agentforge

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

With no annotations, the description bears full burden. It describes the scan's scope (EVM and Solana) and output (risk assessment), but does not detail auth needs, rate limits, or potential side effects. However, as a read-only scan, it is sufficiently transparent.

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 concise sentences front-load the main purpose and cover key details. Every sentence adds value, 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 complexity (cross-chain, multiple risk types) and no output schema, the description covers what is scanned and what is returned (risk assessment). It could detail output format but is sufficient for an 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 coverage is 100%. The description adds meaning beyond schema: for 'chain' it mentions Solana support, for 'address' it specifies formats (0x-prefixed for EVM, base58 for Solana). This aids in correct parameter usage.

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 scans wallets for risky token approvals, specifying EVM (unlimited approvals, unverified spenders) and Solana (delegate authorities) nuances. This specificity distinguishes it from sibling tools like wallet_safety or solana_token_risk_scan.

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 assessing wallet approval risks but does not explicitly mention when not to use or provide alternatives. Context is clear from the description, but lacks 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 provided, the description carries full burden. It describes static analysis-like behavior (finds, suggests, flags) but does not disclose side effects, auth requirements, rate limits, or whether code is executed. The description is insufficiently transparent.

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 no redundancy. The first sentence front-loads the core purpose, and the second efficiently lists supported languages. 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?

Given no output schema, the description should explain what the tool returns. It does not. Additionally, with 4 parameters and no annotations, the description lacks behavioral context (e.g., whether it modifies state, error handling, output format).

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 does not add significant meaning beyond the schema: it lists supported languages (already in enum) and implies focus areas but provides no extra details on syntax or constraints.

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 performs 'smart contract security analysis' and lists specific outcomes (vulnerabilities, gas optimizations, best practice violations) and supported languages. This distinctly separates it from sibling tools like approval_scan or contract_docs.

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 security analysis of smart contracts but provides no explicit guidance on when to use vs alternatives like contract_docs or approval_scan, nor any prerequisites or 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?

No annotations are provided, so the description carries the full burden. It explains the outputs but does not disclose read-only nature, error states (e.g., unverified contract), or any required authentication.

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 no wasted words. The main purpose is front-loaded, making it easy for an agent to quickly understand the tool's function.

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 covers the main output types and purpose. It is reasonably complete for a documentation tool, though it could mention handling of unverified contracts or error responses.

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 schema already documents all parameters. The description adds no additional semantic information beyond reinforcing that the contract must be verified.

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 generates documentation for verified EVM smart contracts, listing specific outputs (function descriptions, risk flags, etc.). It distinguishes from siblings like code_review by focusing on automated documentation generation.

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 use for obtaining contract documentation but provides no explicit guidance on when to use this tool versus alternatives (e.g., code_review, approval_scan) 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 provided, so the description must convey behavioral traits. It does not disclose what the tool returns (e.g., list of events or alerts), nor any side effects, authentication needs, or rate limits. The word 'Monitor' is vague regarding output.

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. It front-loads the main action ('Monitor recent contract activity') and specifies the types of events monitored.

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 lack of output schema and annotations, the description is moderately complete. It covers the core functionality but lacks details on output format, error handling, or behavior when no events are found. For a monitoring tool, more context on what the agent can expect would be beneficial.

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 baseline is 3. The description adds meaning by enumerating the event types (admin ops, proxy upgrades, etc.) that the tool looks for, which clarifies the purpose of the address and lookbackHours parameters beyond their basic schema 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 monitors contract activity for specific suspicious events like admin operations, proxy upgrades, ownership changes, and pause events. This differentiates it from siblings like code_review (which analyzes code) or pool_snapshot (which looks at liquidity pools).

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 security monitoring of contracts, but does not explicitly state when to use this tool versus alternatives like approval_scan (which checks token approvals) or registry_lookup. No 'when not to use' 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 must disclose behavior. It mentions 'current' and 'trend analysis' but omits details on data freshness, caching, authentication, rate limits, or output structure.

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, zero waste. Clearly communicates core function, but could benefit from slight restructuring to front-load key info.

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?

Lacks details on return format, price units (gwei/wei), trend time window, and behavior for unsupported chains. Incomplete 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 describes the single parameter with enum and default; description adds no extra meaning beyond 'any supported EVM chain'. Baseline 3 due to 100% schema coverage.

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 provides current gas prices for EVM chains with slow/standard/fast categories and trend analysis. This distinguishes it from sibling tools that focus on contracts, tokens, or transactions.

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?

Implicitly guides use for any supported EVM chain, but lacks explicit when-to-use or when-not-to-use compared to sibling tools. No alternatives 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. Discloses that data is 'cached', updated every 15 minutes, and returns specific fields. Implies read-only operation. Lacks details on error handling, rate limits, or authentication, but the cache and refresh interval are useful behavioral traits beyond 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?

