recall_memory_tool

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

No annotations exist, so the description carries the burden, and it delivers non-obvious behavior: default freshness filtering ('clusters below min_freshness are hidden') and the include_stale override. It does not address auth, rate limits, or what a 'cluster' is, but the output schema covers returns.

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 short sentences, front-loaded with the primary behavior and each carrying distinct information. No filler or repetition.

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 3-param, dual-mode retrieval tool with an output schema handling return values, the description covers modes, filtering, and overrides adequately. The main gap is no differentiation from sibling retrieval tools like fetch_cluster_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?

Schema coverage is 0%, so the description must compensate, and it does: query triggers semantic recall, min_freshness sets the hiding threshold, and include_stale overrides the filter. All three parameters gain meaning beyond the bare 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?

States a specific verb and resource ('List long-term memory clusters') with scope ('ranked by freshness score') and a second mode ('semantic recall'). Clear enough to distinguish from search_* siblings, but never names or contrasts a sibling such as fetch_cluster_tool.

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?

Explicitly tells the agent when to switch modes: 'Pass query to run semantic recall instead of listing.' This gives a real decision rule. It stops short of when-not guidance or routing to sibling retrieval tools.

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