solenrich

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

No annotations are provided, so the description carries full burden. It states 'returns parallel results', hinting at concurrency, but does not disclose side effects, rate limits, or authentication requirements. The term 'enrich' suggests a read operation, but more detail is needed.

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 a single sentence with no wasted words, but it could benefit from clearer structure (e.g., separating usage intent from behavior). Still, it is appropriately concise.

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?

With no output schema and no annotations, the description is too brief. It does not explain the return format beyond 'parallel results', nor does it cover error handling, limits, or prerequisites. For a batch tool, this is incomplete.

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 has 100% coverage with descriptions for all parameters; the tool description adds no additional parameter information beyond what is already in the schema, so 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 verb 'enrich' and the resource 'multiple wallets or tokens' with a batch size limit (1-25), distinguishing it from single-enrich sibling tools like enrich_token and enrich_wallet.

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 implies the tool is for batch operations by mentioning 'multiple' and 'single call', but it does not explicitly state when to prefer single enrich tools over this one, though the sibling names make it clear.

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?

No annotations are provided, so the description must carry the burden. It discloses that the tool is stateless and lists alert types, but does not mention required permissions, rate limits, or what happens with invalid inputs. The stateless hint is useful but not comprehensive.

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 long, each serving a clear purpose: defining scope, listing events, and noting statefulness. No unnecessary 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?

Given the absence of an output schema, the description should explain the return format but only says alerts are 'graded by severity' without structure. It also lacks behavioral details like error handling or performance.

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%, so the schema already documents all parameters. The description adds no extra semantic detail beyond summarizing the parameters (watchlist, timestamp). 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 is a poll-based event detection tool for spot and Jupiter Perps, listing specific alert types. It distinguishes from sibling tools by focusing on real-time event polling, which no other sibling directly 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?

The description explains how to use the tool by passing a watchlist and a since timestamp, and notes that it is stateless so the caller owns the cursor. However, it does not explicitly state when not to use this tool or compare to 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?

No annotations are provided, so the description carries the full burden. It does not disclose any behavioral traits such as whether the operation is read-only, requires authentication, or has rate limits. The description only states the function without safety or side-effect 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 a single sentence that efficiently conveys the tool's purpose and key metrics. It is front-loaded and contains no redundant information. Slight improvement could be listing metrics in a more structured way, but current is concise.

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 no output schema, the description should provide more detail on what the output includes (e.g., format of rankings, summary picks). It mentions these aspects but is vague. For a comparison tool, additional context on output structure would enhance completeness.

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 only parameter 'mints' having a description that matches the tool's purpose. The description adds no additional meaning beyond the schema, so 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 the tool performs a side-by-side comparison of 2-3 tokens on specific metrics (price, liquidity, volatility, holder concentration, risk) and provides rankings and summary picks. This is distinct from single-token tools like enrich_token or due_diligence.

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 implies usage for comparing 2-3 tokens, but provides no explicit guidance on when to use this tool versus alternatives (e.g., enrich_token for single token analysis) or when not to use it.

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?

No annotations are present, so the description must disclose behavioral traits. While it lists output aspects (portfolio, risk, etc.), it omits critical details like whether the operation is read-only, any rate limits, or authentication requirements. The constraint of '2-3 wallets' is mentioned but not firmly enforced in the schema.

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 a single, well-structured sentence that front-loads the core purpose. No unnecessary words or 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 tool with no output schema, the description covers key return elements (portfolio, activity, risk, labels, rankings, summary picks). However, it lacks specifics on format, ordering, or data sources, which would enhance completeness.

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%, so the schema already explains both parameters. The description adds marginal value by clarifying the number of wallets (2-3) but does not provide additional meaning beyond the schema.

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 specifies the verb ('comparison'), resource ('wallets'), and scope ('2-3 wallets, portfolio, activity, risk, labels, rankings and summary picks'). It effectively distinguishes from sibling tools like 'enrich_wallet' (single wallet) and 'compare_tokens'.

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 implies usage for comparing multiple wallets side-by-side but does not explicitly state when to use this tool versus alternatives (e.g., 'enrich_wallet' for a single deep dive). No exclusions or when-not guidance is provided.

