get_similarity_match

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

No annotations were provided, so the description carries the full burden. It discloses the return format ('hypernatt_similarity_match_v1 with matches[]'), cost structure ('1 credit / free tier / quota / $0.01 x402 Base'), side effects ('none'), and explains how parameters affect behavior (e.g., full_payload returns full feature vectors). It also clarifies payment/authentication mechanisms via x_payment and agent_wallet.

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 (5 lines) and uses keywords (USE WHEN, NOT WHEN, RETURNS, COST, Side effects) to improve scanability. Every sentence adds value. However, it could be slightly better structured by breaking the opening sentence from the guidelines. Overall it is efficient and 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 the tool's complexity (3 optional parameters, no output schema), the description adequately explains return values, cost, side effects, payment handling, and parameter behavior. It provides sufficient context for an agent to decide when to use and what to expect. The lack of an output schema means the description must cover return structure, which it does well.

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 100% with each parameter having a description. The description adds meaning beyond the schema by explaining use cases: e.g., for x_payment 'Omit to receive 402 payment instructions' and for agent_wallet 'Skips x402 when quota covers credit weight.' This provides context that helps the agent decide how to invoke the tool correctly.

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 clearly states that the tool retrieves top-3 historical regime matches for BTC microstructure with observed 4-hour outcomes. It uses a specific verb ('get'), resource ('similarity match'), and scope ('BTC microstructure'). It also distinguishes itself from siblings like get_mm_trap_state and get_btc_usdc_signal by providing explicit NOT WHEN guidance.

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 explicitly states 'USE WHEN: analogies / regime context' and 'NOT WHEN: live trap (get_mm_trap_state) or vault cycle (get_btc_usdc_signal).' This provides clear context for when to use the tool versus alternatives, with named sibling tools.

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