CIPHER x402 — Paid Solana & Crypto Tools

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

With no annotations, the description fully bears the burden of behavioral disclosure. It openly states the snapshot is updated with each release, should be treated as a hint, and that cross-checking is necessary. It also notes the tool is free, no payment required, which is valuable 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?

The description is three sentences, each earning its place: first defines purpose, second adds usage guidance, third addresses limitations and cost. No redundant language, 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?

The description explains the output type (curated snapshot, platforms, purpose) and limitations (stale data, need to cross-check). Without an output schema, it could benefit from a brief mention of what fields or structure the snapshot contains, but overall it is sufficiently complete 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?

The tool has zero parameters, so schema coverage is 100% (empty schema). Per guidelines, baseline is 4 for 0 parameters. The description adds no parameter information because none 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 it returns a curated snapshot of live audit competitions and bug-bounty programs from specific platforms (Code4rena, Cantina, Sherlock). It uses strong verb 'Return' and specifies the resource. It distinguishes itself from sibling tools which are unrelated.

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 mentions this tool is 'useful for solo wardens triaging which contests to enter', providing clear usage context. It does not explicitly state when not to use or offer alternatives, but the caveat to cross-check adds important guidance.

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

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

With no annotations, the description carries full burden. It discloses the tool's paid nature ($0.01 USDC) and the two distinct behavioral paths based on '_payment' presence. It does not cover edge cases like invalid wallets, but the core behavior is 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?

Three sentences: first states purpose, second covers payment detail, third explains behavior without payment. 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?

Given no output schema and only two parameters, the description covers all essential aspects: return data (positions, collateral, PnL, liquidation risk), payment gate, and the two response modes. It is sufficient for an AI agent to understand usage and outcomes.

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%. The tool description adds context beyond the schema: it explains the two modes for '_payment' (present vs absent) and reinforces that 'wallet' is a Base58 address. This adds meaningful usage nuance.

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 explicitly states the tool checks a Solana wallet's exposure to Drift Protocol, listing specific data points (open perp positions, collateral, unrealized PnL, liquidation risk distance). It distinguishes from sibling tools like solana_wallet_scan by focusing on Drift Protocol exposure.

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 clearly explains the payment mechanism: passing a signed x402 v2 authorization as '_payment' unlocks the full response, while omitting it returns the accept-list. However, it does not explicitly guide when to use this tool versus alternatives (e.g., other Solana tools among siblings).

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 and exceeds it. It discloses k-anonymity, that no plaintext is sent, the price, and the exact behavior with and without the _payment parameter. This is 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?

Three sentences, front-loaded with the key action, followed by essential details. Every sentence contributes meaning without 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?

The description covers all relevant aspects: purpose, usage conditions, parameter behavior, and response scenarios (with/without payment). No gaps remain for a tool with two parameters and 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%, so baseline is 3. The description adds value by explaining the role of _payment (402 behavior) and the k-anonymity context for sha1_prefix, going beyond the schema's pattern and examples.

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 checks a password hash prefix against the HIBP breach corpus using k-anonymity. It uses a specific verb ('check') and resource, and distinguishes itself from siblings by highlighting the privacy-preserving approach and payment model.

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 when to use the tool (to check a password breach without sending plaintext) and the payment requirement. It does not explicitly list when not to use it or provide alternatives, but the context of k-anonymity and pricing is 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, so description carries full burden. Discloses paid nature, pricing ($0.01), required authorization (x402 v2), and return structure (per-exchange rates, OI-weighted aggregate, divergence, max/min). Does not explicitly state read-only or non-destructive behavior, but implied by data-fetch nature.

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 packed with useful information in a logical order: purpose, venues, return fields, pricing, payment. Each sentence earns its place, though slightly long. Could be trimmed slightly but still 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, description covers all key aspects: input, payment, return fields, and error handling (402). Adequately prepares an agent to use the tool correctly.

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

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

Schema covers both parameters with descriptions (100% coverage). Description adds value by providing example tickers for symbol and explaining the role of _payment in detail, including the accept-list behavior.

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

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

Specific verb 'Fetch' paired with precise resource 'perpetual-futures funding-rate intelligence for a given base asset'. Lists 17 venues, clearly distinguishing from any potential 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 instructs when to include the _payment parameter for full response and what happens without it (returns 402 accept-list). Mentions target audience (perp-arbitrage bots). No direct alternatives named, but context is 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?

Despite no annotations, the description comprehensively discloses behavior: returns cleaned latest observations, costs $0.005 USDC, requires signed x402 payment, and returns a 402 accept-list if payment is absent.

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 pack essential information: purpose, examples, payment details, and fallback behavior. No redundancy or 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?

Lacks output schema, but description mentions 'cleaned latest observations' which gives a general idea. For a simple data fetch tool, this is adequate, though specifying return structure 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%, so parameters are documented. The description adds value by explaining _payment's role (unlock paid response) and providing examples for series_id, but the schema already provides 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?

Description clearly states the tool fetches a FRED series by ID, provides concrete examples ('DGS10', 'WALCL'), and specifies it returns cleaned observations. No sibling tools overlap, so differentiation is not needed.

