pyocd_memory_dump

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

No annotations are provided, so the description must compensate. It does not disclose any behavioral traits such as idempotency, memory impact, or prerequisites beyond the purpose. The minimal information provided is insufficient for a thorough understanding of side effects.

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 a single sentence that effectively communicates the tool's function and purpose. It is front-loaded with the verb 'dump' and the format details, with no wasted words.

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 two parameters and existence of an output schema, the description adequately covers the essentials. It could briefly mention the line format or include a note about large dumps, but overall it is sufficient for a simple tool.

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 has 100% description coverage, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides for parameters 'address' and 'length'.

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 dumps memory in hex dump format, specifying the output includes address, hex bytes, and ASCII. It distinguishes from sibling tools like pyocd_memory_read by the formatted output.

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 mentions it is useful for inspecting data structures, which implies usage context, but does not explicitly guide when to use this tool versus alternatives like pyocd_memory_read for raw bytes.

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