append_skill_memory

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

With no annotations beyond the title, the description carries the transparency burden. It discloses that the operation appends to per-skill memory and never modifies the built-in skill body, which is key behavioral context. However, it does not mention idempotency, permissions, or response behavior, which would make it more transparent.

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 structured with a brief purpose statement, a usage paragraph, and an Args list. It is front-loaded and each sentence contributes value. Some redundancy exists (e.g., 'append it here' and 'Save a learning'), but overall it is concise and well-organized.

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 and no output schema, the description provides essential context: the workflow (after skill completion, with user confirmation), the target (per-skill memory), and the two key params. The config parameter is unexplained, but since it's optional and has a default, the omission is minor. The tool is otherwise sufficiently described.

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?

The schema has 0% description coverage, so the description must compensate. It explains skill_id ('The skill the learning belongs to') and text ('The learning/workaround/preference to remember') with useful detail. However, the 'config' parameter, though optional, is entirely unexplained, leaving a gap in the parameter semantics.

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 tool's function: 'Save a learning to a skill's MEMORY — the self-learning loop.' It specifies the verb 'append' and the resource (skill memory), and distinguishes from siblings by noting it works for built-in skills without modifying the skill body.

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 explicit guidance on when to use the tool: after completing a skill, ask the user for confirmation, then append. It also clarifies that it works for built-in skills. However, it does not explicitly mention alternatives like get_skill_memory or compact_skill_memory, so it falls short of full exclusion guidance.

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