Base L2 Agent Kit
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: auditing contracts, getting gas prices, finding yield, analyzing token risks, assessing wallet health, generating mnemonics, fetching prices, and getting DEX quotes. There is no overlap where two tools perform the same function.
Naming Consistency3/5Tool names are readable but follow mixed conventions: some use verb_noun (generate_mnemonic), some noun_verb (contract_audit), some noun_noun (wallet_health, dex_quote), and some have a base_ prefix while others don't. The pattern is not consistent enough to be predictable.
Tool Count5/5With 8 tools, the server is well-scoped within the ideal 3-15 range. Each tool covers a necessary aspect of the Base L2 agent domain without redundancy or bloat.
Completeness3/5The set covers a broad range of analytical and informational operations (audit, gas, yield, token analysis, wallet health, price quotes), but lacks actual transaction execution, wallet address derivation, or balance checks. This creates notable gaps for a complete agent workflow, though the existing tools handle a coherent subset.
Average 3.6/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 7 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. 'Get' implies a read-only quote request rather than an executed swap, which is useful, but it does not disclose quote validity, token format, slippage, or whether any state changes occur. The Base L2 scoping is the only extra context beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word earns its place and it is appropriately brief for a simple quote tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists, the description leaves critical invocation details unaddressed, such as token identifier format and amount denomination. Combined with no usage guidelines, the tool is not fully contextualized for an agent to invoke correctly in all cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no parameter details. While from_token, to_token, and amount are self-naming, the description does not specify whether tokens are symbols or addresses, what amount units are used, or how decimals are handled. The description completely fails to compensate for the schema's lack of explanations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Get') and resource ('DEX swap quote') with a clear chain scope ('Base L2'). It also distinguishes this tool from siblings like base_price and base_gas_estimate by emphasizing the DEX swap quote context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The sibling tools cover related but distinct functionality, but the description does not mention any of them or provide selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full transparency burden. It mentions that a risk score is returned, but it does not disclose whether the tool makes external calls, requires specific network access, handles edge cases like invalid addresses, or has any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the action and lists key analysis criteria. It is appropriately sized for a simple one-parameter tool with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The presence of an output schema covers the return structure, but the description still lacks usage context and parameter explanation. Given the security-related nature of the tool, more behavioral detail (e.g., mainnet support, dependency on external data sources) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter (address) with zero description coverage. The tool description does not mention the parameter at all, forcing the agent to rely on the parameter name and tool name to infer that 'address' is the token contract address. No format, network, or validation constraints are specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Analyze a token contract for honeypot risks, mint functions, ownership patterns.' It names specific analysis aspects and mentions a risk score return, making the purpose distinct from broader sibling tools like contract_audit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as contract_audit. The description only states what the tool does, leaving the agent to infer appropriate usage contexts without any explicit exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral disclosure burden. It does not mention data source, freshness, rate limits, or what 'current' means (e.g., latest block, live feed). The description only states the basic action without any behavioral nuance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence conveys the tool's purpose with no unnecessary words. It is concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only price tool, the description is minimally viable, but lacks behavioral context and parameter semantics. An output schema exists, which may cover return values, but it is not referenced in the description. Given no annotations, the description is not fully complete for selecting and invoking the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not elaborate on the 'token' parameter beyond its name. The default 'ETH' appears in the schema, but the description adds no format, supported values, or examples, so agents must guess what tokens are accepted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get current price of a token on Base L2' clearly identifies the action (get price) and resource (token on Base L2), and differentiates it from sibling tools like base_gas_estimate (gas) and dex_quote (quotes for trades).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit when-to-use or alternative guidance, but the context is clear: use this tool when you need a token's current price. It does not mention exclusions or alternatives, so it falls into implied usage rather than explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explicitly mentions the output as a health score from 0-100, which provides some transparency, but it does not state whether the operation is read-only or describe behavior on invalid addresses.