Proof the buyback-and-burn flywheel is actually running: last burn (with BscScan tx), burns over the last 7/30 days, total bot runs — from the public audit log, every entry verifiable on-chain.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds beyond that by revealing the data source (public audit log) and the verifiability guarantee (every entry verifiable on-chain), which is useful behavioral context for trust and expectations.
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?
One dense sentence, front-loaded with the core purpose and then specific data points. No filler or repetition of schema information.
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 no-parameter, read-only lookup tool, the description provides everything an agent needs: what outcome the tool proves, which exact data points will appear, and the source/verifiability context. No output schema exists, but the listed outputs largely compensate.
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?
There are zero parameters and schema coverage is 100%, so the description carries no parameter burden. The 0-param baseline of 4 applies, and the description appropriately avoids inventing parameter-like details.
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 names a specific resource (the buyback-and-burn activity audit log) and enumerates concrete outputs: last burn with BscScan tx, 7/30-day burn totals, and total bot runs. This clearly separates it from siblings like bobai_burned and bobai_tokenomics, which cover different or narrower aspects.
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?
Usage context is implied: an agent would call this when someone asks for burn activity, flywheel proof, or recent buyback-and-burn metrics. However, the description never explicitly states when to prefer this over bobai_burned or other related siblings, nor does it mention exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools operate on overlapping data: bobai_burned, bobai_activity, and bobai_smart_money all report burn-related metrics, while bobai_token_info, bobai_circulating_supply, and bobai_burned overlap on supply numbers. The long descriptions mitigate this, but the purpose boundaries are less crisp than ideal. The BSC pool tools are more easily told apart.
Most token tools use a consistent bobai_* snake_case prefix, but the set mixes conventions: bnb_agent_*, bsc_pool_scan, find_agents_on_bnb_chain, and pancakeswap_fee_tiers break the pattern. The names are still readable and mostly noun-oriented. There is no chaotic mixing of camelCase or vague verbs, but the pattern is not uniform.
19 tools sits in the borderline heavy range for a token research server. Many are focused data views, but some could be consolidated, such as bobai_token_info with circulating supply/burned, or the informational guide/links/tokenomics cluster. Each tool has a defensible role, but the overall surface feels padded.
Core workflows are well covered: price, liquidity, DEX parameters, purchase guidance, burns, wallet balances, and BNB agent discovery. Missing historical price/volume, holder distributions, or detailed per-agent profiles, but these are minor gaps rather than dead ends. The server gives an agent what it needs to understand and interact with $BOBAI.