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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the safety profile is covered. The description adds real semantic context beyond that: default ordering for empty queries and, notably, that evidence labels distinguish reproduced work, documented implementations, author demos and analysis methods without implying compatibility with similar-looking hardware — an important caveat to prevent over-trust. It says nothing about result volume or how the limit interacts with results, but the value added is substantial.

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?

Three sentences, front-loaded with purpose and the default-ordering behavior, then the evidence caveat. Every sentence carries information; there is no filler.

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?

Annotations and an output schema reduce the burden, and the evidence caveat is a good addition. Still, for a 7-parameter search tool with only 43% schema coverage, the description leaves out how the filters combine and what differentiates it from sibling discovery tools, so it is adequate but incomplete.

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?

Schema coverage is 43%, so the description must compensate. It partially does for the evidence filter by explaining what the labels mean, which is genuinely useful. But method, category, use_case, and limit are undocumented in the description, leaving over half the parameters explained only by terse enum values.

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 names a specific verb and resource: 'Search Hackshop's curated hardware reverse-engineering examples and research methods.' An agent can tell this is a discovery/search tool rather than an assessment or planning tool. However, it does not explicitly distinguish itself from the closest sibling, find_firmware_playbooks, leaving that boundary to inference.

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 'with no query, returns the newest dated examples first' clause implies a browse-when-no-query usage pattern, but the description never states when to prefer this tool over find_firmware_playbooks or assess_hackability. Usage is implied rather than stated, and there are no exclusions.

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