list_project_training_packs

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description goes beyond this by clarifying that the output is reproducible candidate lineage only, and explicitly disavowing any production-write authority, training selection, or promotion actions, which reduces the risk of the agent treating this as a mutating capability.

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 action and resource, and the second sentence earns its place by defining the domain-specific concept and its limitations. The long negative list is somewhat dense, but it prevents misuse without adding redundant filler.

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 an output schema present and read-only/idempotent annotations, the description does not need to explain return values or safety. It provides a clear conceptual definition and boundaries, though it would be stronger with explicit guidance on when to prefer this tool over sibling list tools and a note on limit 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%, and the description adds no real meaning for project_id or limit beyond the phrase “the project's.” project_id is inferable from that phrase, but limit semantics, default behavior, or any constraints are left entirely undocumented.

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 opens with “Read the project's Learning Lab candidate-pack ledger,” a specific verb and resource. The second sentence defines exactly what a pack is (a pair of a worker-verified match and a human-admitted mission lesson), so the agent can distinguish this list operation from other learning-run or skill tools.

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 this tool is for inspecting candidate-pack lineage rather than for training runs, model updates, promotions, or production writes. It names several things the tool is not, but it does not explicitly say when to choose this tool over sibling tools such as list_project_learning_runs or list_project_skill_matches.

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