Myworker — 20 paid crypto & AI micro-APIs (x402)

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

With no annotations, the description carries the full behavioral burden, and it does disclose real operational context: the price ($0.0100 USDC per call), the POST endpoint, the x402 payment scheme, and that data is live. It stops short of covering rate limits, retry behavior, or what happens if more than 5 tokens are supplied, but the payment/auth disclosure is well beyond typical.

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?

Purpose and returned metrics are front-loaded, then input format, then commercial/execution details — a sensible order with little waste. Minor redundancy between the metric list and the 'one call replaces five' claim, but it stays compact.

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?

There is no output schema and no annotations, so the description must stand in for both, and it does list the returned fields and the payment/transport requirements. It would be fully complete with a note on limits (e.g., >5 tokens, invalid symbols), but nothing essential for invoking it correctly is missing.

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

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

Schema description coverage is 100% for the single 'token' parameter, so the schema already documents the comma-separated format and the 2-5 limit. The description restates that ('Input: "token" (dipisah koma)') without adding syntax or edge-case detail, so the baseline 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 gives a specific verb and resource — comparing 2 to 5 Solana tokens side by side — and enumerates the exact metrics returned (price, liquidity, mcap, 24h change, holders, organic score) plus per-metric winners. The line 'Satu panggilan ganti lima' implicitly separates it from calling harga repeatedly, but no sibling is named explicitly, so it falls just short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states the input format and the 2-5 token range, which implies 'use this when comparing several tokens.' However, it never says when NOT to use it or points to the obvious alternative (harga) for single-token lookups, so the routing guidance is only implied.

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

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

With no annotations, the description carries the full behavioral burden and does disclose genuinely useful context: a fixed price of $0.0050 USDC per call, the x402 payment requirement, the POST endpoint, the upstream source and its fallback, and that data is live. It stops short of covering rate limits, error/failure behavior, or whether calls are cached, so it is strong but not exhaustive.

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 purpose is front-loaded and the '||' separator keeps sections scannable, which is good. However, the literal POST URL and the partial restatement of the input parameters duplicate what the runtime and schema already convey, so not every sentence 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?

For a two-parameter, annotation-free, output-schema-free tool, the description supplies the essentials an agent needs: what it returns (live FX rates, MYR inclusive), the cost model, the transport, and the input contract. The main gap is that no output schema exists and the description does not sketch the response shape (e.g. rate fields per target currency), which would help an agent parse results.

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 both parameters are already documented in structured form, including the comma-separated format and the default target set. The description merely restates 'dari' (base code) and 'ke' (comma-separated targets) without adding format, constraint, or edge-case detail beyond the schema. Baseline 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?

States a concrete purpose: current currency exchange rates, names the data sources (open.er-api.com with ECB Frankfurter fallback) and the MYR coverage, and sketches the input shape. It is clearly distinguishable from data-processing siblings like json or terjemah, but it never names or contrasts with near-neighbours such as harga or quote, so sibling differentiation is left implicit.

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?

There is no statement of when to choose this tool over alternatives (harga, quote, banding-token), no exclusions, and no preconditions beyond the input format. The only usage-adjacent content is the parameter syntax, which duplicates the schema rather than guiding selection.

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

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

With no annotations, the description carries the full behavioral burden and does disclose meaningful traits: a fixed cost ($0.0050 USDC per call), the x402 payment protocol, the POST endpoint, and that data is returned directly. It omits rate limits and error behavior, so it is strong but not exhaustive.

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 functional summary is front-loaded and the pricing/execution details are cleanly separated by a delimiter, so key info is easy to scan. It is slightly verbose and the trailing 'data/langsung' is cryptic, keeping it short of a 5.

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 single-parameter tool with no output schema or annotations, the description supplies the returned fields, input convention, cost, and execution endpoint, which is enough to call it correctly. Deeper detail on response shape or failures is the only gap.

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

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

Schema description coverage is 100%, so the schema already documents the single 'token' parameter. The description only restates the comma-separated symbol/mint convention already present in the schema, adding no new meaning, which fits the baseline of 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?

