set_review_visibilityChange one authenticated-user-owned review to private, unlisted, public or aggregate_only using its stable experience_id. Use a preceding list_reviews_by_visibility result to translate conversational list numbers back to stable IDs. Setting public also ensures publication_status=published.
| Name | Required | Description | Default |
|---|---|---|---|
| visibility | Yes | ||
| experience_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare non-read-only, idempotent, non-destructive behavior. The description adds meaningful context: only authenticated-user-owned reviews can be changed, stable IDs are required, and setting public also forces publication_status=published. It does not explain side effects for the other visibility values, but it goes well beyond the structured annotations.
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?
Three tightly written sentences with no wasted words. The core action comes first, followed by the practical ID-resolution workflow and then the non-obvious publication side effect. Everything present adds value.
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 mutating tool with no output schema, the description covers the essential invocation context: the resource scope, the auth constraint, the source of the ID, and a non-obvious side effect. The main gaps are the meanings of unlisted and aggregate_only, and what happens to publication_status when moving away from public, but these are not blocking for correct tool selection.
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?
With 0% schema description coverage, the description must explain parameters itself. It does clarify that experience_id is a stable identifier and explains how to obtain it from list_reviews_by_visibility. It also adds behavior for visibility=public. However, it does not define the semantics of unlisted or aggregate_only beyond listing the enum values.
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?
States the exact operation ('change review visibility'), the resource ('one authenticated-user-owned review'), and the allowed visibility values. The mention of a stable experience_id helps distinguish this tool from list-oriented review tools and suggests a precise, single-review scope.
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?
Provides a clear prerequisite workflow: use list_reviews_by_visibility first to map conversational list numbers to stable experience_id values. It does not explicitly discuss when to prefer save_experience or other siblings, but the core usage context is unambiguous.
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.
Most tools are separated by resource and action, but the classification cluster (affirm_subject_classification, propose_subject_reclassification, reopen_subject_classification, get_subject_classification) and the three resolve_subject* tools require close reading to distinguish. Long descriptions help, but an agent could easily pick the wrong member of those clusters.
The dominant pattern is verb_noun in snake_case (create_deliberation, list_reviews_by_visibility, resolve_subject_type, set_review_visibility). Minor deviations such as bare 'fetch' and 'search' and mixed verbs like affirm vs propose vs reopen are readable and do not break the convention.
34 tools substantially exceeds the 25+ threshold even for a server with multiple subdomains. The many classification, type, and location variants add cognitive load, and several could be consolidated or hidden behind a smaller workflow-oriented surface.
The set covers the main lifecycles: review save/fetch/assess/delete/visibility, subject resolution/enrichment/correction, classification with voting/reopening, deliberations, locations, and vocabulary management. Minor gaps remain, such as no direct full-subject getter and no update to review text, but these appear intentional in an immutable-review design.