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?

Clearly explains when to use (need FRED data) and how to use the payment mechanism. While it does not explicitly mention when not to use or list alternatives, the siblings are unrelated, so no confusion arises.

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 reveal behavioral traits. It explains the payment requirement and the dual behavior (with/without payment). However, it does not disclose any side effects, rate limits, idempotency, or error handling beyond the 402 case.

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 (four sentences), front-loaded with the main action, and structured logically. Every sentence adds necessary context without 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 (2 params, no output schema), the description adequately explains the workflow and response types (markdown content vs. accept-list). It lacks details on error cases or output format, but these are minor given the 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?

The input schema already covers both parameters with descriptions. The tool description adds no new information about parameter semantics beyond what the schema provides. With 100% schema description coverage, 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 action ('Fetch a CIPHER premium chapter (markdown)') and lists all four available chapter slugs, making the purpose explicit and distinct from any 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 explains when to use this tool (to fetch a premium chapter) and what happens without the required payment (returns a 402 accept-list). However, it does not explicitly state when not to use it or mention 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 provided, so description carries burden. Discloses the paywall and authentication flow via x402. Lacks details on rate limits, data freshness, or error handling, which would improve 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?

Two sentences: first covers core functionality and return value, second explains payment flow. Efficient and front-loaded with no superfluous 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?

Describes return format (0-100 score with per-factor breakdown) and payment mechanism. Given no output schema, this is adequate. Missing details like pagination or depth of breakdown, but overall sufficient for a paid API 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%, so schema already documents parameters. Description adds no extra meaning for 'owner' or 'repo' beyond schema. The _payment parameter behavior is explained in description, but overall adds minimal value over 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 identifies the tool as scoring GitHub repository health with specific factors listed (commit cadence, issue-close latency, etc.). Distinguishes itself from diverse sibling tools by focusing on repo health 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?

Provides clear context on payment requirement and behavior when _payment is omitted. Does not explicitly state when to use vs alternatives, but the unique functionality and sibling diversity make this less critical.

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, but description discloses paid nature, x402 authorization requirement, and fallback behavior. Includes input constraints (slot_probability range) and output description.

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?

Concise 5-sentence paragraph. Purpose is front-loaded. Every sentence adds necessary information without 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?

No output schema, but description covers return values (tip lamports + EV breakdown), all inputs, and payment mechanism. Sufficient for an agent to use correctly.

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

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

Schema coverage is 100%, so baseline 3. Description adds units (USD, [0..1]) and explains the role of _payment. Also mentions return format, which helps interpret inputs.

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 'Compute an expected-value-maximizing Jito tip for a Solana arbitrage bundle.' Verb and resource are specific. No sibling tool overlaps with this domain.

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?

Explains when to include the payment parameter and what happens without it. Context is clear, but no explicit when-to-use vs alternatives since siblings are unrelated.

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 key behaviors: searching multiple name types in parallel and the payment mechanism (402 accept-list if unpaid). It could mention error handling or rate limits but is transparent enough.

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

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

The description is four sentences, front-loaded with purpose, and each sentence adds necessary information without 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 no output schema and no annotations, the description adequately covers what the tool does and returns. It could mention output format or error cases but is largely complete for its complexity.

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

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

Schema coverage is 100%, but the description adds context about parallel name search and defaults (limit: 10). It also explains the payment parameter behavior, adding value 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 it is an openFDA drug adverse-event lookup for the last 12 months, specifies the returns (top reactions, report count, seriousness breakdown), and distinguishes itself from sibling tools like pubmed_medical_search and usda_food_nutrition.

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 when to use (for adverse event data) and includes the payment prerequisite. However, it does not explicitly state when not to use or provide 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?

With no annotations, description fully discloses payment requirement, pricing, fallback behavior (402 accept-list), and output structure. No contradictions.

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 covering purpose, pricing, and authorization mechanism. No extraneous 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?

Covers key aspects: input, output, payment flow. Lacks mention of error handling or rate limits, but sufficient for typical invocation.

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 both parameters with descriptions; description adds important context on '_payment' (x402 v2 authorization, effect on response) 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?

Clear specific verb ('forward geocode') and resource ('OpenStreetMap Nominatim'), with explicit output (lat/lon, normalized address block, match_quality). Differentiates from sibling 'osm_reverse_geocode' by direction.

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?

Explains how to invoke with optional payment parameter and consequences of omitting it. Lacks explicit comparison to alternatives but provides sufficient context for 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. It discloses the payment flow: cost ($0.001), requirement for a signed x402 v2 authorization, and the two possible responses (paid result vs 402 accept-list). It also mentions the output structure. This is good transparency for a monetized tool, though it doesn't cover error handling 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 concise (three sentences) and front-loaded. The first sentence states the core purpose, the second adds pricing and output, and the third details the payment argument. Every sentence serves a purpose 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 no output schema, the description adequately explains what the tool returns (normalized address + place class/type). The payment flow is fully described. Missing details like error codes or rate limits, but the core functionality and monetization model are sufficiently covered for an agent to invoke the tool correctly.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds value beyond the schema: it explains that '_payment' is optional and describes its behavior (forwarded if present, returns 402 list if absent). For 'lat' and 'lon', the schema already provides clear descriptions, so the tool-level description doesn't need elaboration.

