workflow_get_paper

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

Without annotations, the description carries full burden. It details the return structure including a 'found' bool and possible empty fields ('fulltext may be empty'). No contradictions, but could mention error handling or performance traits.

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?

Front-loaded with purpose, then usage, parameters, and return format. Every sentence earns its place; no redundancy. Ideal balance of detail and brevity.

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 one parameter, no output schema, but rich return format described with sample JSON. Covers all needed info for analysis: metadata, fulltext, annotations, existence flags. Adequate for an LLM to use effectively.

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 single parameter 'identifier' lacks schema description (0% coverage), but the Args section adds rich meaning: examples (Zotero key, citekey, DOI, title keywords) far exceed schema.

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?

Clearly states the verb 'Retrieve' and resource 'everything needed to analyze a paper' including metadata, full text, and PDF annotations. Explicitly positions as first step before generating a literature note, distinguishing it from sibling tools like workflow_get_note.

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?

Provides explicit context: 'Use this as the first step before generating a literature note.' While it does not list alternatives or when not to use, the context is clear and sufficient for guiding the agent.

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