Search the blog for shorter, faster-moving analysis. Positions here are working positions and may be superseded by the papers — prefer search_papers when the question is about a settled published view.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | 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=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds no behavioral context beyond purpose and guidance, which is acceptable but not additive.
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?
Two sentences, front-loaded with purpose, no wasted words. Highly efficient.
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 description covers purpose and usage guidelines. It does not mention output, but an output schema exists. Minimal gap given tool simplicity and annotation richness.
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%, and the description does not explain param meanings. 'query' and 'limit' are self-explanatory from schema names, but with zero coverage the description should compensate; it does not.
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 clearly states the tool searches blog posts for 'shorter, faster-moving analysis' and distinguishes it from search_papers for settled views. This provides a specific verb+resource and explicit sibling differentiation.
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 explicit when-to-use (shorter analysis) and when-not-to-use (settled views, prefer search_papers). It names the alternative tool and provides context for choice.
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 distinct resource or action: overviews, specific claims/papers, searches by different granularities, citation help, and document verification. No two tools overlap in purpose.
All tool names use lowercase snake_case with clear verb-noun or noun-preposition patterns (e.g., get_claim, search_papers, claim_layer_overview). The naming is uniform and predictable.
With 11 tools, the set covers the core operations for exploring a scholarly corpus without being excessive. Each tool serves a clear and necessary purpose.
The tools provide comprehensive coverage for discovering, retrieving, and verifying content from the corpus: overviews, searches at paper/claim/post level, direct retrieval, and document verification. No obvious missing operations for the intended use case.