Compare production methods
compare_production_methodsReturn source-backed AI, CGI, live-action, and hybrid capability context.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | ru | |
| methods | Yes |
compare_production_methodsReturn source-backed AI, CGI, live-action, and hybrid capability context.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | ru | |
| methods | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds that results are 'source-backed' and scoped to four methods, but it does not disclose output structure, language behavior, or other operational details.
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 a single, efficient sentence with no filler or redundant restatement. It is slightly vague in wording but structurally sound and front-loaded with the key action and scope.
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?
The required methods parameter is reasonably self-explanatory, but the description leaves the return format unclear and omits the locale parameter entirely. Since there is no output schema, the agent receives minimal information about what 'capability context' actually contains.
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 needed to explain both methods and locale. It only restates the four method enum values and says nothing about locale, which has a default of 'ru' and would affect what the agent should expect in the response.
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 uses a specific verb ('Return') and references a concrete resource: source-backed capability context for AI, CGI, live-action, and hybrid methods. It distinguishes itself from the get_* siblings by focusing on production-method comparison, though 'capability context' is somewhat vague and comparison is not explicitly named.
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 gives no guidance about when to use this tool versus alternatives such as get_media_provenance or search_knowledge. The intended usage is only implied by the tool's name and title, with no explicit context or exclusions.
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.
Each tool targets a different public knowledge resource (cases, services, evidence, provenance, clients), so an agent can usually tell them apart. However, get_industry_experience overlaps with search_cases, and get_public_evidence versus get_media_provenance could be confused without careful reading.
All tool names follow a consistent snake_case verb_noun pattern, with get_ as the dominant verb and list_/search_/compare_ as clear variants. No camelCase or inconsistent verb styles appear.
15 tools sits at the upper edge of a well-scoped read-only knowledge server. Each tool has a distinct purpose, but a few could be consolidated (e.g., industry experience as a search_cases filter) without losing capability.
The surface covers the main public knowledge workflows: service catalog, cases, evidence, provenance, pricing, clients, and production context. Minor gaps exist, such as no direct get_claim stable-identifier lookup and no list_cases endpoint, but search_knowledge and search_cases provide workarounds.