Paper Distill MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavioral traits. It mentions actions like updating paper statuses and appending to files, which implies mutation and side effects, but doesn't specify permissions needed, whether changes are reversible, or error handling. For a tool with significant side effects, this is inadequate transparency.

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 highly concise and well-structured: two sentences that front-load the core purpose and then detail the specific actions and return value. Every sentence adds essential information without redundancy, making it efficient for an agent to parse.

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 complexity (a multi-step mutation tool), lack of annotations, and presence of an output schema, the description is moderately complete. It outlines the tool's actions and return value, but gaps remain in behavioral transparency and usage guidelines. The output schema likely covers return values, so the description doesn't need to explain those.

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 100%, so the schema already documents both parameters thoroughly. The description adds minimal value by mentioning 'AI's review response' for 'selections' and implying a finality context for 'is_final', but doesn't provide additional syntax or format details beyond the schema. This meets the baseline for high schema coverage.

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's purpose: 'Process AI review decisions, update pool, and generate push output.' It specifies the verb ('process', 'update', 'generate') and resources ('AI review decisions', 'pool', 'push output'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'send_push' or 'pool_status', which prevents a perfect score.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a prepared review from 'prepare_review'), exclusions, or comparisons to siblings like 'send_push' (which might handle push output differently). This leaves the agent without context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.