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?

No annotations provided, so description carries burden. Discloses proprietary data source and behavior based on address. Does not explicitly confirm read-only nature, permissions, or side effects, which would be helpful.

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 concise sentences, front-loaded with purpose, no wasted words. Each sentence adds value.

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?

Covers main behavior and parameters well, but lacks explicit output format description. For a tool with no output schema, hinting at the structure of the response would improve completeness.

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 covers all parameters, but description adds significant meaning: explains dual behavior, example fields for single entity (rank/percentile/trend), and window values. Goes beyond schema.

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?

Clearly states the tool returns tokens/wallets being queried by other agents, with dual behavior based on address presence. Distinct from all 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?

Explicitly describes two use cases: pass address for single entity rank/percentile/trend, omit for top-N. Mentions windows. Lacks explicit when-not-to-use or alternatives, but instructions are clear.

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?

No annotations provided, and the description does not disclose behavioral traits like read-only nature, error handling, or authentication requirements. It only states what it analyzes, leaving the agent uninformed about side effects or prerequisites.

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?

Single sentence, no filler, front-loaded with the core action. Highly concise and efficient.

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?

Without output schema and annotations, the description is insufficient. It omits return format, error conditions, and usage context, making it incomplete for an agent to reliably invoke.

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 parameters are already described. The description adds value by listing output metrics, but does not enhance parameter meaning beyond the schema.

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 analyzes a wallet's trading performance with specific metrics (win rate, PnL, consistency, hold time, smart_money classification). It distinguishes from siblings like enrich_wallet and wallet_history by focusing on performance analysis, though it does not explicitly differentiate.

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?

No guidance on when to use this tool versus alternatives such as enrich_wallet, compare_wallets, or wallet_history. The description lacks context for usage decisions.

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?

No annotations are provided, so the description carries the full burden. It describes what the tool returns but fails to disclose behavioral aspects such as rate limits, authentication needs, side effects, or whether it queries external sources. The output list is informative but insufficient for full transparency.

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?

A single, front-loaded sentence that efficiently conveys the tool's scope and outputs. No unnecessary words; every element contributes to understanding.

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?

The description lists outputs but lacks detail on format or structure, and there is no output schema. For a tool providing multiple complex results, more detail would benefit completeness. However, it is minimally adequate for an experienced agent.

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%, so the baseline is 3. The description does not add any semantics beyond the schema (just 'mint'), which is acceptable given full coverage. No additional parameter guidance is 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?

The description clearly states the tool's purpose: 'comprehensive token research' and lists specific outputs (security audit, holder concentration, whale activity, risk score, verdict). It distinguishes from siblings like 'enrich_token' and 'check_alerts' by emphasizing a holistic risk assessment.

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 implies usage for comprehensive token due diligence but does not explicitly state when to use this tool over alternatives or when not to use it. No exclusions or context for selection are provided.

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?

With no annotations, the description carries the transparency burden. It lists output contents but does not disclose behavioral traits like auth requirements, rate limits, or potential 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.

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

The description is a single sentence that front-loads purpose and is packed with information, though slightly long. No redundant 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?

Given no output schema, the description thoroughly lists the data returned, covering price, market cap, liquidity, holder concentration, slippage, risk flags, and verification. Missing error handling or limits.

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 the description adds minimal value beyond the schema. It does not elaborate on parameter usage or syntax.

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 analyzes a Solana SPL token and lists all provided data points (price, market cap, liquidity, etc.), making the purpose specific and 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?

The description implies usage for detailed token analysis but does not explicitly guide when to use this tool versus alternatives like batch_enrich or compare_tokens.

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?

No annotations provided, so the description carries full burden. It does not disclose any behavioral traits such as side effects (should be read-only), authentication requirements, rate limits, or data freshness. Only describes return content, not behavioral aspects.

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?

Single sentence containing all essential information, front-loaded with the verb and resource. No unnecessary words. Every word adds value.

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 effectively summarizes the key return fields. It covers the main purpose and variations ('light' vs 'full'). Could mention if read-only or cached, but overall sufficient for common use cases.

