Astria-Index

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

No annotations provided, so description carries full burden. Discloses ranking algorithm (frequency-based), reliability interpretation, and empty state behavior ('Returns an empty list if no insights recorded yet'). Minor gap: doesn't explicitly declare read-only/safety characteristics, though implied by 'browse'.

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?

Well-structured with clear sections (opening statement, ranking logic, usage bullets, Args, Returns). Content is dense and relevant. Slightly verbose with four usage examples when two might suffice, but each adds distinct context (debugging vs onboarding).

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 simple 1-parameter tool, description is complete. Documents return structure (pattern, cause, solution, confidence, count) despite lack of structured output schema. Behavioral expectations (ranking, empty state) are covered.

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 0% (limit parameter has no description field). Description fully compensates by defining limit as 'Maximum insights to return', confirming default (20), and crucially specifying max constraint (50) absent from schema.

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?

Opens with specific verb 'Browse' and clear resource 'discovered cause-and-effect patterns'. Distinct from sibling 'record_insight' (implied write counterpart) and 'list_memories' (raw vs processed insights) by specifying these are ranked, reliability-indicating patterns.

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 this when:' section lists four specific scenarios including debugging prep, similarity checking, knowledge base building, and onboarding. Includes concrete example invocation `my_insights(limit=10)` demonstrating intended usage pattern.

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