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by com.serpier
OverviewDiscussionsAdmin

add-seo-keywords

Add or tag tracked SEO keywords. Each row has keyword, tags (tag names, [] for none; missing tags are created), and optional countryCode (ISO-2). Existing keywords get the row's tags without losing their current ones. More keywords raise the Navi credit cost of each scheduled rank check.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "advertiserProjectId": "<advertiserProjectId>",
      "rows": "<rows>",
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "add-seo-keywords"
  }
}

Input Schema

NameRequiredDescriptionDefault
rowsYesKeywords to add, one row each.
tagIdsNoTag ids from get-organization-tags to add to every row.
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
advertiserProjectIdYesProject id from get-projects or get-project.

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the annotations (destructiveHint=false, readOnlyHint=false), the description discloses non-obvious behavior: tags are merged additively rather than overwriting, missing tag names are silently created as a side effect, and adding keywords raises the Navi credit cost of each scheduled rank check. These are exactly the consequences an agent cannot derive from the schema or annotations, and all are consistent with destructiveHint=false.

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?

Four compact sentences, front-loaded with the verb and resource, then row shape, then cost warning last where it belongs. Minor waste repeating that tags are '[] for none', which the schema already documents.

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 annotations and no output schema, the description covers merge semantics, tag auto-creation, country defaulting, and credit cost. It omits the 2000-row cap, how tagIds interacts with per-row tags, and what the call returns, leaving small gaps for an agent planning a bulk add.

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 baseline is 3. The description restates the row fields (keyword, tags, countryCode, ISO-2, default country) but adds almost nothing beyond the schema wording, and says nothing about tagIds, context, or llm_model.

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 names a specific verb+resource ('Add or tag tracked SEO keywords') and immediately explains the row shape and the upsert semantics ('Existing keywords get the row's tags without losing their current ones'), which separates it from remove-seo-keywords and get-seo-keywords without opening the schema.

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?

Usage is implied by 'Add or tag tracked SEO keywords' and the merge behavior gives a hint about using it for additive tagging, but it never states when NOT to use it or points to the obvious alternative update-seo-keyword-tags for replacing/removing tags. The agent must infer the boundary from sibling names alone.

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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