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% with both 'address' and 'depth' described. The description adds minimal extra meaning beyond the schema; it repeats the return fields but does not clarify parameter formats or constraints beyond what's in the schema. 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 the tool returns a Solana wallet profile including specific details like balance, holdings, DeFi positions, labels, and risk. It uses a specific verb 'Get' and resource 'wallet profile', distinguishing it from siblings like 'batch_enrich' and 'wallet_graph'.

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?

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, scenarios, or when to choose 'light' vs 'full' depth beyond the schema default. No exclusions or comparisons provided.

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?

No annotations provided, so description carries burden. Discloses caching, lazy population, and short-circuit behavior via since. Lacks details on return structure, auth needs, or rate limits, which is a gap given no 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, no wasted words. Front-loaded with purpose, then additional behaviorals. Every sentence adds value.

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?

No output schema, so description must cover response. Mentions ranking of tokens and unchanged flag, but lacks explicit detail on the full response structure. Adequate for mostly complete usage guidance.

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% for the single parameter 'since'. Description adds extra meaning by explaining its use for short-circuiting on no-change polls, enhancing the schema's ISO 8601 description.

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?

Clearly states it provides a daily intelligence brief of trending Solana tokens with composite-signal scoring. Distinguishes from siblings like new_tokens, token_trend, and trending_signals by specifying 'daily brief' and caching behavior.

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 describes caching behavior (24h, lazy-populated) and the since parameter for short-circuiting polls. Provides clear context for usage but does not contrast with alternative sibling tools for when not to use.

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?

Fully describes the internal logic: filters out market-makers and dust, aggregates per-coin consensus (long/short counts, net notional, bias, conviction), and provides top-trader drill-down. No annotations exist, so description carries full burden and does so thoroughly.

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, front-loaded with purpose, no redundant information. Every sentence adds value and the structure is easy to parse.

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 explains what the tool returns (per-coin consensus and top-trader drill-down). With 2 optional params and no required, the description is complete and leaves no ambiguity.

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 both parameters already described in input schema. Description adds minimal new semantic value beyond schema (e.g., default for top_traders is already in schema). Provides context for usage but not significant parametric insight.

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?

Clearly states the tool aggregates smart money positions from Hyperliquid leaderboard, with specific details on filtering and output. Distinguishes from sibling tools by emphasizing it's a positioning signal, not a standalone entry.

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 it should be used as confluence/risk context, not as a standalone entry. Also mentions optional single-coin focus via `market`, providing clear guidance on when and how to use.

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?

The description notes it is 'read from HL's public on-chain state' indicating a read-only operation, but without annotations the transparency is moderate. No contradictions with annotations (none provided).

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 two sentences, front-loaded with the core purpose, and lists all key data points efficiently. 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?

Given one parameter and no output schema, the description enumerates all returned fields (position details, PnL, profile type, etc.), providing sufficient context for an AI agent to understand what to expect.

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% for the single 'address' parameter, and the description repeats the schema's description ('Hyperliquid EVM (0x) address') without adding new meaning. 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 the tool provides 'Live Hyperliquid perp positions for an EVM (0x) address' and enumerates specific metrics (side, leverage, entry, PnL, etc.), distinguishing it from sibling tools like 'hyperliquid_smart_money' which focuses on smart-money tracking.

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 implies usage for fetching perp positions for a given address but does not explicitly state when to use or when to avoid, nor compare to alternatives like 'hyperliquid_smart_money'. Usage guidance is only implied.

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?

With no annotations, the description discloses that the tool filters and ranks tokens by safety, implying read-only behavior. It does not mention destructive traits, but the simple list operation is well understood.

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?

Single sentence with no wasted words. The purpose is front-loaded, making it immediately clear what the tool does.

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?

Adequate for a simple filtered list tool: covers purpose, filtering criteria, and ordering. Could explicitly mention return format (e.g., token addresses), but not required given no 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?

Schema description coverage is 100%, providing baseline 3. The description adds value by explaining that parameters filter by liquidity and risk score, and that results are ranked safest first, which is not in the schema.

