Skip to main content
Glama

campaignstack_decide_playbook_proposal

Accept or reject the pending playbook proposal. Accept applies every change in one transaction through the same caps, version snapshot and user-authored reconciliation as a manual edit; it fails when a targeted text changed since the proposal was made, in which case propose again. Reject applies nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
decisionYes
proposalIdYesPending proposal id from campaignstack_get_playbook_proposal
workspaceIdNoDefaults to the API key's workspace

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?

The annotations only declare readOnly=false, idempotent=false, and destructive=false, so the description carries the burden of behavioral context. It does this well by explaining that accept is transactional, mirrors manual edits, fails on conflicting changes, and that reject applies no changes. This is meaningful behavioral detail beyond 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 compact and front-loaded, with the core action stated in the first sentence and the critical failure/no-op behavior in the second. Every sentence provides necessary context without filler or repetition.

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 mutation tool with only two required parameters and no output schema, the description is mostly complete: it explains what accept and reject do, how acceptance behaves transactionally, and what to do if it fails. The only minor gap is that it does not describe the response or result of a successful decision, but that is not essential given the tool's straightforward nature.

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 schema documents proposalId and workspaceId, while decision is an undocumented enum. The description clarifies that 'accept' applies all changes and 'reject' applies nothing, which adds meaning to the decision parameter. With 67% schema coverage, the description partially compensates, though it does not add much about workspaceId or return behavior.

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 clearly identifies the action ('Accept or reject') and the resource ('pending playbook proposal'), and it distinguishes accept from reject. It also sets expectations around the proposal lifecycle, which separates it from related proposal-creation and reversion tools.

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 conveys when to use the tool: when a playbook proposal is pending and a decision must be made. It also instructs the user to propose again if acceptance fails due to stale text. However, it does not explicitly mention sibling alternatives or state conditions where another tool should be used instead.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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