campaignstack

campaignstack_search_console_list_competitors

Read-onlyIdempotent

List this workspace's competitor roster with each entry's relationship and whether it is confirmed or merely suggested. The roster is per-workspace data, never a built-in list: who competes with a tenant is a fact about their market. Suggested entries come from the workspace's own competitor watches and probe answers and are inert until confirmed. An empty roster still finds competitors through query grammar (" alternative"), just not by name.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`workspaceId`	No	Workspace ID (required for user keys; workspace keys are bound)

Schema Changelog

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

First observedSep 4, 2026

TDQS

A4.4/5.0

Behavior5/5

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

The annotations already declare readOnly, idempotent, and non-destructive, and the description adds meaningful behavioral detail: entries have relationship and confirmation state, suggested entries are inert until confirmed, and an empty roster still discovers competitors via query grammar but not by name. 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.

Conciseness4/5

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

The main purpose is front-loaded and each sentence contributes distinct context. However, the unresolved placeholder in 'query grammar ("<tool> alternative")' is a minor clarity defect that keeps it from being perfectly polished.

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?

For a one-parameter read-only listing tool with no output schema, this is complete: it describes the returned fields, the data source, confirmation semantics, and the empty-roster edge case. Nothing an agent needs to interpret the result is missing.

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

Parameters3/5

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

The input schema covers the single parameter with 100% detail, including the user-key vs workspace-key binding distinction. The description adds no parameter-specific semantics, but the schema already carries that burden, so baseline 3 is appropriate.

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 states an explicit verb-resource pair: 'List this workspace's competitor roster,' and specifies what each entry includes (relationship and confirmed/suggested status). This makes the tool's purpose unambiguous and distinguishes it from related siblings like search_console_set_competitor and list_competitor_watches.

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?

It provides clear context for when to call the tool: it returns per-workspace roster data, explains that suggestions come from competitor watches and probe answers, and notes that they are inert until confirmed. It does not explicitly name alternatives or state when not to use it, 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

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).

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