MEV Intelligence

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

The description explicitly discloses that the tool does not touch funds and does not submit anything, and lists the return fields (target address, calldata, gas limit, value, chain). This adds meaningful behavioral context beyond the readOnlyHint/destructiveHint annotations, clarifying what 'read-only' means in this context.

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 three sentences, front-loaded with the main purpose, and contains no unnecessary repetition. Every sentence adds value: purpose, output/scope, and explicit safety boundary.

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 there is no output schema, the description properly explains the return values and the tool's scope, making it complete for agent use. It also clarifies supported protocols and chains, which is crucial for a multi-protocol tool.

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 provides 100% parameter descriptions, so the baseline is 3. The description adds minimal parameter-specific detail beyond what the schema already covers, but it doesn't need to since the schema is thorough.

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 uses a specific verb ('Build') and resource ('agent-ready calldata for a liquidation transaction'), and explicitly differentiates from siblings by positioning it as a calldata builder that feeds into submit_bundle. It also lists supported protocols and chains, making the tool's scope unmistakable.

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?

It clearly indicates the tool builds calldata for later submission via submit_bundle and explicitly states it does not submit anything, giving a clear usage boundary. However, it doesn't explicitly contrast with other sibling tools like get_builder_recommendation, so it's not a perfect 5.

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

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

Annotations already declare readOnlyHint and destructiveHint, and the description adds context by explaining the data sources (live relay acceptance rate and submission volume) and that it returns only the top recommendation. It also mentions a paid endpoint for full telemetry, which is useful behavioral context beyond annotations.

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?

Two sentences, front-loaded with the core purpose and outcome. The second sentence efficiently introduces the extended resource and payment requirement without unnecessary detail.

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 simple read-only tool with no output schema, the description is complete: it explains the recommendation criteria, the returned data (builder name and acceptance percentage), and a pointer to the full ranked list. No key information is missing for an AI agent to use this tool effectively.

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?

With zero parameters, the description fully compensates by explaining what the tool does and what it returns. There is no need for parameter-level semantics, and the description provides enough detail about outputs and criteria.

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 a specific action: getting the best Ethereum block builder for MEV bundle submission right now, based on live relay acceptance rate and submission volume. It distinguishes from siblings like recommend_bundle_submission by focusing on builder selection, and specifies the return value (builder name and acceptance percentage).

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?

Provides clear context: use this when you need the best builder immediately based on live telemetry. It also points to an alternative endpoint for the full ranked list with payment, but does not explicitly exclude or contrast with sibling tools such as recommend_bundle_submission.

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

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

Annotations already declare read-only, non-destructive, and open-world behavior. The description adds value beyond annotations by specifying the 'morning briefing' usage pattern, the report's scope, and pointing to a full accuracy archive at /intelligence/accuracy-archive for deeper metrics. This provides behavioral context without contradicting annotations.

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 three sentences, each earning its place: the first states the purpose and contents, the second gives usage guidance, and the third points to supplementary resources. It is front-loaded, efficient, and free of fluff.

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 simple read-only report with one optional parameter and no output schema, the description is complete. It explains what the report contains, when to call it, and where to find more detailed accuracy metrics, fully equipping the agent to select and invoke the tool correctly.

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 the single parameter 'window_hours' already described in the schema ('Lookback window in hours (default 24, max 48)'). The tool description does not add any parameter-specific meaning beyond the schema, so the baseline score of 3 is appropriate.

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 the tool's purpose with a specific verb ('Get') and resource ('daily intelligence report summarizing liquidation market activity'). It enumerates the report's contents (competitor count, positions, funnel metrics, top candidate) and distinguishes it from sibling tools by positioning it as the 'morning briefing' tool.

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 provides explicit when-to-use guidance: 'call it once per session to understand market state before executing.' This contextualizes the tool within a workflow and implies it should be used before other execution tools, offering clear usage direction without needing to name alternatives.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable context by clarifying that this is a top-10 preview and that the full universe requires a paid call, plus the atomic submission workflow. No contradiction with annotations.

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?

Four sentences, each earning its place: tool definition, output specification, next-step workflow, and paid alternative. No filler, no repetition, and the core function is front-loaded. Excellent structure.

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 simplicity (one optional parameter, no output schema, strong annotations), the description is complete. It covers what the tool does, what it returns, how to proceed after using it, and when to use the paid alternative. No critical gaps.