Three concise sentences: purpose, filters, return values + refresh info. No redundant phrasing, every sentence adds value. Well front-loaded.

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 8 parameters and no output schema, description covers key input filters and output fields (TVL, APY, volume, IL risk, registry enrichment). Mentions refresh interval. Lacks details on sorting/pagination, but these are in schema. Adequate for a read-only pool snapshot 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%, baseline is 3. Description adds context by giving examples for protocol ('uniswap-v3'), chain ('ethereum'), and token ('ETH'), but does not explain all 8 parameters (e.g., pool, limit, offset, sortBy, order). No contradictory or additional semantic depth 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?

Description states 'Get a cached snapshot of top DeFi liquidity pools' with specific verb 'get' and resource 'cached snapshot'. Lists return fields (TVL, APY, volume, IL risk) and filter options (protocol, chain, token). Clearly distinguishes from sibling tools like token_intel or token_compare by focusing on pool-level data.

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 implicitly defines usage context (DeFi pool data) but offers no explicit guidance on when to prefer this tool over siblings like token_risk_metrics or code_review. No mention of exclusions or 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?

Given no annotations, description carries full burden. It states return types and no payment required but lacks explicit disclosure of read-only nature, rate limits, or authentication needs. 'Free' implies no cost but not behavioral traits.

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 extremely concise (two sentences, 18 words). Front-loaded with action and output, 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?

For a simple lookup tool, description covers main purpose and return fields. It omits supported chains, but schema parameter 'chain' fills that gap. 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?

Input schema has 100% coverage with descriptions for both parameters. Description adds no new parameter information beyond what schema already provides, 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?

Description uses specific verb 'Look up' and identifies resource 'Known Contract Label Registry'. It lists return fields (protocol name, category, risk level, tags), clearly distinguishing it from siblings like contract_docs or token_intel.

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 explicit guidance on when to use this tool versus similar siblings. The 'Free' note is positive but does not help selection. Context for alternatives 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?

No annotations provided, so description bears full burden. It lists return fields (score, confidence, etc.) but does not disclose any side effects, 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?

Two sentences: first defines purpose and scope, second lists output fields. No redundancy, front-loaded.

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 2-parameter tool with no output schema, description explains inputs (text, context with enum) and return fields (score, label, etc.). Missing interpretation of score/confidence, but adequate overall.

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 description does not add significant new meaning beyond the parameter descriptions. Baseline score applies.

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 verb 'analyze' and resource 'sentiment of text', with specific contexts (crypto, finance, social_media, general). No sibling tool duplicates this function.

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?

Implied usage for sentiment analysis across specified contexts, but no explicit guidance on when to use versus alternatives or 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?

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions that the tool is free and returns certain data, but lacks details on side effects, rate limits, error conditions, or whether it is read-only. This is insufficient 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?

The description is two sentences, front-loaded with the purpose, and contains no extraneous words. 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?

Given the tool's low complexity (single required parameter, no output schema), the description is fairly complete: it explains what the tool does, what it returns, and that it is free. It could be improved by specifying the return format or error handling, but it is adequate for its simplicity.

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 a description for 'programId' ('Base58 Solana program ID'). The tool description adds no additional meaning beyond the schema; it only notes the tool is free. Baseline 3 is appropriate as schema does the heavy lifting.

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 'Look up' and the resource 'Solana program ID in the program label registry', and specifies the returned fields (protocol name, category, risk level). It distinguishes itself from sibling tools like 'registry_lookup' by focusing specifically on Solana programs.

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 includes a note that the tool is free, but provides no explicit guidance on when to use this tool versus alternatives (e.g., registry_lookup). It does not state when not to use it or mention 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?

The description lists the checks performed (authority, concentration, liquidity) and mentions a composite score, giving some insight into behavior. However, with no annotations, it fails to explicitly state that the tool is read-only, non-destructive, or any rate limits or authorization needs, leaving gaps in 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?

The description is a single, concise sentence (18 words) that front-loads the core purpose and lists key elements without superfluous words. Every part earns its place.

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 has no output schema, and the description only mentions a composite risk score without detailing the full return structure (e.g., whether individual metrics are returned). For a single-parameter analysis tool, this omission reduces 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% (one parameter 'mint' described as 'Base58 Solana token mint address'). The description adds no extra meaning beyond what the schema already provides, so the baseline score of 3 applies.

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 'rug check' on Solana tokens, listing specific risk factors (mint/freeze authority, holder concentration, liquidity depth) and a composite 0-100 risk score. It uses a specific verb and resource, and the inclusion of concrete elements distinguishes it from siblings like token_risk_metrics.

