get_console_log

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

With no annotations, the description carries the full burden and does well: it reveals the ephemeral nature of logs ('only sees what was logged since that tab loaded'), the need for a connected tab, and that extension import errors are only console.error'd, making this the sole record. It could go further by describing the output structure, but an output schema exists, so the return format is covered elsewhere. The description adds meaningful behavioral context beyond the schema.

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 well-structured and front-loaded with the core purpose, followed by context, limitations, and an Args list. While it contains extra explanatory prose about node architecture, every sentence adds value by distinguishing this tool from alternatives and explaining why it exists. It is slightly longer than strictly necessary but not wasteful, earning a 4 rather than a 5.

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 moderate complexity (5 parameters, no annotations, output schema present), the description is remarkably complete. It covers purpose, usage scenario, prerequisite, data scoping, and all parameter semantics. The only missing piece would be concrete examples, but they are not essential for a read-only log retrieval tool. The description fully equips an agent to select and invoke this tool correctly.

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 only provides titles and defaults, with 0% description coverage. The description compensates fully by explaining each parameter in plain language: lines (how many recent matching entries, 0 for all), level (severity filter with allowed values), search (case-insensitive text filter), regex (treat search as regular expression), and client_id (which tab). This adds clear meaning beyond the schema titles.

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 opens with a specific verb and resource: 'Read the browser console - the frontend half.' It explicitly distinguishes itself from sibling get_comfy_log by explaining that it answers a different question about frontend extension failures. The purpose is unmistakable and well-scoped.

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 clearly contrasts with get_comfy_log, stating 'it answers a different question' and details the scenario where a JavaScript half fails while the Python half succeeds, making this the only tool that can see such failures. It also notes a prerequisite: 'Needs a connected tab' and warns that only logs since tab load are visible. This gives explicit when-to-use and behavioral context.

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