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 'Discover' and resource 'recently launched Solana tokens', clearly distinguishing from sibling tools like token_trend or trending_signals which focus on analysis rather than discovery.

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 context on when to use (discovering new tokens with filters) but lacks explicit exclusions or alternative tool comparisons, though the sibling list implies differentiation.

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?

No annotations exist, so the description must disclose behavioral traits. It mentions the data returned but does not state whether the operation is read-only, if authentication is required, or any side effects. Important transparency is missing.

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 a single, concise sentence that front-loads the main action ('Parse a Solana transaction') and lists key outputs. It is efficient and focused, with no redundancy.

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 (1 parameter, no output schema), the description covers the basics of what is parsed. However, it does not describe the return format or structure, which would be helpful since there is no 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?

Schema coverage is 100% and the 'signature' parameter is well-described in the schema. The description adds no further meaning beyond what the schema provides, so a 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 function: parsing a Solana transaction. It lists specific extracted details (type, protocol, transfers, accounts, fees), which distinguishes it from sibling tools that focus on other analyses like token enrichment or wallet history.

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?

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing a valid transaction signature, or when not to use it (e.g., for filtering or searching). The usage context is only implied.

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?

No annotations provided, so description carries full burden. It discloses the computation (perp mark vs spot), flags non-viable venues with reasoning, and states output format (per-venue trade, filtered opportunities, best trade). Could mention rate limits or authorization needs, but core behavior is clear.

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?

Description is three sentences, efficiently conveying purpose, venue viability, and output. Slightly dense but not verbose. Could be split for readability.

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 tool complexity (cross-venue basis signal) and lack of output schema, description adequately explains return values. Context of sibling tools (e.g., perps_cross_venue_funding) suggests this is a specialized signal tool, and description is complete enough for agent to understand when to invoke.

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 has 100% coverage with descriptions for both 'asset' and 'min_yield_apr_pct'. Description adds no additional parameter meaning beyond the schema, so 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?

Description clearly states it computes perp mark vs spot price across venues and surfaces earnable yield. It distinguishes between funding-rate venues (viable) and pool perps (not viable), differentiating from siblings like perps_cross_venue_funding.

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?

Description specifies when to use (for funding-rate venues like HL, dYdX) and when not (pool perps like Jupiter, Adrena). It implies that pool perps should be skipped due to borrowing costs, but does not explicitly name alternative tools.

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?

No annotations are provided, so the description carries the full burden. It describes the outputs (best entry, basis, arbitrage) but does not disclose whether the operation is read-only, data freshness, or any side effects. While it implies a safe read operation, it lacks explicit behavioral details.

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 primary purpose. Every sentence provides distinct value: comparison scope, return items, and supported assets. No unnecessary 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?

Given the complexity of multi-venue cross-chain comparison and no output schema, the description provides a high-level overview but lacks details on return structure, venue-specific availability for each asset, or data freshness. It is adequate but leaves gaps for an AI agent to fully understand what to expect.

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% as both parameters have descriptions. The description adds that assets have venue-specific availability, but does not significantly enhance the schema descriptions. Baseline 3 is appropriate as the schema already documents parameters adequately.

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 compares borrow/funding APR and OI across specific venues (Jupiter Perps, Adrena, Hyperliquid, dYdX v4) and returns best entry, basis, and arbitrage opportunities. It specifies the supported assets (SOL/BTC/ETH/BONK). This distinguishes it from sibling tools like perps_basis_signal or perps_venue_comparison.

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 implies the tool is for comparing funding across venues but does not explicitly state when to use it versus alternatives. No when-not guidance or prerequisites are mentioned, and it does not differentiate from sibling tools like perps_basis_signal which might serve similar purposes.

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?

With no annotations, the description must carry the full burden of behavioral disclosure. It states 'Reads on-chain Anchor accounts directly,' which implies read-only operation, but lacks details on permissions, rate limits, latency, freshness, or whether the data is cached. The behavioral profile is minimal.

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 extremely concise: two sentences without filler. Every word adds value—specifying the metrics, markets, and data source. There is no redundancy or unnecessary 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?

