mcp_engram_update_with_tensor_bond

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

With no annotations, the description carries full burden. It discloses the composite flow (recall-first, update, bond, optional scar), return types, and the scar_on_mismatch behavior. However, it does not explain failure modes (e.g., what if recall fails), auth requirements, or rate limits. The behavioral description is good but not exhaustive.

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 front-loaded with the core purpose and negative guideline, followed by two concrete examples. It is somewhat lengthy due to the examples, but each sentence adds value. The structure is clear and easy to parse, though it could be trimmed slightly without losing meaning.

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 no output schema, the description covers return values (crs_delta, tensor_pattern, lineage). It explains the composite operation flow and optional scar behavior. However, it omits error conditions (e.g., concept not found), prerequisites, and side effects beyond the update. The examples compensate partially but not fully.

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 all 6 parameters. The description adds contextual flow meaning (recall-first, update, bond) but does not elaborate on individual parameter semantics beyond what the schema provides. The examples illustrate parameter usage but do not add new semantic detail. Baseline 3 is appropriate.

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 it is a 'SAFE composite for memory updates' combining recall-first, update, tensor bond, and optional scar. It explicitly lists return values (crs_delta, tensor_pattern, lineage) and distinguishes from using forget+remember. The verb and resources are specific and unique among siblings.

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 provides a clear negative guideline ('NEVER use forget+remember to mutate') and includes two detailed few-shot examples showing concrete when-to-use scenarios. It implies this tool is for composite updates with tensor bonding, but it does not explicitly list alternatives or state prerequisites (e.g., concept must exist).

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