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update_project_settings

Change a client's AI-visibility project settings beyond scanning: brand name, product type, the Brand Profile (how the brand describes itself), pause/resume the project, Local-GEO fields (locality, region, Google Business Profile URL, service areas), the brand's own off-site channel URLs, the monthly perception email opt-in, target attributes (messaging pillars to score against what AI says), declared brand facts for fact-checking, and the Follow-up-Survival opt-in. Only the fields you pass are changed; array fields REPLACE the stored list. NOTE: changing brandName changes how mentions are matched from the next scan onward. Requires MCP write actions; without confirm:true it returns a preview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
activeNofalse pauses the whole project (no scheduled scans); true resumes. Writes a timeline note.
regionNoLocal GEO: region/state. Null clears.
confirmNoSet true to apply. Omit for a preview. With confirm:true, also pass the preview's previewToken.
isLocalNoLocal-GEO mode on/off.
profileNoBrand Profile free-text fields — MERGED onto the existing profile; only the keys you pass change.
clientIdNoClient id — alternative to projectId.
localityNoLocal GEO: town/city. Null clears.
brandNameNoThe brand name mentions are matched against. Changing it affects matching from the NEXT scan; history keeps the old matching.
projectIdNoAI-visibility project id.
brandFactsNoDeclared factual claims to fact-check against what AI says, one line each (max 15, 200 chars) — REPLACES the stored list.
productTypeNoWhat the brand sells, e.g. "marketing agency". Null clears it.
previewTokenNoWith confirm:true: the previewToken from this tool's preview (valid 15 minutes, once, for exactly the previewed arguments).
serviceAreasNoLocal GEO: service areas — REPLACES the stored list (max 25).
offSiteChannelsNoThe brand's OWN off-site profile URLs (YouTube/LinkedIn/Reddit/…) for off-site citation attribution — REPLACES the stored list. Include the handle, not a bare host.
perceptionEmailNoMonthly "How AI describes you" email on/off for this project.
targetAttributesNoAttributes the brand WANTS to be known for (scored by the Messaging-gaps widget) — REPLACES the stored list (max 20).
followUpSurvivalEnabledNoFollow-up-Survival (multi-turn) opt-in for this project.
googleBusinessProfileUrlNoLocal GEO: the brand's Google Business Profile URL (must be http/https). Null clears.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Adds substantial behavior beyond annotations: array fields REPLACE the stored list, brandName changes affect mention matching from the next scan only, writes require MCP write actions, and confirm/preview gating. These are exactly the gotchas an agent needs and annotations alone (readOnlyHint=false, destructiveHint=false) do not convey.

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?

Front-loaded with the core action, then the field groups, then the two critical caveats. It is dense but every clause maps to real parameters and constraints. The long inline enumeration is a minor readability cost rather than waste.

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 an 18-parameter mutation tool, the description covers the merge-vs-replace rule, the confirm/preview workflow, the matching side effect, and auth needs, which is what an agent must know before invoking it. No output schema exists, but the preview/confirm return behavior is described.

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?

Schema description coverage is 100%, so the schema already documents every parameter, including the REPLACE semantics and the brandName matching note. The description mostly consolidates and repeats that content rather than adding new parameter meaning, so the 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?

States a specific verb (change) and resource (a client's AI-visibility project settings) and explicitly scopes it 'beyond scanning,' immediately routing away from scan-related siblings. It enumerates the categories of settings so the agent knows the tool's surface area.

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?

Gives clear operating conditions: 'Only the fields you pass are changed,' 'without confirm:true it returns a preview,' and 'Requires MCP write actions.' However it never names the specific alternatives (update_scan_settings, update_report_settings), so sibling differentiation is 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.

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