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Zoho_crm

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

A3.7/5.0
Behavior1/5

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

Description contradicts annotations: mark_read:true is described as flagging returned events read so the next call only shows newer ones, which is a persistent state change, while readOnlyHint=true declares the tool read-only. This is a significant conflict, overriding the otherwise useful disclosure of return fields and filtering behaviors.

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 five sentences, front-loaded with purpose, and every sentence adds value. The HTTP endpoint mention is slightly beyond tool scope but useful; no wasted words, though slightly longer than necessary for a top conciseness score.

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, the description explains the return shape (source, citation_uri, raw event payload). It covers filtering, mark_read side effects, polling suitability, and an HTTP alternative. It does not mention unread_only or limit, but the schema already documents those, so the tool is complete enough for selection and invocation.

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 with descriptions, so baseline is 3, but the description adds meaningful enrichment: a concrete example for type ('sec_8k') and explains that mark_read:true makes the next call only show newer events, which is a behavioral consequence beyond the schema's 'flag read' wording.

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 opens with a specific verb and resource: 'Pull fired events from your subscription feed.' It clearly differentiates this tool from siblings like recent_changes and list_subscriptions by focusing on fired alerts from the persisted feed and mentioning filtering and read-state management.

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 clear when-to-use context: polling works, and the same feed is available via GET registry.pipeworx.io/alerts.json for scripts/dashboards, implying when to use an alternative access method. However, it does not explicitly contrast with sibling tools, so it stops short of a 5.

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

B3.3/5.0
Disambiguation2/5

The five Zoho CRM tools are well-differentiated, but the 31 Pipeworx/Polymarket tools create heavy overlap (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research all serve similar lookup purposes). Mixing two unrelated domains makes it easy for an agent to select a tool from the wrong group.

Naming Consistency2/5

The Zoho tools share a consistent zoho_ prefix, but the remaining 31 tools follow no clear convention—ask_pipeworx, bet_research, deep_research, entity_profile, forget, scan_dependency, etc. mix noun-first, verb-first, and bare verb patterns without a unifying scheme.

Tool Count2/5

36 tools is well beyond what a Zoho CRM server needs, and only 5 actually relate to Zoho CRM. The bulk are for unrelated data sources, prediction markets, memory management, and web generation, making the set feel bloated and unfocused.

Completeness2/5

The Zoho CRM surface includes create, get, list, and search, but omits essential operations like update, delete, and upsert. The other 31 tools cover a completely different domain, so the server fails to provide complete lifecycle coverage for its stated purpose.

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