write_bookmark_analysis

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

With no annotations, the description must disclose behavior, and it does add a key behavior: merge semantics, preserving existing data. It also clarifies that the agent performs the analysis (not the tool). However, it doesn't mention potential side effects, permissions, or error conditions, so the behavioral transparency is moderate.

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, efficiently front-loaded with the primary purpose. It avoids repeating schema details and earns its place by adding the merge behavior and agent workflow context. There is no unnecessary verbosity.

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 complexity (nested object with multiple optional fields) and the absence of an output schema, the description provides sufficient context: it clarifies the write intent, the merge behavior, and the agent's role. It could mention validation or return behavior, but for a write tool, the current description is largely adequate.

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 input schema already provides detailed descriptions for both parameters and all nested fields (100% coverage). The description adds value by explaining the merge semantics, which clarifies that only provided fields in the 'analysis' object are written, and existing fields are retained. This goes beyond the schema's per-field descriptions and is critical for correct usage.

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 a specific verb and resource: 'Write AI analysis results into a bookmark.' It further distinguishes itself by explaining the agent workflow ('Agent analyzes content with its own LLM, then writes structured results back to Burn'), which is unique among the sibling tools and clarifies the tool's role in the system.

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 for when to use the tool: after the agent has analyzed content, it writes the results back. It also gives an important usage guideline: 'Only provided fields are merged — existing data is preserved,' indicating partial updates. While it doesn't explicitly name alternatives, the sibling list shows this is the only write-analysis tool, so the usage context is clear.

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