (ai_visibility_check), and some are single word (forget). This makes it hard to predict tool names.

Tool Count2/5

28 tools is high, and the set spans many unrelated domains (brand visibility, SEC/FDA data, Polymarket, npm packages, memory, etc.) while the server is named 'Expression Atlas' with only 2 tools related to that purpose. The tool count feels excessive and unfocused.

Completeness1/5

For a server named 'Expression Atlas', only two tools (get_experiment, search_experiments) cover the domain. There are no tools for submitting, updating, or deleting experiments, nor any for data visualization. The surface is severely incomplete.

Resources