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 usage guidelines are provided. The description does not indicate when to use this tool versus alternatives like token_risk_metrics or token_intel, nor does it specify any prerequisites or contexts where the tool is appropriate.

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 adequately discloses the output: labeled programs, token/SOL movements, success status, and risk flags. It does not mention side effects but for a read-only explainer this is sufficient.

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. It is front-loaded with the main action and is concise with 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 an explainer tool with no output schema, the description covers the key aspects of the output (programs, token movements, status, risks). It lacks mention of error handling or edge cases, but is reasonably complete.

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 (signature). The description does not add new information about the parameter beyond what the schema provides (Base58 transaction signature). 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 'Explain' and the resource 'Solana transaction', and specifies the aspects covered (programs, token/SOL movements, success status, risk flags). This distinguishes it from sibling tools like tx_decode or solana_tx_simulate.

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 a clear purpose but does not include explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. Usage is implied but not directly stated.

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 full burden. It discloses that the simulation is deterministic and provides a risk recommendation, but it does not specify whether it has side effects, required permissions, rate limits, or any error conditions. The outputs are listed but behavioral traits are minimally covered.

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 outputs without extraneous text. It could be slightly structured with bullet points for better readability, but 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?

Given the low complexity (1 parameter, 100% schema coverage, no output schema), the description adequately covers inputs and outputs. It explains what the simulation produces, though it lacks details on errors, limitations, or use cases. Overall sufficient for the tool's simplicity.

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, which is adequately described as 'Base64-encoded unsigned (or signed) Solana transaction'. The description does not add any additional semantic meaning or usage details beyond what the schema already 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 action (Simulate), the resource (Solana transaction), the context (before signing), and lists specific outputs (balance changes, labeled programs, risk rules, recommendation). This distinguishes it from siblings like solana_tx_explain which likely explains without simulation.

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 before signing, providing contextual guidance, but it does not explicitly state when to use this tool over alternatives like solana_tx_explain, nor does it mention when not to use it. No exclusion criteria or competitor 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 provided, so description carries full burden. Describes output fields (summary, key points, compression ratio) but does not mention potential failures, rate limits, or authorization needs. Adds useful behavioral 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?

One sentence that front-loads the purpose and lists key options. Concise with no fluff, though slightly long. Could be split for readability but not necessary.

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, description explains returns. Parameter coverage is full. Still lacks details on error handling or edge cases, but is sufficient for a straightforward summarization 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 description coverage is 100%, baseline 3. Description adds human-readable enumeration of format and length options and mentions return fields, but does not add significant 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?

Clearly states verb 'summarize' and resource 'text', with configurable aspects (length, format, focus). Distinguishes from sibling tools like translate, sentiment, code_review which deal with other text operations.

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?

Implies usage for text summarization with clear options, but does not explicitly state when not to use or recommend alternatives. No exclusions provided, but context is clear enough.

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?

Since no annotations are provided, the description must convey behavioral traits. It explains the return types (full research, abbreviated metrics, AI analysis) but omits details on data freshness, rate limits, or authentication requirements. Sufficient for a straightforward comparison tool.

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 concise: two sentences that immediately state the action and output. No filler, front-loaded with key 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?

Despite no output schema, the description clearly outlines the three types of results returned. This is sufficient for an agent to understand the tool's complete behavior.

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 descriptions are brief but cover all parameters. The description adds context beyond the schema by explaining the comparison logic and output structure. With 100% schema coverage, baseline is 3; the description adds marginal value.

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: comparing a primary token against up to 3 others. It specifies the output format (full research, abbreviated metrics, AI analysis), distinguishing it from sibling tools like token_research which likely focus on single 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 multi-token comparison but does not explicitly state when to use it versus alternatives like token_research or token_risk_metrics. No when-not or alternative tool references 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?

No annotations are provided, so the description carries full responsibility. It mentions 'basic risk assessment' but does not explain the assessment criteria, nor does it disclose any non-obvious behaviors (e.g., data freshness, API dependencies). The read-only nature is implied but not explicit.

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 core purpose. Every word contributes value, with no redundancy or 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?

Given the absence of an output schema, the description should ideally explain the return format. It mentions outputs (price, market cap, volume, risk assessment) but lacks detail on structure, precision, or error handling. For a tool with many sibling tokens, a more complete description would aid selection.

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 both parameters (chain with enum and default, address as required string). The description adds no additional semantic meaning beyond 'EVM or Solana', which is partially covered by the chain enum. 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 a lightweight token lookup for price, market cap, volume, and basic risk assessment, and specifies it works for EVM or Solana tokens. This distinctly differentiates it from more specialized sibling tools like token_research or token_risk_metrics.

