inject_context

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

No annotations are provided, so the description bears full responsibility. It discloses that injection auto-triggers /resume via dashboard and warns against trigger markers. Missing details on permissions, side effects, or reversibility.

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 four sentences, all substantive. It front-loads purpose, then gives usage context, a behavioral trait, and a warning. No redundant or wasted words.

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 4 parameters and no output schema, the description covers purpose, usage, behavioral traits, and parameter tips comprehensively. It answers likely questions about when and how to use the 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 100%, setting a baseline of 3. The description adds value by elaborating on each parameter: natural-sounding content, session fallback behavior, prune_orphans effect, and how to find conversation_id. This goes beyond the schema definitions.

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?

Description clearly states the tool injects context into the conversation as a new branch, with specific use cases: restoring after pruning or seeding a session. It distinguishes its purpose from sibling tools like prune_context and context_status.

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?

Provides clear 'when to use' guidance (after pruning, to seed knowledge) and a warning about prompt injection detection. However, it does not explicitly state when not to use or suggest alternatives among siblings.

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