ingest_visual_qa_analysis

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

No annotations are provided, so the description must cover behavioral traits. It discloses validation, issue reporting, and that no fix is applied. However, it does not state whether the tool has side effects (e.g., storing data) or is idempotent, leaving some uncertainty.

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 concise: two sentences of purpose, then bullet-pointed args and returns. Every sentence adds value, and key info is front-loaded.

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 that an output schema exists, the description adequately summarizes return values (has_issues, issues, overall_quality) and the workflow. It lacks details on storage or error handling, but overall provides sufficient context for correct invocation.

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%, so the description fully documents parameters. It adds meaning: 'project_id' is Target project ID and required, 'slide_index' is 1-based, and 'analysis_json' is the client-generated JSON. This is clear and useful, though could detail the JSON structure.

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 states the tool ingests client-generated analysis, validates it, reports issues, and explicitly says 'No fix applied.' It also mentions the correct preceding step (prepare_visual_qa_analysis), distinguishing it from sibling tools like prepare_visual_qa_fix.

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 workflow guidance: 'Call AFTER prepare_visual_qa_analysis' and 'If has_issues, call prepare_visual_qa_fix...' No ambiguity about when to use.

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