perf_c2c_report

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

No annotations exist, so the description carries the full burden. It discloses what the tool does (HITM analysis), key parameter behaviors, output structure, and a prerequisite ('perf record -d -a'). It does not describe error handling or exit codes, but for a read-only analysis tool, this is sufficient.

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 concise, starting with a clear definition, then usage guidance, key parameters in a bulleted list, output summary, and a prerequisite. Every sentence contributes information without redundancy.

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 (21 parameters, output schema), the description provides essential context: purpose, usage scenario, key parameters, output format, and prerequisite. It does not explain every parameter, but the schema already covers those. The description adds context that is not available elsewhere, making it complete enough for an AI agent to select and invoke the 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 already describes all 21 parameters, achieving 100% coverage. The description adds extra meaning for key parameters like display (explaining 'tot', 'lcl', 'rmt' values), coalesce (example grouping), stats, and call_graph, going beyond the schema's minimal descriptions. This added value justifies a score above baseline.

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 identifies the tool as a cache-to-cache false sharing analysis, specifically detecting cache lines with the most HITM events. This distinguishes it from sibling perf tools like perf_mem_report or perf_report, which focus on different aspects of memory and performance analysis.

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?

It explicitly states when to use the tool: to diagnose multi-threaded performance issues from false sharing. However, it does not mention when NOT to use it or point to alternatives. This is clear usage context but lacks explicit exclusions or alternative recommendations.

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