Resume

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

The description discloses the effect ('canonical mutation'), idempotency constraints ('no client idempotency key; do not retry'), human approval (not required for read/staging), and detailed error paths ('On failure: login_required → login;...'). Annotations are sparse but consistent; the description adds essential behavioral context beyond them.

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 clear headings ('Use when', 'Then', 'On failure', etc.), making it easy to scan. However, it is somewhat verbose, containing repetitive phrases like 'project-scoped' and 'API-authorized'. Could be tightened without losing information.

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 the tool's complexity (11 params, 0 required, has output schema, many siblings), the description is remarkably complete: it covers prerequisites, errors, post-action steps, and references the output schema. Little is left to inference.

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 45%, leaving many parameters undocumented in the schema. The description does not add parameter-level semantics beyond the schema; it focuses on usage and error handling. Without parameter details, tool invocation may be unclear for some parameters. A moderate score reflects minimal added value for parameters.

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 creates a 'project-scoped resume context package' for continuing the AI chat, distinguishing it from sibling tools like recall or handoff. The verb 'Create' and resource 'resume context package' are specific. It implies a distinct purpose among many sibling 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?

Explicit 'Use when' and 'Do not use when' sections provide clear guidance on appropriate use cases and exclusions. Additionally, it lists prerequisites ('authenticated API authority', 'selected Project') and postconditions ('Then: follow typed result state').

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