Search SHAR public knowledge
search_knowledgeSearch canonical public services, cases, and claims with source lineage.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | ||
| locale | No | ru |
search_knowledgeSearch canonical public services, cases, and claims with source lineage.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | ||
| locale | No | ru |
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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful context by specifying 'canonical' and 'source lineage,' but it does not explain result behavior, pagination, or locale effects. No contradiction with 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?
A single sentence with no filler, front-loading the verb and resource. 'Canonical' and 'source lineage' add useful nuance without bloat.
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 tool is simple, but with no output schema and no parameter guidance, the description leaves some gaps. It clarifies what is searched and the provenance feature, but not what results look like or how query/locale/limit affect the response. Adequate but not complete.
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 0%, so the description needed to compensate by explaining query, limit, and locale semantics. It does not mention any parameter; it relies on the self-explanatory parameter names. The locale enum and query matching behavior remain undocumented.
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, 'Search,' and names the resource: 'canonical public services, cases, and claims with source lineage.' This differentiates it from narrower siblings like search_cases, though it doesn't explicitly name an alternative. The scope is clear and actionable.
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 implies usage for broad lookups across public services, cases, and claims, but it does not explicitly state when to choose this over search_cases or other sibling search tools. No exclusions or alternative routing guidance is provided, so usage context is only implied.
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.