States a specific resource (token) and enumerates the returned fields (USD price, liquidity, 24h change, decimals), so an agent knows exactly what it fetches. It does not, however, explicitly contrast itself with sibling crypto tools like banding-token, quote, or tokens-baru, leaving differentiation to inference.

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?

Usage is only implied: the description gives the input format (symbol or mint, comma-separated) but never states when to prefer this over banding-token, quote, or trending. No exclusions or prerequisites are offered, so the agent must infer the right context.

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

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

With no annotations, the description carries the burden and does disclose meaningful traits: the result is heuristic, costs $0.0200 USDC per call, is executed via POST to a specific x402 endpoint, and returns data directly. It does not describe failure modes, rate limits, or confirm the operation is a read-only scan.

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 purpose and scanned scope are front-loaded in one dense clause, followed by input and pricing details. It is compact and mostly earns its sentences, though the execution/pricing boilerplate is somewhat tangential to the core capability.

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 single-parameter tool with no output schema and no annotations, the description is fairly complete: it implicitly lists the return contents (code, metadata, proxy status, risky selectors), specifies the input format, and documents cost and transport. Missing only error behavior and explicit read-only confirmation.

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 there is a single parameter, so the schema already carries the semantics. The description merely restates the input ("token", alamat 0x…) without adding format, chain, or validation meaning 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 names a specific verb (imbas/scan) and resource (ERC-20 contract on Base) and enumerates exactly what is inspected: code, name/symbol/decimals/supply, EIP-1967 proxy, and risky selectors. It never names or contrasts a sibling, so it falls short of the top band despite being highly specific.

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?

Usage is only implied: an agent can infer you call this to vet a token address before interacting with it, but there is no explicit when-to-use/when-not guidance and no routing to alternatives like risiko or saring-token. The pricing and execution note adds context but not selection 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?

No annotations are provided, so the description carries the full burden. It usefully discloses the cost ($0.0050 USDC per call), the x402 payment scheme, and the exact POST endpoint — real behavioral context beyond the schema. However, it says nothing about failure modes, whether malformed text errors out, or any rate/auth constraints.

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?

Front-loaded with the core purpose, then pricing and execution details, in a compact form. The "||" separator is slightly awkward but the content is efficient and every clause carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter extraction tool, the description covers what it does, how the output is shaped (valid JSON via schema), and the cost/transport. With no output schema, it does signal the return type (valid JSON); only error behavior and edge cases are missing.

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 both parameters (text, skema) are already documented in the schema. The description restates them ("Input: text", shape via "skema") but adds no format, syntax, or constraint detail beyond what the schema provides, so the baseline 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?

States a specific verb+resource: converting unstructured text into valid JSON, with the shaping mechanism ("skema") named. The purpose is immediately clear, though it offers no differentiation from siblings (none of which are JSON-extraction tools, so little differentiation is 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?

No when-to-use or when-not-to-use guidance is given, and no alternative is named. The only contextual cue is the pricing line, which implies the call is paid and should be used deliberately, but that is not framed as usage 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 the full behavioral burden and does disclose meaningful traits: the exact price ($0.0050 USDC per call), the x402 payment protocol, the POST endpoint, that Solana data comes from a free public RPC while others are live eth_gasPrice, and that a USD estimate is included. It does not mention rate limits or failure/timeout behavior, which keeps it short of a 5.

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?

Front-loaded with the capability (live gas for four chains plus Solana tip), then the optional input, then pricing/transport in a compact '||' separated block. Every clause carries information. The endpoint URL and pricing token make the second half denser than it needs to be, but nothing is wasted.

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 no-annotation, no-output-schema tool with one optional parameter, the description covers what an agent needs: what data is returned (chain gas prices plus Solana tip plus a 21k-gas USD estimate), the cost and payment mechanism, and the transport. Only rate-limit and error-handling context is absent, which is a minor gap.

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

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

Schema description coverage is 100% and the single parameter is already documented in the schema ('base | ethereum | arbitrum | optimism | solana | kosong = semua'), so the baseline is 3. The description only restates the parameter name and adds example values ('cth base / sol / ethereum'); it contributes no new semantics such as default network or invalid-value 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?

