Skip to main content
Glama

campaignstack_update_workspace

Idempotent

Update workspace settings. Only provided fields are updated. offerContext is the factual company/offer grounding injected into every AI craft (pass an empty string to clear it). capabilities describes what the SYSTEM behind this workspace can detect and do (signal detection, automated actions, integrations), as opposed to what it sells: it is injected into AI reply crafts only, so the agent can recognise when a lead describes a problem the product solves. Keep it short and factual; it is never used as a pitch list. Pass an empty string to clear it. playbookSections is the playbook itself, one field per section, each with its own hard character cap: a write over a cap is rejected, so shorten rather than retry. Read all current values via campaignstack_get_playbook.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
industryNo
companyNameNo
workspaceIdYes
capabilitiesNo
offerContextNo
outreachIntentsNoAcceptable outcomes for this outreach, most preferred FIRST. Answers 'why are we writing to these people': a message with no stated purpose reads as a compliment plus an open question. Resolution is workspace then campaign then workflow, and the narrowest non-empty list REPLACES the wider ones rather than merging, so setting it here overrides the level above. Pass an empty array to clear this level and fall back. The craft picks the highest outcome the individual reader could plausibly give, so listing several is how a non-buyer still gets a relevant message.
playbookSectionsNoThe workspace playbook, one field per section. Only the fields you pass are changed. Each field has a target length and a HARD character cap; a write over the cap is REJECTED, not truncated. Write to the target, not the cap: identity (aim for about 400, max 1200, sent on every message): who we are, positioning, what makes us different; voice (aim for about 400, max 1200, sent on every message): tone, formality, words to use and avoid; boundaries (aim for about 500, max 1500, sent on every message): topics to avoid, claims never to make; angles (aim for about 1000, max 3000, sent on messages we send first): reasons to reach out that land, and the levers that persuade; objections (aim for about 2000, max 6000, sent on replies, after they have written back): what people push back with, and the real answers. Sections are selected per message, so a long objections list costs a first message nothing. Do NOT restate the offer, the personas or the campaign goal here: all three already reach the prompt from structured data, and a second copy can only contradict the first.
companyWebsiteUrlNo

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

With idempotentHint=true and destructiveHint=false already declared, the description adds substantial behavior beyond annotations: writes over a hard cap are REJECTED rather than truncated (telling the agent to shorten, not retry), empty strings clear fields, outreachIntents uses replace-not-merge resolution with fallback to wider scopes, and playbook sections are selected per message. This is exactly the kind of operational detail an agent needs to avoid failed calls.

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 long but every sentence earns its place — the offerContext/capabilities distinction is essential and non-obvious, and the character-cap warning prevents a whole class of failed writes. It is front-loaded with the core partial-update semantic, then organized logically by parameter. The outreachIntents detail is deferred to the schema description, which keeps the main description from bloating further.

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 9-parameter mutation tool with nested objects and no output schema, the description covers the high-risk aspects: error behavior, clearing semantics, override resolution, and what not to include in playbook sections. Minor gaps remain — no mention of what the response looks like on success, whether empty strings clear the simple fields, or auth requirements — but the critical decision points for a correct call are addressed.

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 coverage is only 22%, so the description carries the burden — and it earns its keep on the three genuinely ambiguous parameters: offerContext (factual grounding injected into every craft), capabilities (system detection abilities injected into replies only, never a pitch list), and playbookSections (per-section char caps with target lengths). The self-evident params (name, industry, companyName, companyWebsiteUrl, workspaceId) are left to their names, which is an acceptable trade given the description cannot cover all nine at this length.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 ('Update workspace settings') and immediately clarifies the partial-update semantics ('Only provided fields are updated'). It clearly identifies the operation, though it does not explicitly differentiate itself from closely named siblings like campaignstack_update_workspace_branding or campaignstack_get_workspace; the agent must infer the boundary from the name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives strong contextual guidance about when field values are consumed (injected into crafts, reply crafts only, per-message selection) and explicitly points to campaignstack_get_playbook for reading current values before updating. However, it never states when NOT to use this tool or names alternatives for branding/workspace-level reads, so the when-to-use is largely implied rather than explicit.

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