The description lists the metrics returned but does not describe the output structure (e.g., whether it returns a list, a dict, time series). With no output schema, the agent lacks information on how to parse the result. This is a notable gap for a tool that returns multiple per-market data points.

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 is empty (0 parameters), so schema coverage is 100%. Per the rubric, the baseline score is 4. The description does not add parameter-level details, but no parameters exist to describe.

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 specifies the verb ('Per-market'), the resource ('Jupiter Perps'), the exact markets (SOL/BTC/ETH), and the data points (OI, utilization, borrow APR, skew, OI caps, health flags). It also explains the data source (on-chain Anchor accounts), making it easy to distinguish from sibling tools like perps_market_trend or perps_basis_signal.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, suitable scenarios, or exclusive conditions. The description only states what the tool does, not when it should be preferred.

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?

No annotations exist, so description carries full burden. It explains it returns deltas (changes), direction indicators per metric and per market, and notes overall direction excludes mark price. This adequately describes the behavioral output without omissions. For a read-only data tool, no further behavioral traits (e.g., side effects) are needed.

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: first lists what the tool returns, second gives usage guidance. No filler, front-loaded information. Every word serves a purpose.

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?

With a single enum parameter and no output schema, the description fully covers what the tool does, including specific metrics, symbols, time windows, and direction indicators. No critical information is missing for a data retrieval 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 only parameter (lookback) has 100% schema description coverage with enum values and a description 'History window'. The description reinforces this by mentioning 'over 7/14/30 days'. It adds no new meaning beyond the schema, so 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 provides per-symbol deltas for specific metrics over defined time windows. It lists the symbols (SOL/BTC/ETH) and metrics (mark price, OI, skew, utilization, borrow APR), and mentions direction indicators. This distinguishes it from sibling tools like perps_basis_signal which focus on basis, or perps_market_structure which likely gives current state. Purpose is highly specific and unambiguous.

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 for regime detection — bots that adjust behavior based on whether markets are growing, stressed, or rebalancing.' This gives clear guidance on when to use the tool. While it doesn't mention when not to use or alternatives, it provides a concrete use case that differentiates from siblings. Minor improvement would be to mention alternatives like perps_market_structure for snapshot data.

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?

No annotations provided, so the description carries full burden. It mentions that Adrena PnL may be null when mark prices are unavailable, providing some behavioral context, but lacks details on safety (read-only), authentication, or rate limits.

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 relatively concise and front-loaded with the main action, but the last sentence about Adrena PnL could be integrated more smoothly.

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 lacking an output schema, the description details key outputs (positions with venue, classification, risk flags) and notes missing data, providing sufficient context for a complex multi-venue 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?

Schema coverage is 100%, and the description does not add additional meaning beyond the existing param description ('Solana wallet address').

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 specifies the tool's function: retrieving open positions across Jupiter Perps and Adrena for a given wallet, and distinguishes it from sibling tools like hyperliquid_trader_profile.

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 implies usage by naming specific venues, but lacks explicit guidance on when to use versus alternatives or any 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?

With no annotations, the description carries the full burden. It explains the model inputs (slippage, fees, OI cap, total cost) and outputs (rankings, recommendation, warnings), indicating a read-only analytical tool. It does not mention side effects, speed, or data freshness, but for a comparison tool this is adequate.

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 efficient sentences with no wasted words. The core question is front-loaded, and the rest builds on it logically.

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 simple parameters) and lack of output schema, the description covers inputs, model components, and output nature. It lacks details on output format or potential limitations but is sufficient for an agent to understand its function.

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%—all three parameters already have descriptions in the schema. The description contextualizes them in the comparison but adds no new constraints or syntax details beyond what the schema provides.

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: 'Where to trade this market at this size.' It specifies the input components (funding, slippage, fees, OI cap, total cost) and output (rankings + recommendation + warnings), distinguishing it from sibling tools like perps_cross_venue_funding that likely focus only on funding.

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 implies usage for venue selection based on total cost but does not explicitly state when to use this tool versus alternatives (e.g., perps_market_trend for trend analysis). There are no exclusions or prerequisites mentioned.

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?