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the action and includes the return range. Every word earns its place, making it highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and an output schema, the description adequately covers purpose and output. It could benefit from usage guidance, but the simplicity of the tool allows for a short description to be mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It implicitly explains that 'address' refers to the wallet to analyze, but it does not explicitly define the parameter format or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes wallet portfolio diversification, token concentration, and recent activity, with a specific verb and resource. It distinguishes itself from sibling tools like token_analyzer by focusing on overall wallet health, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or exclusions, leaving the agent to infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool scans code and returns a risk score and findings, which is a useful behavioral disclosure. However, it does not mention whether the code is executed, sent off-platform, or if there are any limitations or side effects, which would be valuable context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is direct and front-loaded. It succinctly states the action, target, scope, and return value without any wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple one-parameter tool with an output schema present, so the description does not need to explain return values in detail. It covers the core purpose and network context ('Base L2'), and adds return value information. The main gap is the lack of parameter format details, but given the low complexity, the overall context is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter ('code') with no description, resulting in 0% schema description coverage. The description mentions 'smart contract code,' which aligns with the parameter, but it does not specify the expected format (e.g., Solidity source vs. bytecode), size limits, or other constraints. Thus, the description only partially compensates for the missing schema metadata.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Scan') and resource ('smart contract code') with a clear scope ('on Base L2'). It also mentions the return value (risk score + findings). This clearly differentiates it from the sibling tools, which cover gas estimation, yield farming, token analysis, wallet health, mnemonic generation, price, and DEX quotes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool should be used to audit smart contract code, but it does not explicitly state when to use it over alternatives or mention any exclusions. No sibling alternatives are named, so the guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'secure BIP39' but doesn't explain what this means in practice (e.g., entropy source, word count, format of the output, or any failure behavior). This lack of detail is a significant gap for a tool that generates sensitive data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately conveys the core functionality. It is efficiently front-loaded with the verb and resource, with no wasted words or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (zero parameters, output schema available), and the description adequately covers the primary action. It doesn't mention output details like word count or format, but given the output schema exists and the tool's simplicity, the description is reasonably complete for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline for parameter semantics is 4. The description doesn't need to explain any parameters, but it also gives no hints about how the mnemonic is formatted or returned, which is acceptable given the schema is empty.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Generate' and identifies the resource as 'a secure BIP39 mnemonic phrase,' making the tool's purpose unambiguous. It clearly distinguishes itself from the sibling tools, which are all unrelated to mnemonic generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, but the siblings are clearly in different domains, so the implied usage is straightforward. There is no exclusion criteria or alternative named, leaving the guideline at a basic level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool scans and returns pool name, APY, TVL, and risk level, giving a clear sense of the output. However, it does not explicitly mention that this is a read-only operation, whether it aggregates live data, or how 'highest yield' is determined. The behavior is transparent enough for a simple query tool but lacks deeper context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two well-structured sentences: the first states the action and target, the second lists the return fields. There is no redundant wording, and the information is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (zero parameters, clear output, presence of an output schema), the description is mostly complete. It mentions key output fields and the network (Base). It lacks subtle details like limitations (e.g., 'only covers TVL above X') or data freshness, but these are not critical for a basic scan tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty (0 parameters), so the description does not need to explain parameter usage. Per the rubric, a 0-parameter tool receives a baseline of 4. The description adds value by describing the output structure, which compensates for the lack of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's action ('Scan'), resource ('DeFi protocols on Base'), and objective ('highest yield opportunities'). It also lists the output fields, making it distinct from sibling tools like token_analyzer or dex_quote, which focus on different aspects of DeFi.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that this tool should be used when seeking yield opportunities on Base, but it does not explicitly state when to prefer it over alternatives or when not to use it. There is no mention of alternative tools or exclusionary conditions, so the usage context is only implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the core behavior (fetching current gas prices with tiers) but does not mention potential side effects, rate limits, or caching behavior. For a straightforward read-only operation, this is adequate but not rich in contextual detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loading the action and resource, and includes the essential detail of output tiers. Every word adds value with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is very simple, with no parameters and an output schema to describe return values. The description covers the core purpose and key output attributes (Gwei, tiers). It does not add extra caveats, but given the low complexity, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, so the schema fully covers them (vacuously). The description adds no parameter-specific details, but none are needed. Given the baseline of 4 for zero-param tools, this scores well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' with a clear resource 'current Base L2 gas prices in Gwei' and specifies the output tiers (safe/recommended/fast). This distinguishes it from siblings like base_price, which likely pertains to token prices rather than gas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies this tool is for fetching gas prices on Base L2, and the presence of 'gas' differentiates it from token price tools. However, it does not explicitly compare itself to alternatives or state when not to use it, but the context is sufficiently clear for a simple read-only tool.
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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