List every work published in a given year. Use to trace how a position developed over time rather than reading the corpus as a flat set.
| Name | Required | Description | Default |
|---|---|---|---|
| year | 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, openWorldHint, idempotentHint, and destructiveHint, which cover the behavioral safety profile. The description adds the nuance that it returns every work for a year and the rationale for chronological tracking, but no further details like pagination or ordering.
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 two sentences long, front-loaded with the action and then the usage context. It is concise but could potentially include more parameter details without being overly verbose.
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?
Given the tool's simplicity (one parameter, output schema present, low complexity), the description covers the main purpose and use case adequately. It lacks parameter specifics but remains functional for an agent.
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 burden is on the description to explain the 'year' parameter. However, the description only mentions 'given year' without specifying format, range, or constraints, leaving ambiguity despite the integer type.
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 lists every work published in a given year, with a specific verb and resource. It differentiates from siblings like search_papers and corpus_overview by providing a use case: tracing a position over time.
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 explicitly advises when to use this tool (to trace development over time) rather than reading the corpus as a flat set. It implies not for general searches or overviews, though it does not list explicit alternatives.
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.