nexo_context_packet

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

No annotations are provided, so the description must carry the burden. It discloses the return content (learnings, changes, etc.) and the mandatory before-delegation requirement. However, it does not explicitly state whether the tool has side effects or is read-only, leaving some behavioral ambiguity.

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 extremely concise: two sentences cover purpose, output, and usage. Every sentence adds value without redundancy, making it efficient for an agent to parse.

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 lack of output schema, the description compensates by listing the types of information returned. It provides necessary usage context and aligns with the sibling tool set. However, it omits potential error conditions or variations in output based on parameters.

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 100%, so the schema already documents parameters well. The description adds context by mentioning 'for a specific area' and linking to usage, but it does not elaborate on how the 'files' parameter modifies the output beyond the schema's description.

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 builds a context packet for subagent injection and lists the types of information returned (learnings, changes, followups, preferences, cognitive memories). It effectively distinguishes this from sibling tools like nexo_context_router by specifying the exact output and use case.

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 explicitly instructs that this tool MUST be called before delegating any task to a subagent and directs how to use the result (inject into the subagent's prompt). This provides precise when-to-use guidance and clear usage context.

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