gauge_demand_live

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

With no annotations, the description carries the full burden and does so thoroughly: it discloses the $0.10 x402 cost, live Reddit search up to 50 posts, one LLM synthesis call, ~45s budget, timeout → no-charge 504, USDC-on-Base payment, compute-first/settle-after model, and EVM_PRIVATE_KEY requirement. This is exemplary operational transparency.

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?

Though dense, every sentence conveys a distinct operational fact—cost, live source, budget, parity with gauge_demand, timeout handling, payment settlement, and key requirement. No filler or redundancy; the structure is an efficient single paragraph.

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?

There is no output schema, but the phrase 'Same verdict shape as gauge_demand' anchors the return format to a sibling tool, which mitigates the gap. The description covers pricing, auth, timeout, and error behavior well, though it could be even more explicit about the actual verdict fields.

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?

The schema already documents both parameters at 100% coverage, so the baseline is 3. The description adds meaningful context that the query drives a live Reddit search and corpus match, clarifying how the query is actually used beyond the schema text.

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?

Clearly defines a demand-gauge tool backed by a LIVE Reddit search, and explicitly distinguishes it from the cached sibling gauge_demand via 'Same verdict shape as gauge_demand (cache always miss)'. The verb and resource are specific and the live-vs-cached contrast is immediately apparent.

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?

Names gauge_demand as the alternative and implies this tool is for live-demand situations by noting the cache always misses and that a live Reddit search is performed at request time. However, it stops short of an explicit 'use this when' statement or exclusion criteria.

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