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 uses 'lightweight' to imply it is a quick, high-level lookup rather than deep analysis, but it does not explicitly state when to use this tool versus alternatives like token_compare or token_research. No exclusions or prerequisites 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?

With no annotations, the description should disclose behavioral traits like idempotency, auth needs, or potential delays. While 'aggregates' implies read-only and multi-source fetching, it does not detail rate limits, caching, or error behavior. This is adequate 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 two sentences with no wasted words. It front-loads the core purpose ('Multi-source token intelligence') and lists key data sources and modules in a compact, scannable way.

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 (multi-source, multiple modules) and no output schema, the description lacks detail on return format or structure. It mentions modules but not what each returns. For a research tool, more output context would be 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%, so the baseline is 3. The description adds no new meaning beyond the schema; it merely restates module names already listed in the include parameter. No additional context on parameter values or format is provided.

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 ('research') and clearly defines the resource ('token intelligence'). It enumerates the data modules and sources, distinguishing it from siblings like token_compare (comparison) or token_risk_metrics (risk-only) by emphasizing its multi-source aggregation.

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 no guidance on when to use this tool versus alternatives such as token_compare or token_intel. It lacks explicit 'when-to-use' or 'when-not-to-use' statements, leaving the agent to infer 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 full burden. It details the computed metrics and the pre/live computation distinction, which clearly communicates the tool's behavior as a read-only analysis. However, it does not mention that no state changes occur, though that is implied.

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: the first enumerates the metrics concisely, the second provides a crucial performance note. Every word adds value with no redundancy or 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?

The tool is moderately complex with multiple metrics and a composite score, yet no output schema exists. The description lists the metrics but does not describe the output format (e.g., numerical values, structure). This is a minor gap that prevents a perfect score.

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 baseline is 3. The description does not add parameter-specific details beyond what the schema already provides (address pattern, chain enum with default). It only states 'any ERC-20 token,' which is redundant with 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 quantitative risk metrics for ERC-20 tokens, listing specific metrics (holder concentration, permissions, liquidity, deployer history, composite score). It distinguishes itself from sibling tools like token_intel, token_research, and the Solana-specific solana_token_risk_scan by focusing on EVM-based ERC-20 risk analysis.

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 mentions pre-computed vs live-computed, hinting at performance differences but does not explicitly state when to use this tool over alternatives or provide exclusion criteria. The context of siblings is implicit but not elaborated.

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. States it preserves formatting and cultural nuances, but does not disclose behavioral traits like rate limits, authentication needs, or whether translation is deterministic.

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 with clear purpose, front-loaded. 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?

Good parameter descriptions but lacks detail on output format, error handling, or return value structure. No output schema available to compensate.

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

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

Schema coverage is 100%, so baseline 3. Description adds value by noting auto-detection of source language and quality guarantees (preserves formatting, cultural nuances), which go 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?

Description uses specific verb 'translate' and resource 'text', includes tone control and auto-detection features, clearly distinguishing from sibling tools like summarize or sentiment.

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 explicit guidance on when to use this tool versus alternatives (e.g., summarization or specialized translation tools). Implies general translation use but lacks exclusions or comparisons.

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 explains what is decoded (function call, params, tokens, explanation) but does not explicitly state that the tool is read-only, non-destructive, or any side effects. Given a decode tool, this is adequate but could be more explicit.

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, front-loaded sentence that conveys the purpose and scope without any wasted words. Every part 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?

With only 2 parameters and no output schema, the description sufficiently explains the tool's behavior and return values (function call, parameters, token transfers, explanation). It is complete for a decode 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% with descriptions for both parameters (chain and txHash). The description does not add any semantic meaning beyond what is already in 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 specifies the verb 'Decode' and the resource 'EVM transaction', listing specific components like function call, parameters, token transfers, and plain-English explanation. This clearly distinguishes it from siblings such as solana_tx_explain.

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 states it decodes 'any EVM transaction' and implicitly contrasts with Solana-specific tools in the sibling list, but it does not explicitly state when not to use or 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?

Without annotations, the description should disclose behavioral traits like read-only nature, authorization needs, or rate limits. It only describes functionality and does not address these 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?

The description is two sentences, front-loaded with actions and outputs, with no unnecessary words. It is efficient and 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?

The description covers purpose, inputs, and outputs but lacks details on data freshness, complexity, or differentiation from sibling tools. Adequate but not complete.

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 parameters are well-described in the schema. The description adds no additional semantic value 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 performs a comprehensive wallet safety check including approval scanning, activity analysis, and contract risk assessment. However, it does not explicitly differentiate from sibling tool 'approval_scan' which may overlap.

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 like approval_scan or token_risk_scan. The description lacks context on 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.