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 description coverage is 100% for the single optional `limit` parameter, with schema text explaining 'Max results (default 10, preview max 10)'. The description mentions 'top 10' consistently but adds no further parameter-level semantics. Baseline 3 is appropriate.

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 uses the specific verb 'Get' and names the exact resource: 'near-liquidation borrowers ranked by health factor proximity across Aave V3, Spark, and Morpho on L1 and Base.' It also enumerates the returned fields (borrower addresses, health factor, debt USD, collateral USD), making it unmistakable and clearly distinct from sibling tools.

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?

It states a clear usage workflow: after obtaining a target, sign a liquidation transaction and call submit_bundle. It also directs users to the paid /intelligence/liquidation-waves endpoint for net profit estimates and the full borrower universe, providing an explicit alternative. It does not explicitly exclude sibling tools like monitor_crossing_candidates or predict_liquidation_probability, but the context is strong.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool's safety profile is known. The description adds valuable behavioral context: it returns exactly 10 positions, lists the fields included, and discloses that a fuller stream is available via paid endpoint. This goes beyond the annotations by setting expectations about response size and data limitations. No contradiction with annotations.

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 three sentences with no redundant words. It front-loads the primary action, then gives return details, and finally provides alternative/premium options. Every sentence contributes useful 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 simple read-only tool with one optional parameter and no output schema, the description is sufficiently complete. It specifies the return size, key fields, and the related action tool (submit_bundle), while annotations cover safety. It also informs about the paid full stream, which is relevant context for agents with payment capabilities.

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 provides a complete description for the only parameter (min_net_usd: 'Minimum estimated net USD profit to include'), giving 100% coverage. The tool description adds no additional meaning about this parameter, so the baseline score of 3 applies because the schema handles the semantic burden.

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 the tool's function with a specific verb and resource: 'Get a risk-enriched MEV opportunity stream.' It also lists the exact return fields (chain, protocol, health factor, risk tags) and explicitly mentions the sibling tool submit_bundle for acting on opportunities, distinguishing it from that action-oriented sibling.

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 provides clear usage context by stating 'Use submit_bundle to act on opportunities directly from this feed,' which directs the agent to the appropriate alternative for a follow-up action. It also mentions that the full stream requires x402 payment at another endpoint, implying this feed is a limited/preview option. However, it does not contrast this tool with other read-only siblings like get_daily_liquidation_report or get_liquidation_waves, so some exclusion guidance is missing.

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

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

Annotations already mark it read-only and non-destructive; description adds return shape (top 5, fields, time window) and the payment limitation, giving concrete behavioral context beyond annotations.

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?

Two sentences with all information front-loaded; no wasted words.

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 simple read-only tool, description fully explains what is returned and its scope; no output schema needed.

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?

Zero parameters, so schema coverage is trivially 100%; baseline for no params is 4, and description confirms no inputs needed.

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?

Specific verb 'Get' + resource 'top MEV searchers ranked by landed liquidation fires in the last 4 hours'; clearly differentiates from siblings like get_daily_liquidation_report by time window and focus.

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?

Covers intended use (top 5 recent searchers) and points to a paid alternative for the full 25-entry leaderboard; doesn't explicitly exclude other siblings but provides directional guidance.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the read-only nature is covered. The description adds transparency about the output fields (health factor, cross probability, net profit, protocol) and sorting by cross probability, which is useful for understanding behavior without an output schema. It does not disclose pagination or rate limits, but this is minor given the tool's simplicity.

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 four concise sentences, each adding meaningful information: purpose, output contents, usage, and follow-up action. It is front-loaded with a clear verb+resource and contains no redundant or filler text.

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 read-only query tool with two simple, documented parameters and no output schema, this description is comprehensive. It covers what the tool does, what it returns, when to use it, and what to do next, making it effectively complete for an agent to select and invoke the tool correctly.

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 input schema covers 100% of parameters with descriptions for both limit and min_cross_prob, so the schema does the heavy lifting. The description adds no additional parameter details, though it does mention cross probability (0–1) in the context of the returned data. Baseline 3 is appropriate.

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 it 'Get[s] the highest-priority liquidation candidates sorted by cross probability', identifies the target resource, and explains what each candidate includes. It differentiates from sibling tools by focusing on prioritization for pre-building bundles, which is distinct from prediction, reporting, or submission tools.

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?

