memory_detect_supersessions

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

Despite no annotations, the description fully discloses behavior: it uses LLM classification without timestamp bias, creates 'supersedes' edges, supports a dry-run mode, and mentions a 120-second rate limit. This provides comprehensive behavioral insight beyond the schema.

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 well-structured with a summary line, process explanation, parameter list, return description, and rate limit note. Each sentence is informative, and there is no redundancy or extraneous text.

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?

The tool has 5 optional parameters with defaults, an output schema (not depicted but described), and a single algorithm step. The description covers the what, why, how, and constraints (rate limit), making it complete for confident invocation. The mention of memory_absorb further enriches context.

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?

Input schema has 0% description coverage, but the description lists each parameter with default values and explanations (e.g., 'min_similarity: Minimum embedding similarity to consider'). This adds necessary meaning that the schema alone lacks.

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 begins with 'Detect memories that supersede (update/replace) other memories,' which is a specific verb-resource combination. It clearly distinguishes from the sibling tool memory_absorb by stating it complements it, making the purpose 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?

It explicitly mentions memory_absorb as an alternative that 'only catches supersessions at write time,' guiding the agent to use this tool for historical or retrospective detection. The description also explains the scanning and edge creation process, providing clear context for when to invoke this tool.

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