inject_memories

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

With no annotations, the description adequately discloses key behaviors: cost (0.001 AIC per call up to 50 memories), return format (plaintexts), deflationary tokenomics, and optimistic mode. It does not mention side effects on the memory store or error handling, but covers the most important aspects.

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 concise (5 sentences), front-loaded with the core action, and contains no unnecessary information. Every sentence adds useful context.

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 tool with 3 parameters, no output schema, and no annotations, the description covers purpose, cost, behavior, and optimization. It explains what the tool returns (plaintexts) but lacks error conditions or prerequisite checks like balance requirements.

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% with clear parameter descriptions. The tool description adds no new semantic value beyond what the schema already provides for memory_ids, project_filter, and target_platform.

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 specific action (Inject selected memories into current conversation context), using a precise verb and resource. It distinguishes from sibling tools like chainmemory_remember or chainmemory_recall by focusing on injection into active context.

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 implies usage for injecting memories into conversation context but does not explicitly state when to use this tool versus alternatives. No exclusions or when-not-to-use guidance is provided.

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