States a specific verb+resource: fetch live gas price via eth_gasPrice for Ethereum, Base, Arbitrum, Optimism, plus Solana priority tip, with a USD estimate for a standard 21k transfer. That is concrete and unambiguous. However it never distinguishes itself from the sibling 'yuran-rangkaian' (network fee), which an agent could plausibly confuse it with.

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?

Usage is only implied: you call it when you need a current gas price, and 'rangkaian' is optional with 'kosong = semua' meaning all networks. There is no explicit when-to-use, when-not-to-use, or pointer to an alternative sibling for fee-related questions. Adequate but leaves routing to inference.

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 the full burden and does disclose meaningful non-schema behavior: cost ($0.0200 USDC per call), the POST endpoint, and that payment/execution uses x402 with 'data/langsung'. The main gap is that it doesn't describe the output shape or failure behavior, but pricing and payment context are genuinely valuable.

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?

Front-loads the action, then inputs, then pricing/execution using a clean '||' separator. Every clause carries information, though the Malay/English mix and the endpoint URL add some density without waste.

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 no-output-schema, no-annotation combined tool, the description covers what it does, its inputs, cost, and execution method. It stops short of explaining the returned summary/Markdown structure, but overall an agent has enough to invoke it 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 the schema already documents url, arahan, and had. The description restates the same three inputs with matching glosses ('apa yang hendak difokuskan', 'bilangan aksara') and adds no format, range, or default detail beyond what the schema provides, so the baseline 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?

States a specific compound operation: fetch a URL, convert to clean Markdown, and summarize with AI 'dalam SATU panggilan' (in one call). This distinguishes it conceptually from the sibling pair kikis-web and ringkas by emphasizing the combined single call, though it never names those siblings directly as alternatives.

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 phrase 'dalam SATU panggilan' implies the tool exists to avoid chaining kikis-web + ringkas, but there is no explicit when-to-use or when-not-to-use guidance and no conditions under which a separate scrape or summarize call is preferable.

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

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

With no annotations, the description carries the burden well: it discloses what is removed (menus, scripts, ads), that the output is Markdown, the price ($0.0200 USDC per call), the x402 payment mechanism, and the POST endpoint. It omits error/truncation behavior when a page exceeds the character limit, which keeps it short of a 5.

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?

Front-loads the value proposition, then gives inputs, then pricing/transport in a compact second segment. Slightly dense with the endpoint and protocol string, but every element is operational and earnable.

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 two-parameter, no-output-schema fetch tool, the description covers what it returns, what it strips, the cost and the transport, which is close to sufficient. It stops short of explaining truncation/pagination behavior when the Markdown exceeds the limit.

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

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

Schema description coverage is 100%, so the baseline is 3; the description only restates the same 'url' and 'had' (500-40000) facts already in the schema without adding format or default-value nuance beyond it.

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?

States a concrete verb+resource+outcome: fetch a URL and return cleaned Markdown with menus, scripts and ads stripped. An agent can tell it apart from summarization-style siblings (kikis-ringkas, ringkas) by the raw-extraction framing, though it never names them explicitly.

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 its niche with 'jimat token untuk agen AI', signalling it is the token-efficient path for pulling page content. However, it gives no explicit when-to-use/when-not guidance and never references an alternative among the many 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 delivers notably rich context: it scans 2-leg and 3-leg paths, returns net profit after fees, caches data for 30s, costs $0.0200 USDC per call, and uses an x402 POST endpoint for live data. Caching, pricing, and payment model are all disclosed. It could say more about rate limits or error behavior, but this is strong for a no-annotation 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?

Two sentences, front-loaded with the core scan-and-return behavior, followed by the operational pricing/endpoint details. It is dense with a URL and pricing block but every element is functional; little waste.

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 zero-parameter tool with no output schema, the description conveys what is returned (best opportunity with net profit after fees), the data freshness (30s cache), and the call cost. That is sufficient for an agent to decide whether to invoke it.

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

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

The input schema has zero parameters, so there is nothing to document and the baseline of 4 applies. The description correctly implies a parameterless invocation.

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?

