suggest_next

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

With no annotations, the description carries the full burden; it does disclose the ranking signal (frequency plus recency) and, valuably, that output is non-authoritative about correctness or safety. It still omits side-effect/read-only status, scope of 'recent history', and result shape.

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?

Two compact sentences with zero filler: the mechanism is front-loaded and the safety caveat follows immediately. Every clause carries information an agent needs.

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?

For a four-optional-parameter read tool with no output schema, the description conveys what the result conceptually is and warns about its epistemic limits. It could say slightly more about the returned row structure (the detail flag hints at directory/duration/executor/session), but nothing critical for invoking it is missing.

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 description coverage is 100%, so the schema already documents limit, detail, offset and directory including defaults and the next_offset paging pattern. The description adds no parameter-level meaning beyond that, so the baseline 3 applies.

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?

States the resource (commands) and the exact selection mechanism (statistically likely next, ranked by frecency over recent history), which cleanly separates it from search_commands and recent_commands. It isn't framed with a leading verb, but the intent is unambiguous.

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 caveat 'a guess about habit, not a recommendation' implies the when-not condition (don't treat suggestions as validated choices), implicitly pointing toward risk-aware siblings like assess_risk. However, no alternative tool is named and no explicit trigger for using this tool is given.

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