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Glama

campaignstack

by io.campaignstack

campaignstack_seo_update_prompts

Destructive

Batch-update probe prompts: add (text, 10-300 chars), edit (promptId + text), toggle (promptId + active), or delete (promptId). Up to 200 operations per call. Active prompts are unlimited (5,000 total per workspace); every active prompt is probed on each engine per audit and charged per call, so cost scales with the active set. Free weekly runs cover only the first 20 active prompts (user prompts first). Every response echoes the cost state: overagePromptCount and weeklyOverageCredits (what the set costs per week when the overage opt-in is on) plus perAuditProbeCredits — check it after adding prompts so charges are never a surprise. Use campaignstack_seo_list_prompts to find prompt IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operationsYes
workspaceIdNo

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the destructiveHint annotation, the description discloses important behavioral details: operation limits (up to 200), cost scaling with active prompts, free-run coverage of only the first 20 active prompts, and the cost-related response fields (overagePromptCount, weeklyOverageCredits, perAuditProbeCredits). This is substantial value-add over the 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 dense but well-structured: operation semantics first, then limits, then cost implications, then response fields, then a pointer to the sibling tool for IDs. Every sentence contributes useful information and there is minimal fluff.

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?

For a batch mutation tool with no output schema, the description covers input rules, cost behavior, response cost fields, and prompt ID discovery. It falls slightly short on describing the overall response shape beyond cost fields and does not clarify workspaceId usage, but overall it is unusually complete.

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?

The description compensates for the low schema description coverage by explaining which parameters each operation requires, including text length constraints and the promptId/active relationships. However, workspaceId is not explained in the description, leaving one optional parameter without semantic guidance.

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: 'Batch-update probe prompts' and then enumerates the four supported operations (add, edit, toggle, delete) with their required inputs. This clearly distinguishes it from siblings like campaignstack_seo_list_prompts and campaignstack_seo_run_audit.

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 gives clear context for when to use this tool and explicitly points to campaignstack_seo_list_prompts as the way to find prompt IDs. It does not provide explicit 'when not to use' exclusions, but the intended usage is unambiguous.

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