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

No annotations are provided, so the description carries the burden. It discloses the monitoring behavior, the 20-voice cap, the lexicon-scored sentiment, and convergence detection. However, it does not disclose whether this is a read-only operation, whether it creates subscriptions or side effects, rate limits, or what happens when voices are invalid or exceed 20. The description adds meaningful behavioral context but leaves the safety profile undisclosed.

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 a single sentence that front-loads the core action (monitor voices) and packs in the key outputs. It is efficient and every clause earns its place. It could be slightly more structured (e.g., separating the output metrics into a list), but it is not bloated or repetitive.

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 monitoring tool with no output schema and no annotations, the description covers the main inputs and outputs but omits important operational details: whether the tool is read-only, how results are returned (streaming vs. one-shot report), what happens if more than 20 voices are provided, and whether there are rate limits or authentication requirements. The sibling tools suggest a research context, but the description alone is not fully complete for an agent to invoke it without further assumptions.

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 schema already documents all three parameters. The description adds context by explaining the voice ID format (tg:, bs:, x:) and the default behavior for tokens (every cashtag found), which goes slightly beyond the schema. However, it doesn't explain the hours parameter's default beyond the schema's 'default 24' or clarify edge cases like overlapping tokens. Baseline 3 is appropriate because the schema does the heavy lifting and the description adds only marginal value.

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 ('Monitor') and names the exact resource (up to 20 user-selected voices from Telegram public channels and X handles) and the outputs (tokens mentioned, lexicon-scored sentiment, conviction, urgency, convergence). It clearly distinguishes itself from the sibling tools (news_verify, price_crosscheck, technicals_crosscheck) by focusing on narrative convergence across social voices.

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 when to use this tool: when you need to track which tokens multiple voices mention and whether they converge on a narrative. It does not explicitly state when not to use it or name alternatives, but the sibling tool names and the description's focus on social voices make the use case clear. A small gap: no explicit exclusion like 'for price verification use price_crosscheck'.

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