With no annotations provided, the description bears full responsibility for behavioral disclosure. It accurately describes read-only behavior (daily snapshots, summary stats) and implies non-destructive nature. No contradictions are present.

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 a single, information-dense sentence with clear structure. It front-loads the primary purpose and lists included data types efficiently. No extraneous content.

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 moderate complexity and absence of an output schema, the description adequately details return values (daily snapshots with specific fields and summary stats). It does not mention limits or pagination, but for a time-series tool, this is acceptable.

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% (2 params documented). The description adds context by stating 'over 7/14/30 days' for the period parameter, but this largely repeats schema enum values. It does not add new syntax or format details beyond the schema, so 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 defines the tool as retrieving full portfolio time-series data for a wallet, specifying daily snapshots of value, balance, holdings, risk score, and summary stats. It uses a specific verb+resource structure and is distinct from sibling tools like wallet_history.

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 usage for 'charting and PnL tracking', providing clear context. However, it does not mention when not to use this tool or suggest alternatives, which would improve differentiation.

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?

With no annotations provided, the description does not disclose whether the tool is read-only or has side effects. It mentions analytics but does not state that it does not modify state. Important behavioral context is missing.

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 a single concise sentence that immediately states the tool's purpose and lists supported protocols. No unnecessary 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?

The tool outputs complex data (TVL, yields, health signals) but the description does not describe the return format or structure. Without an output schema, this is a significant gap.

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 describes both parameters with 100% coverage. The description adds context about the tool's output categories but does not add new semantic meaning to the parameters beyond the schema.

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 provides DeFi protocol analytics including TVL, yield pools, and health signals. It lists supported protocols. However, it does not explicitly differentiate from sibling tools beyond being protocol-focused.

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?

No guidance on when to use this tool versus alternatives like compare_tokens or enrich_wallet. The description is purely functional and does not provide context for selection.

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?

No annotations provided, so description carries full burden. It explains routing behavior (single vs parallel enrichers) and provides realistic examples, but omits details like read-only nature, rate limits, or auth requirements.

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 front-load the core purpose, each sentence adds unique value, and no unnecessary words or repetition.

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 complexity and many siblings, the description covers purpose, usage patterns, and examples well. It does not detail return format, but that is acceptable without an 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?

Only one parameter 'question' with a generic schema description, but the tool description enriches it significantly with concrete examples and expected input formats, achieving high utility.

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 answers plain English questions about Solana wallets, tokens, or markets, and distinguishes from 27+ specialized sibling tools by being a general query tool that can chain enrichers.

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?

Examples illustrate appropriate usage (single vs compound intents) and implicitly differentiate from siblings, but no explicit when-not-to-use or alternative suggestions.

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?

With no annotations provided, the description bears full burden for behavioral transparency. It mentions scoring by copy-trade metrics, surfacing accumulated tokens, and mapping clusters, implying read-only analytical behavior. However, it lacks details on data freshness, cost, or side effects, and does not explicitly state if it modifies anything.

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 a single concise sentence that front-loads the main purpose. It efficiently communicates three key actions. However, it lacks structural elements like bullet points that could improve readability.

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 complexity of 5 parameters and no output schema or annotations, the description provides adequate context about inputs and purpose but is insufficient regarding output format, required permissions, or data source. It does mention Solana-specificity, which is helpful.

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% and the schema provides clear descriptions for each parameter. The tool's description adds overall context about copy-trade metrics, but does not significantly enhance understanding beyond the schema. 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 the tool's purpose with specific verbs: 'scores', 'surfaces', and 'maps' in relation to 'high-performing Solana wallets' and tokens. It distinguishes itself from sibling tools like copy_trade_signals by focusing on Solana and wallet cluster mapping.

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 does not provide any guidance on when to use this tool versus alternatives, nor does it mention when not to use it or any prerequisites. Users must infer usage from the context of 'smart money flow', but no explicit instructions are given.

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?

No annotations are provided, so the description must carry full burden. It mentions output format but omits important behavioral traits like read-only nature, permissions, error handling, or data freshness. Lacks comprehensive disclosure for a tool with no 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?

Single concise sentence with no wasted words. Front-loaded with key information ('Token metrics over time').