It explicitly says to use this tool to 'prioritize which positions to pre-build bundles for' and instructs to 'Call submit_bundle when a candidate crosses HF=1.0', giving clear usage context and a follow-up action. However, it does not mention when to use alternative tools like predict_liquidation_probability or get_liquidation_waves, so it lacks explicit exclusions.

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

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

Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds value by detailing the output fields (health_factor, cross_probability, etc.) and hinting at time sensitivity ('how long until crossing'). It goes beyond simple read-only disclosure by explaining what the prediction includes.

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 multi-sentence but every sentence earns its place: purpose, output details, usage guidance, and a link to a richer alternative. It is front-loaded with the purpose and structured logically, with no fluff or redundant phrasing.

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?

Despite no output schema, the description enumerates all return fields and their units, making the return contract understandable. It also ties the tool into the broader workflow (before submit_bundle), and distinguishes itself from the more comprehensive endpoint, providing complete context for the agent's decision-making.

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%, so baseline is 3. The description enriches parameter understanding by clarifying that borrower is optional and that omitting it 'returns top 5 candidates by cross probability,' and that protocol is a filter when borrower is not specified. This adds contextual meaning beyond the schema's field descriptions.

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 the tool's function: 'Get a structured liquidation probability prediction for a specific borrower or the top candidates.' It uses a specific verb ('get') and resource ('prediction'), and distinctively positions itself as 'the core moat tool' that exposes the prediction layer, differentiating it from sibling tools like submit_bundle or get_liquidation_waves.

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?

Explicit usage guidance is provided: 'Call this before submit_bundle to confirm the opportunity is still live and to size your bribe correctly.' It also mentions an alternative (full model at /intelligence/liquidation-waves with payment), giving clear when-to-use and when-to-consider-other-options context.

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

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

Annotations already mark this as read-only and non-destructive. The description adds valuable behavior beyond annotations: it uses live relay telemetry, falls back to market conditions when no borrower is specified, and returns a human-readable reason. No contradiction exists.

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?

Three sentences, each with clear purpose: the action, the return values, and the workflow pairing. No filler or redundancy. Front-loaded and well structured.

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 tool with one optional parameter, no output schema, and a read-only annotation, the description is complete. It explains what it does, what it returns, and when to use it. The return shape is described enough in prose to compensate for the missing output schema.

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 the single optional 'borrower' parameter at 100% coverage. The description adds important semantic nuance: omitting the borrower switches to market-conditions mode. This extra meaning goes beyond the schema description, justifying a 4.

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 the tool's purpose: getting an actionable bundle submission recommendation. It specifies the return values (best builder, inclusion probability, reason) and mentions the optional borrower scope. However, it does not explicitly distinguish itself from the similarly named sibling tool 'get_builder_recommendation', so it stops short of a 5.

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 gives clear usage context: pair with 'monitor_crossing_candidates' after identifying a hot candidate, and use either a specific borrower or current market conditions. It does not explicitly mention when not to use it or name alternative tools, but the workflow guidance is strong enough for a 4.

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

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

Annotations provide no safety signals (all false), so the description carries the behavioral burden. It reveals that bundles are forwarded to rbuilder and fanned out to multiple relays, mentions the API key attribution requirement, and notes the returned tracking_id. This adds meaningful context about side effects and monitoring without contradicting annotations.

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 front-loaded with the core action, followed by usage context, forwarding details, API key note, analytics reference, and a tip. It is slightly verbose but each sentence contributes useful information; the tip somewhat repeats usage guidance but still adds value. Good structure overall.

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 an action tool with no output schema, the description covers the purpose, usage timing, forwarding behavior, API key requirement, and where to check submission status. It does not explicitly mention error handling or prerequisites beyond having a signed bundle, but the sibling tools provide the pipeline context. Reasonably complete for the complexity.

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 every parameter already described in detail (e.g., max 10 transactions, hex blockNumber, optional revertingTxHashes). The tool description adds no new parameter-level meaning beyond the schema, so the baseline score of 3 is appropriate.

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 opens with 'Submit a signed Ethereum bundle directly to MEV SearcherNet rbuilder for inclusion,' which is a specific verb and resource, clearly distinguishing it from sibling tools that analyze or build transactions. It unambiguously identifies the action and target, making it easy for an agent to know what the tool does.

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?

Explicitly states 'Use this after get_liquidation_waves or get_mev_feed to act on a liquidation opportunity,' providing clear when-to-use context. It also offers a pairing tip but does not explicitly list when not to use it or name alternative submission tools, though siblings imply a unique role.

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