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Glama

Ca Procurement

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

A4.4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, so description adds value by explaining the mark_read side effect ('flag returned events read') and noting the idempotent nature. No contradiction. Adds behavioral context beyond structured fields.

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?

Approximately 100 words, efficiently structured: purpose first, return payload, filtering, mark_read effect, polling info. No wasted sentences; every part earns its place.

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?

Despite no output schema, description compensates by listing return fields (source, citation_uri, payload). Covers parameter behaviors and polling suitability. Lacks full return structure but adequate for an agent.

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 has 100% coverage, but description enriches semantics: explains return types, gives example for 'type' filter ('sec_8k'), clarifies 'since' is ISO timestamp, and describes mark_read behavior. Adds value beyond 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?

Description clearly states the verb ('Pull') and resource ('fired events from your subscription feed'). It specifies the returned contents (source, citation_uri, raw event payload) and distinguishes itself from siblings like 'list_subscriptions' by focusing on alert 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?

Provides explicit usage context: 'Filter by type... and/or since (ISO timestamp). Polls work fine.' Also mentions an alternative endpoint for scripts/dashboards. Lacks explicit when-not-to-use guidance, but overall clear.

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

All Ca Procurement toolsInspect
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TDQS

A3.7/5.0
Disambiguation1/5

The tool set has severe overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve similar query/discovery purposes, and multiple polymarket tools (polymarket_edges, polymarket_arbitrage, bet_research) overlap heavily in finding betting opportunities. An agent would struggle to select among these without deep familiarity, especially when ask_pipeworx and ask_pipeworx_beta are currently identical.

Naming Consistency2/5

Individual families are internally consistent (ca_procurement_*, polymarket_*, pipeworx_*), but the server as a whole mixes domain-prefixed snake_case, bare verb phrases (ask_pipeworx, bet_research), and descriptive noun phrases (entity_profile, recent_changes). More importantly, the vast majority of tool names have nothing to do with the server's stated 'Ca Procurement' identity, so the naming fails to signal a coherent tool set.

Tool Count2/5

36 tools is well past the 25+ threshold for 'too many,' and over 85% of them (31 tools) are unrelated to California procurement—they cover general data lookup, prediction markets, npm packages, and memory storage. A scoped CA procurement server would reasonably have 5–8 tools; this is a general-purpose data platform wearing a procurement label.

Completeness3/5

The five relevant ca_procurement_* tools cover the main read-side query patterns well: award search, commodity rankings, department profiles, supplier aggregation, and top suppliers. However, the surface lacks contract/award detail retrieval by ID, solicitation or RFP search, and any vendor registration or contract lifecycle data, leaving notable gaps for a procurement-focused tool set.

Resources