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

With no annotations, the description carries the full behavioral burden and does well: it discloses persistence semantics (Supabase-backed vs in-memory fallback) and describes return contents (artifact URLs, channels, execution modes, measurement state). It does not explicitly state read-only behavior, but 'query' implies it; still, a clear 'does not modify data' statement would strengthen this.

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 compact, front-loaded with the tool's core purpose, and uses exactly three sentences to convey purpose, usage triggers, return content, and persistence behavior. Every sentence adds value; there is no redundant or filler text.

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 query tool with 5 optional parameters, no output schema, and no annotations, the description covers the main context: what it returns, when to use it, and behavioral persistence. It does not mention result ordering or default limit, but the schema provides default limit and the description gives a solid overall picture, making it largely complete.

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 100%, so the baseline is 3. The description does not add per-parameter meaning; it merely references the ledger query context. The schema already explains each parameter's purpose, so the description adds little beyond the structured field definitions.

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 uses a specific verb ('query') and resource ('persistent proof ledger'), and clearly explains the tool's output with concrete examples of user intents ('what has ChiefLab actually shipped?', 'show me the launch history'). It distinguishes itself from sibling tools by focusing on the ledger of executed publishes/sends/manual-posts rather than actions like checking due measurements.

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 gives explicit 'USE WHEN' scenarios with example user phrasings, making it clear when to invoke the tool. However, it does not explicitly state when not to use it or name alternative tools, so it misses the full 'when-not/alternatives' tier.

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