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 adequately explains the tool's return format (daily snapshots with direction indicators). For a simple two-parameter tool, this provides sufficient context.

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 adds value by explaining that output includes direction indicators per metric, which goes beyond the schema's parameter 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 'Token metrics over time' with specific details (daily snapshots, direction indicators). This distinguishes it from sibling tools like enrich_token or compare_tokens.

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 implies usage for getting time-series token metrics, but does not explicitly state when to use this tool over alternatives, nor does it provide exclusions or prerequisites.

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?

With no annotations, the description carries the burden. It discloses that the tool composes multiple signals and returns a ranked list with reasoning, but does not mention rate limits, authentication needs, or any potential side effects. The behavioral info is adequate but minimal.

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 a single, well-structured sentence that conveys the core purpose and composition without extraneous 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?

The description explains what the tool does and its inputs, but lacks details on output format, pagination, or error conditions. Since there is no output schema and no annotations, more context would improve completeness.

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%: all parameters have descriptions. The tool description does not add extra meaning beyond the schema, so 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 the tool returns a ranked list of Solana tokens with composite signals (DexScreener trending, risk scoring, whale-flow). However, it does not explicitly differentiate from similar sibling tools like 'consensus_signal' or 'new_tokens', so not 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?

No guidance is provided on when to use this tool versus alternatives. Sibling tools exist for similar purposes (e.g., 'token_trend', 'consensus_signal'), but the description gives no usage context or exclusion criteria.

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?

With no annotations, the burden falls on the description. It does not disclose behavioral traits like result limits, data freshness, performance expectations, or that depth is limited to 1 or 2 (only in schema).

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 a single sentence that is efficient but omits important context. It could include more without being verbose.

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 complexity of a graph tool (no output schema), the description is incomplete. It does not explain the output format, pagination, or what constitutes a 'cluster' or 'suspicious pattern'.

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 description does not need to add much. The description does not provide additional meaning beyond the schema's parameter 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 it maps wallet connections to find counterparties, clusters, and suspicious patterns. This is specific and distinguishes it from sibling tools like enrich_wallet or wallet_history.

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 implies usage for exploring wallet connections but lacks explicit guidance on when to use vs alternatives or prerequisites. No exclusions are mentioned.

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?

No annotations provided, so description bears full burden. It explains the output includes snapshots with changes and direction, which adds useful behavioral context. However, it does not disclose side effects, idempotency, authentication needs, or rate limits.

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?

Single sentence, no wasted words, front-loaded with 'Wallet portfolio over time'. Efficient and clear.

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?

Tool has 2 parameters and no output schema. Description provides the gist of the return type (snapshots with changes) but omits details like output format, pagination, or what 'direction indicators' specifically mean. Adequate for simple tool but leaves some ambiguity.

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% (both parameters have descriptions). The description adds no additional meaning beyond schema; 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?

Description clearly states tool provides wallet portfolio snapshots over time with position changes and direction indicators. It communicates the core action (snapshots with changes) but does not explicitly differentiate from sibling like portfolio_history.

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?

No guidance on when to use this tool versus alternatives (e.g., portfolio_history, enrich_wallet). Description implies tracking historical holdings but lacks explicit when/when-not usage 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?

With no annotations, the description carries the full burden of behavioral disclosure. It implies a read-only operation ('track'), but does not explicitly state side effects, authorization requirements, or any constraints beyond the implied analysis.

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 a single, concise sentence that front-loads the key purpose and outputs. Every part adds value with no redundancy.

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 and the schema coverage, the description adequately lists the returned metrics. An output schema would enhance completeness, but the current information is sufficient for an agent to understand the tool's value.

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 all three parameters with descriptions, achieving 100% coverage. The tool description does not add further meaning beyond what the schema already provides, so a 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: tracking top token holders with specific metrics like balances, % supply, buy/sell volumes, and accumulation vs distribution signals. This verb+resource definition is specific and distinguishes it from sibling tools such as due_diligence or token_trend.

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?

No guidance is provided on when to use or avoid this tool compared to alternatives. The description merely states what it does without indicating contexts where other tools might be more appropriate.

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