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campaignstack_priority_enrich

Idempotent

Immediately enrich specific LinkedIn profiles, bypassing the normal priority queue. Profiles are queued at highest priority and processing starts immediately. Maximum 50 slugs per request. Use campaignstack_get_enrichment_status to monitor progress.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugsYes
platformNo
accountIdYes
workspaceIdYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already mark the operation as non-read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond those annotations: profiles are queued at highest priority, processing starts immediately, there is a 50-slug limit, and progress should be monitored via a status tool. This gives the agent an accurate mental model of the asynchronous queue behavior.

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 three short sentences that front-load the core action, then add the key constraint and the monitoring suggestion. Every sentence earns its place, and there is no redundant or filler content.

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?

The description covers the core action, urgency/priority behavior, batch limit, and how to monitor progress, which is largely sufficient for correct invocation. However, since there is no output schema, the description does not clarify what the response will contain (e.g., a job identifier) or how the status tool correlates to this request, leaving a minor but real gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it only partially does. It clarifies that 'slugs' refer to LinkedIn profiles, which is useful, but workspaceId and accountId are left unexplained. The 'Maximum 50 slugs per request' simply restates the schema's maxItems constraint and adds no new semantic value.

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 uses a specific verb and resource ('Immediately enrich specific LinkedIn profiles'), states the key differentiator ('bypassing the normal priority queue'), and clearly distinguishes this from other enrichment tools. The mention of campaignstack_get_enrichment_status further clarifies the tool's role in a workflow.

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 clearly conveys when to use this tool: when immediate, high-priority enrichment of LinkedIn profiles is needed. It also gives a follow-up action ('Use campaignstack_get_enrichment_status to monitor progress') and a hard limit ('Maximum 50 slugs per request'). It does not explicitly name alternative enrichment tools or state when not to use it, which prevents 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

A3.6/5.0
Disambiguation3/5

Many tools share the same verb prefix (create_, list_, update_, get_) across closely related resources, so pairs like add_lead_to_external_list vs add_lead_to_sequence, create_signal_agent vs create_signal_watch, and approve_review vs approve_content_post can be confused. The descriptions are unusually detailed and cross-referenced, which mitigates but does not eliminate the ambiguity inherent in a 282-tool surface.

Naming Consistency4/5

Virtually every tool follows the campaignstack_verb_noun snake_case pattern, which is highly predictable. Minor deviations exist: destructive operations mix remove_ and delete_ (remove_lead_list vs delete_campaign), AI generation uses both craft_ and generate_, and the seo_/search_console_ subdomains introduce a second prefix convention.

Tool Count1/5

282 tools is an extreme mismatch by any reasonable standard, exceeding the 50+ threshold by more than 5x. Even for a full B2B outreach platform, this surface is far too large and would be better consolidated into higher-level operations or grouped sub-servers.

Completeness4/5

The tool surface is impressively comprehensive, covering campaigns, workflows, leads, content, ads, SEO, integrations, billing, and more with CRUD-level depth. Minor gaps remain: no single-ICP getter, no direct pause/delete for search watches, and no explicit delete for ad campaigns (only archive via update).

Resources