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 does 'Reverse geocoding via OpenStreetMap Nominatim. lat/lon → normalized address + place class/type.' This explicitly names the verb (reverse geocode), resource (OSM Nominatim), and output. It also naturally distinguishes from the sibling 'osm_geocode' which does forward geocoding.

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 the payment mechanism and the two modes (paid vs unpaid response). However, it does not provide explicit guidance on when to use this tool over alternatives like 'osm_geocode'. The usage context is implied through the payment requirement but not explicitly 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?

No annotations are provided, so the description fully bears the responsibility. It fully discloses the paywall mechanism (x402 authorization, $0.005 USDC), the enriched return format (pmid, title, authors, etc.), and the fallback 402 accept-list response. No contradictions.

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 moderately sized (4-5 sentences) and front-loaded with the main purpose. Each sentence adds necessary context, but could be slightly trimmed without losing meaning.

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 thoroughly explains the return value structure and the payment process. For a search tool with 3 parameters, it is complete and actionable.

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?

All three parameters have schema descriptions (100% coverage). The description adds value by explaining the enrichment block and payment flow, going beyond the schema definitions.

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 'Search' and resource 'PubMed (NCBI) for medical / life-sciences literature'. It is specific and distinct from sibling tools, which are unrelated (e.g., osm_geocode, fred_macro_series).

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 notes it is 'Ideal for medical RAG agents', providing a clear use case. However, it does not explicitly state when not to use it or mention alternatives, though siblings are unrelated, so no confusion arises.

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, but description fully discloses payment gate behavior: without '_payment' returns 402 accept-list; with it, returns findings and referral CTAs. Pricing and authorization method are clearly stated.

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

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

Four sentences, no redundancy. Front-loaded with what the tool does, followed by payment details. Every sentence adds essential 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?

Given two simple parameters and no output schema, the description covers core functionality and payment flow adequately. Lacks detail on response format, but not critical for an agent to select and invoke correctly.

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

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

Both parameters are described in schema (100% coverage). Description adds value by explaining the payment mechanism and the conditional behavior of the '_payment' parameter, going beyond schema's basic 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?

Description clearly states the action ('Scan a Solana wallet') and specific resources (portfolio value, dust accounts, stale stake accounts, low-liquidity warnings). It clearly differentiates from sibling tools such as solana_wallet_security_audit_rules.

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 explains the tool's purpose and the prerequisite of x402 payment for full response. It does not explicitly state when not to use it, but the context is clear given sibling tools are dissimilar.

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 disclose behavioral traits. It states that the tool is free and returns metadata, implying it is a safe read operation. However, it does not mention idempotency, authentication requirements, or any side effects, which are minor gaps for a metadata 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 a single sentence, but it is somewhat long due to enumerating many anti-patterns. However, it front-loads the core purpose ('Return metadata for...') and the list is relevant. Every part earns its place, but brevity could be improved slightly.

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 parameters and no output schema, the description is fairly complete. It explains what the tool returns (metadata for a ruleset) and what the ruleset covers. It also notes that it is free. It might lack detail on the metadata 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?

The tool has no parameters (schema is empty with 100% coverage). As per guidelines, baseline is 4 for zero parameters. The description adds no parameter info because none exists.

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 returns metadata for a specific ruleset and enumerates what the ruleset catches. The verb 'Return metadata' is specific and the resource (ruleset) is clearly identified. It does not explicitly distinguish from sibling tools like solana_wallet_scan, but purpose is still clear.

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. It only describes what the tool returns, not any context for its use, such as prerequisites or comparison to other 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?

With no annotations provided, the description fully discloses the payment mechanism: it requires a signed x402 v2 authorization via the '_payment' parameter to unlock the paid response, and without it returns a 402 accept-list. The description also states it returns a clean macro block plus alternates, giving clear behavioral expectations.

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 about five sentences and front-loads the purpose ('USDA FoodData Central nutrition lookup'). It is efficient and all sentences add value, briefly covering input, output, and payment. However, it could be slightly more structured (e.g., bullet points) for easier scanning.

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 the return of a 'clean per_100g macro block' and alternates but does not detail the full return format (e.g., food name, description, or how alternates are structured). There is no output schema to compensate. Error handling and edge cases (e.g., invalid query) are not addressed. For a paid tool, this is 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 description coverage is 100% with all three parameters described in the schema. The description adds value for the '_payment' parameter by explaining the x402 v2 authorization format and that it unlocks the paid response. For 'query' and 'limit', the schema descriptions suffice, but the extra payment context raises the score above baseline 3.

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 'USDA FoodData Central nutrition lookup' and specifies what it returns: 'best-matching record with a clean per_100g macro block' plus alternates. This distinguishes it from sibling tools which are unrelated (e.g., solana_wallet_scan, pubmed_medical_search).

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 says 'Query any food (brand or generic)' and explains the payment workflow, but does not provide when to use this tool versus alternatives or any conditions to avoid using it. It implicitly assumes the user wants nutrition data but offers no comparative guidance.

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