Paper Distill MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the tool returns ('accumulated keywords and summaries from interests.jsonl') and mentions the loading behavior, but doesn't cover important aspects like error conditions, performance characteristics, or what happens if the file doesn't exist. The description adds some value but leaves gaps in behavioral understanding.

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 extremely concise with just three sentences, each earning its place: the core action, usage timing, and return value. It's front-loaded with the main purpose and wastes no words on redundant information.

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 has an output schema (which handles return values), 1 parameter with 100% schema coverage, and no annotations, the description provides adequate context about purpose, usage timing, and source data. However, for a tool that loads persistent data, it could benefit from mentioning error handling or data format expectations to be fully 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?

The schema has 100% description coverage, so the baseline is 3. The description doesn't directly discuss parameters, but it implies the parameter's purpose by mentioning 'If None, load all previous context' which aligns with the schema's description. This adds marginal semantic context beyond the schema, warranting a slightly higher score.

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 with specific verbs ('Load previous research context into current session') and identifies the resource ('interests.jsonl'). It distinguishes from siblings by mentioning 'init_session' as a prerequisite, but doesn't explicitly differentiate from all similar tools like 'ingest_research_context'.

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 clear context about when to use this tool ('Call this after init_session if user chose to load context'), giving a specific prerequisite and trigger condition. However, it doesn't mention when NOT to use it or explicitly compare with alternatives like 'ingest_research_context' among the sibling tools.

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