States a specific verb and resource: scanning multiple sizes and paths (2-leg and 3-leg) on Jupiter and returning the best net-profit opportunity. This is clearly distinct from price-oriented siblings like quote and harga. It stops short of naming a sibling to differentiate explicitly, but the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains what the tool does but never says when to prefer it over siblings like quote or yield-defi, nor any prerequisites or exclusions. There is no when-to-use/when-not guidance beyond the implied arbitrage scenario.

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 does well: it discloses price ($0.0200 USDC per call), the payment protocol (x402), the transport (POST endpoint), and that data is live. It does not cover failure modes, rate limits, or what happens when the wallet does not exist, which keeps it from a 5.

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 capability statement is front-loaded in one dense sentence, then the use case, then commercial/transport metadata after a separator. No filler, and the ordering puts the most decision-relevant information first.

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 one-parameter tool with no output schema, the description enumerates the returned fields, the cost, and the invocation protocol, which is nearly everything an agent needs. Remaining gaps (error behavior, response shape specifics) are minor.

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

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

Schema coverage is 100% and the single parameter is already documented as a base58 Solana address. The description only restates the input name ('dompet') and adds no format, constraints, or validation detail beyond the schema, so the baseline 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?

States a specific verb and resource (check a Solana wallet) and enumerates exactly what is inspected: existence, SOL balance, account type, owner program, activity count/timing, plus risk warnings. This is clearly distinguishable from siblings like harga, risiko, or tokens-baru, which cover price, generic risk, and token discovery.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit use context – bots verifying a user before a transaction – which tells the agent when this tool fits. It stops short of naming alternatives or stating when not to use it, so it is clear context without 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 behavioral burden. It does disclose genuinely useful context: paid access at $0.0100 USDC per call, the x402 protocol, the POST endpoint, and live data. It does not clarify that this is quote-only and executes no transaction, nor does it mention rate limits or the failure modes of a live pricing endpoint.

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 useful content is front-loaded: what it returns, then the inputs, then cost and transport. It is compact and each clause carries information. The mixed-register and the '||' separator are slightly awkward but cost nothing in comprehension.

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, the description correctly names the return fields (outAmount, priceImpact, route), and it covers inputs, cost, and access method. An agent has enough to invoke it. The only real gap is the absence of any guidance on when this beats its pricing siblings.

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 three is the baseline. The description restates the same names and the same 'unit terkecil, cth lamports' note already present in the schema's 'jumlah' description, adding no new meaning beyond the structured fields.

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 states a specific verb+resource: fetch a real Jupiter swap quote and returns outAmount, priceImpact, route. That is concrete and tells an agent exactly what the tool produces. It does not, however, distinguish itself from adjacent siblings like 'harga' or 'fx-kadar', which are not mentioned.

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?

There is no explicit when-to-use statement, no prerequisite, and no routing to or away from alternatives such as 'harga' or 'fx-kadar'. The input enumeration implies usage but the agent is left to infer when a swap quote is the right call versus a plain price lookup.

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 the full behavioral burden and does disclose genuinely useful operational facts: a per-call price ($0.0050 USDC), the x402 payment protocol, and the POST endpoint the agent must hit. It does not cover input size limits, error/failure behavior, or retry semantics, which keeps it from a 5.

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?

Purpose is front-loaded in the first sentence, followed by a compact pricing/execution clause separated by '||'. The raw endpoint URL is arguably heavy, but it is actionable information for a paid micro-service, so the structure is efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter paid service with no output schema and no annotations, the description covers purpose, input, price, and protocol, and loosely describes output as compact points. It still omits input length limits, whether short text is valid, and any concrete return shape, so it is adequate rather than 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% for the single required parameter, and the description only restates it as 'Input: "text"'. That matches the baseline 3 – the schema does the work and the description adds no syntax, format, or length 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?

States a specific verb and resource: summarize long text into compact points. An agent immediately understands the operation. However, it does not differentiate itself from the related sibling 'kikis-ringkas', so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'teks panjang' implies the use case (long input text), giving implied usage guidance. There is no explicit when-to-use vs. when-not guidance and the similar sibling 'kikis-ringkas' is never mentioned, leaving the agent to guess which summarizer to route to.

