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Glama

Opencellid

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

A4.7/5.0
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description adds key behaviors: marking events as read (mark_read), returning specific fields (source, citation_uri, payload), and confirming polling suitability. No contradiction 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 concise (two main sentences plus a note about an alternative endpoint). It is front-loaded with the core purpose and each sentence provides necessary detail without repetition.

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 the tool's simplicity (no required parameters, no nested objects, no output schema), the description covers what is returned, filtering options, state-changing parameter behavior, and an alternative method. It is complete for an agent to understand and use 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%, providing baseline 3. The description adds meaning by explaining the effect of mark_read, giving an example filter (sec_8k), and clarifying that since expects an ISO timestamp. This adds value beyond the schema.

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 it pulls fired events from the subscription feed and returns recent alerts. It distinguishes itself from sibling tools like list_subscriptions (which lists subscriptions) and subscribe/unsubscribe (which manage subscriptions) by focusing on event retrieval.

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 this tool (e.g., polling works fine) and mentions an alternative endpoint for scripts/dashboards. However, it does not explicitly state when not to use this tool or contrast with alternatives like search tools.

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

Several tools are near-indistinguishable by role: ask_pipeworx and ask_pipeworx_beta are documented as currently identical, and ask_pipeworx, ask_pipeworx_grounded, and deep_research overlap as lookup/research entry points. The six-tool Polymarket cluster and the suggest_questions/discover_tools pair add further boundary confusion despite very long descriptions.

Naming Consistency3/5

Snake_case is used consistently, and clusters like ask_pipeworx_* and polymarket_* have internal consistency. However, the global convention is mixed: verb_object names (get_cell, resolve_entity, unsubscribe) sit beside noun phrases (entity_profile, recent_changes, cells_in_area) and product-prefixed nouns (pipeworx_feedback, polymarket_edges), so tool names are not predictable from function.

Tool Count2/5

33 tools is too many for a server named Opencellid, especially since only get_cell and cells_in_area actually belong to the cell-tower domain. Even as a broader Pipeworx/data bundle, the set is heavy and includes unrelated one-offs like generate_llms_txt and scan_dependency.

Completeness2/5

For an OpenCellID server, the surface is just two lookups, missing coverage stats, operator-based search, and other natural cell-tower operations. If judged instead as a Pipeworx data-research suite, coverage is broad, but the lack of a coherent stated domain makes obvious gaps and dead ends harder to identify.

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