scoring-rule-upsert
Upsert a scoring rule
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| profileId | Yes | Scoring profile UUID | |
| __requestBody | Yes | Request body |
Upsert a scoring rule
| Name | Required | Description | Default |
|---|---|---|---|
| profileId | Yes | Scoring profile UUID | |
| __requestBody | Yes | Request body |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral information beyond the annotations. While annotations indicate idempotentHint=true and destructiveHint=false, the description does not explain what 'upsert' entails (e.g., whether it creates new rules, updates existing ones, or both) or any side effects such as overwriting existing rule configurations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short, but this is under-specification rather than concise writing. It consists of a single tautological sentence that adds no value; a useful description would include details about the request body and upsert behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a complex nested request body (five answer types, multiple point-value modes, enum constraints) and no output schema, a one-line description is wholly inadequate. The description gives no information about required fields, validation rules, or how upsert semantics apply, making it impossible for an agent to correctly construct an invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with detailed parameter descriptions for profileId and the nested request body properties (e.g., answerType drives shape validation). The description itself provides no parameter information, but the schema fully compensates, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Upsert a scoring rule' simply restates the tool name 'scoring-rule-upsert' in sentence form, providing no additional detail about the specific behavior, scope, or how it differs from sibling tools like scoring-rule-delete or scoring-rule-list. It is a tautology rather than an informative purpose statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives, no prerequisites, no exclusions, and no mention of related tools that could achieve similar outcomes (e.g., scoring-assignment-create for assigning rules). With no usage context, an agent cannot determine appropriate invocation scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as signals-firmographics vs companies-enrich_firmographics, findEmail vs contacts-enrich_work_email, and monitors vs signal_subscriptions vs market_signals. While descriptions add some context, an agent could easily select the wrong tool due to the high similarity in function.
Most tools use a resource_subresource-action pattern, but there are inconsistent separators: underscores within some names, hyphens in others (e.g., scoring-assignment-bulk-create), and several camelCase exceptions (findEmail, findEmailBatchGet, getContactResearchByExternalID). This mixed convention makes the tool set feel unpredictable.
With 119 tools, this server vastly exceeds the typical well-scoped range. Even for a comprehensive B2B data platform, the sheer number creates cognitive overload and increases the risk of incorrect tool selection.
The server covers an extensive range of operations: enrichment, lists, contacts, signals, subscriptions, monitors, and scoring. Nearly every resource has create, read, update, and delete or lifecycle equivalents, leaving very few practical gaps for the intended use case.