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

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

With no annotations, the description carries the full burden. It usefully discloses cost ($0.0200 USDC per call), execution method (POST to a specific x402 endpoint) and that data is live. However, it does not state the output format, error behavior, rate limits, or explicitly confirm the operation is read-only.

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 compact sentences, front-loading the analytical purpose before cost and execution details. The '||' separator is slightly awkward but the content is efficient with no filler.

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 one-parameter analysis tool with no output schema and no annotations, the description lists checked metrics and invocation details but never describes the shape of the risk recommendation or return value. It is adequate to invoke, but leaves a meaningful gap about the output.

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 single parameter already documents 'Simbol atau alamat mint penuh.' The description merely restates the input as "token" and adds no format or syntax detail beyond the schema, so baseline 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?

States a specific action (semak risiko) and enumerates exactly what is inspected: mint authority, freeze authority, supply, decimals, liquidity and token age, plus a risk recommendation. The purpose is unmistakable, though it does not explicitly contrast itself with token-analysis siblings like banding-token or saring-token.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It only states the required input and invocation mechanics, leaving the agent to infer when it 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?

With no annotations, the description carries the full burden and does disclose valuable behavioral traits beyond structure: a concrete cost ($0.0200 USDC per call), the x402 payment protocol, the POST endpoint, and that data is live. It still omits rate limits, failure behavior, and explicitly confirming it is a read-only operation, keeping it short of a 5.

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?

It is front-loaded with the capability list before the input and pricing details, and every sentence carries information. It is somewhat dense with the price/execution block appended, but nothing is clearly wasteful.

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?

There is no output schema, but the description compensates by summarizing the returned artifacts (risk score 0-100 with reasons, liquidity depth, honeypot verdict). With no annotations, it also supplies the cost and payment model. Only error/edge-case behavior is missing, so it is largely complete for this 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% with only 2 parameters, so the schema already documents both 'token' (symbol or mint) and 'saiz_usd' (test size in USD, default 100). The description restates that token accepts a symbol/mint and that saiz_usd is optional, adding little beyond the schema, so the baseline 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 states a specific verb and resource (full safety screening of one token) and enumerates concrete outputs: mint/freeze authority, top-holder concentration, sell/honeypot test, liquidity depth at 5 sizes, safe trade size, and a 0-100 risk score. The phrase 'satu token' (one token) implicitly distinguishes it from the sibling banding-token, which compares 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?

Usage is implied by 'full safety screening of one token', so an agent can infer this is for vetting an individual token. However, it never names an alternative (e.g., banding-token for comparison) nor states when NOT to use it, leaving routing to inference.

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 does disclose meaningful operational facts: $0.0200 USDC per call, POST to a specific endpoint, x402 payment requirement, and that the response is a structured object rather than free text. It still says nothing about failure modes, rate limits, or language handling.

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?

Purpose and output shape are front-loaded, then a compact pricing/execution segment. Slightly dense and mixes two languages, but every clause carries information and nothing is repeated.

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?

There is no output schema, so the description must characterize returns — and it does (structured object with label, score -1..1, confidence, emotions, reason). Payment and transport details are covered. Only error behavior and input language support are unaddressed, which is minor for a one-parameter tool.

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

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

Schema coverage is 100% and there is only one parameter ('text', documented as 'Teks input'). The description mentions 'Input: "text"' but adds no format, length, or language constraints beyond the schema, so the baseline 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?

States a specific verb+resource (sentiment analysis of text/reviews/news) and enumerates the actual outputs: positive/neutral/negative labels, a -1 to 1 score, confidence, emotions and reason. No sibling in the list covers sentiment, so there is nothing to confuse it with.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It names the content types it applies to (teks/ulasan/berita), which implicitly tells the agent when to reach for it. There are no exclusions or alternatives offered, but no sibling tool performs sentiment, so the lack of routing guidance costs little.

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 disclosure burden and does meaningful work: it declares the price ($0.0050 USDC per call), the payment protocol (x402), the execution method (POST to a specific endpoint), and that the backend is a structured AI service. It stops short of describing error behavior, limits, or the exact response shape.

