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Glama

Kroger

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

A3.8/5.0
Behavior1/5

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

The description states that setting mark_read:true flags events as read, implying a state mutation. This contradicts the readOnlyHint annotation, which indicates no side effects. Therefore, the description contradicts the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four sentences and front-loads the core purpose. It contains minimal redundancy, though the last sentence about an alternative endpoint could be considered optional but still useful.

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 lacking an output schema, the description covers all important aspects: return fields (source, citation_uri, payload), filter parameters, the mark_read feature, and polling safety. It is complete for a read-oriented tool with no required parameters.

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 adds value by giving example values for type ('sec_8k') and explaining the effect of mark_read, which is not fully captured in the schema 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 begins with 'Pull fired events from your subscription feed,' specifying a clear verb and resource. It distinguishes from sibling tools like list_subscriptions by focusing on events from the feed rather than managing subscriptions.

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 explains filtering and the mark_read option, and notes that polling is acceptable. It provides an alternative endpoint for scripts/dashboards, but does not explicitly contrast with sibling tools like subscribe or list_subscriptions.

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

A3.7/5.0
Disambiguation2/5

Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research all query data), making it hard for an agent to choose the correct one. Additionally, entity_profile and compare_entities both provide company profiles, adding further ambiguity.

Naming Consistency2/5

Tool names are inconsistent: some use verb_noun (ask_pipeworx, compare_entities), some noun_verb (entity_profile), and some are single verbs (forget, recall). There is no clear pattern, and the mix of styles (e.g., kroger_*, polymarket_*, pipeworx_*) adds confusion.

Tool Count3/5

34 tools is on the higher end, but the server covers a broad domain (grocery, data query, betting, subscriptions). However, the presence of multiple similar query tools (e.g., three ask_pipeworx variants) inflates the count unnecessarily, making it feel bloated.

Completeness3/5

For its stated Kroger grocery focus, the tools (search, details, store locator) are complete. However, the server also includes many unrelated tools (betting, entity profiles, subscriptions) that feel tacked on, leaving gaps in coverage for the non-Kroger domains (e.g., no tools for user management or other store chains).

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