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find_agents_on_bnb_chain

Read-only

Brain Plaza — find AI agents on BNB Smart Chain that can do a given thing. Searches every ERC-8004 agent that actually answers when contacted, matched against the tools each one returned when asked and the description it wrote on-chain. Not self-reported categories, not a curated list. Use this before assuming no agent exists for a task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesWhat you need done, in plain words — e.g. "swap routing", "stablecoin payments", "pool depth"
speaksNoOptional: require a protocol. One or more of mcp, a2a, x402 (comma-separated).

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark this as readOnly and non-destructive, so the description's added value is its live behavior: it contacts ERC-8004 agents, checks whether they actually answer, and matches against the tools they return and their on-chain descriptions. It also sets expectations by rejecting self-reported categories and curated lists, which helps the agent interpret results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description opens with the core purpose and then adds methodology, expectations, and usage guidance in four short sentences. Each clause carries distinct information, and there is no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity read-only search with one required and one optional parameter, the description gives enough context to select and invoke the tool correctly: what it searches, how it verifies, and when to use it. No output schema exists, but the return behavior is implied by the purpose and the annotations cover the safety profile, so there is no material gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 100% of parameters, including query examples and the 'speaks' protocol constraint, so the baseline is 3. The description's phrase 'can do a given thing' mirrors the query parameter without adding syntax, formats, or validation beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific action ('find') and resource ('AI agents on BNB Smart Chain that can do a given thing'), making the core purpose unambiguous. The second and third sentences sharpen the definition by describing the live-verification method and explicitly distinguishing this search from self-reported or curated lists, which separates it from related agent tools like bnb_agent_census and bnb_agent_employment.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The last sentence provides explicit placement guidance: use this tool before assuming no agent exists for a task. It does not name sibling tools to use instead or state exclusions, so it falls just short of an explicit when/when-not/alternatives rule.

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

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TDQS

A3.7/5.0
Disambiguation3/5

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.

Naming Consistency3/5

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.

Tool Count3/5

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.

Completeness4/5

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.

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