mem_provenance

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

No annotations are present, and the description does not disclose behavioral traits such as read-only nature, authentication needs, rate limits, or side effects. It only states what is returned, not the tool's operational characteristics.

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 a single, efficient sentence that immediately communicates the action and resource. While concise, it sacrifices explanatory depth, but for a tool with one parameter, it is appropriately sized.

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?

With no output schema, no annotations, and a single parameter, the description should explain the return value and any constraints. Terms like 'audit provenance' and 'original turn context' are undefined, leaving an agent uncertain about the tool's output and behavior.

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 description coverage is 0%, yet the description does little to explain the observation_id parameter beyond implying it identifies an observation. It fails to clarify the format, source, or how to obtain valid IDs, which could lead to invocation errors.

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 action ('Return audit provenance') and the specific resource ('for one stored observation'), including additional detail ('original turn context'). It distinguishes from sibling tools like mem_get (which likely returns the observation itself) and mem_search (which finds observations).

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, typical use cases, or conditions that would make provenance retrieval appropriate compared to other mem_ tools.

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