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?

Front-loads the purpose, then parameters, then commercial/execution details in a compact block. The pipe-delimited formatting is terse but every clause (languages, input, price, endpoint) earns its place; nothing is padded.

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 two-parameter translation tool with no output schema and no annotations, the description covers purpose, parameters, cost, and transport. The main omission is any statement of what comes back (translated string vs. structured payload), which the 'AI berstruktur' note only hints at.

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% and the description only restates the same facts the schema already carries ('to' target languages, 'text' input). No syntax, defaults, length limits, or format guidance is added 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?

States a specific verb+resource ('Terjemah teks' / translate text) and enumerates the supported target languages (ms|en|zh|ta). No sibling tool in the list performs translation, so there is nothing to disambiguate against, but the purpose itself is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description tells the agent which parameter carries the target language and which carries the source text, which implies usage. However, it gives no when-to-use/when-not guidance, no prerequisites, and no alternatives to consider.

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 does substantial work: it lists the implicit safety gates (mint and freeze authority must be disabled, small dev supply, liquidity/holder/top-10 concentration limits), honestly flags that "baharu" mode has unindexed liquidity, and discloses cost ($0.0100 USDC per call) and the x402 POST endpoint. It stops short of rate limits or what a rejected/failed payment returns.

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 dense sentences that front-load the resource and its screening criteria, then append mode semantics, pricing and endpoint. Every clause carries information, though the pricing/endpoint tail could reasonably live in structured metadata rather than the description.

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 six-parameter filtering tool with no annotations and no output schema, the description supplies the missing context: what qualifies a token, how the two modes differ, and what the call costs. The only real gap is that it never sketches the shape of the returned token list.

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 six parameters are already documented in the schema and the baseline is 3. The description reinforces the meaning of the threshold filters (liquidity/holders/top-10 must pass "your limits") and notes that maks_umur_hari applies only to organik mode, but adds little syntax or format detail 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 names a specific verb+resource: it returns filtered young Solana tokens that pass a stated safety screen, with a second "baharu" mode for raw recent launches. An agent can grasp the scope without opening the schema, but the description never distinguishes this tool from lookalike siblings such as saring-token or banding-token.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly contrasts the two modes: "organik" (default, young tokens with trading plus full screening) versus "baharu" (latest launches, audit only, liquidity not yet indexed). The condition selecting each mode is stated, though there is no guidance on when to prefer this tool over sibling filter/screener tools.

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

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

No annotations are provided, so the description carries the behavioral burden, and it does disclose important traits: paid call cost, x402 execution, POST endpoint, live data, and returned fields. It still lacks details on auth flow, rate limits, or error behavior, but the cost and execution disclosure is substantial.

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 key purpose and returned fields are front-loaded, and the pricing/execution note is clearly separated. There is some redundancy because the parameter options are repeated from the schema, but the description remains efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description usefully lists the returned token fields and adds cost, execution method, and live-data context. It is nearly complete for invocation, though it could say more about x402 payment/auth requirements and failure 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 description coverage is 100%, so the schema already documents all three parameters, including enums and ranges. The description mostly repeats those choices rather than adding new semantics, which fits the 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 states a specific verb and resource: listing Solana tokens that are hottest by Jupiter organic score or newest. It is clear, but it does not explicitly differentiate itself from sibling tools such as tokens-baharu or saring-token, so sibling routing is left implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains the available parameter choices, but gives no explicit guidance on when to use this tool versus alternatives like tokens-baharu, saring-token, or harga. Usage is only implied by the tool's purpose.

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 does well on the operational side: it discloses the per-call price ($0.0100 USDC), the x402 payment protocol, the concrete POST endpoint, and that output is structured AI-generated. The remaining gap is what the response actually looks like and whether calls can fail or be retried after payment.

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 compact segments: purpose and content types first, then price and execution details. The URL and x402 note are dense but operational information the agent genuinely needs, so little is wasted.

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 single-parameter generator with no output schema and no annotations, the definition covers purpose, cost, and transport. It still leaves the agent guessing about return shape, output language, length limits, and error/payment-failure behavior, which matter for a paid call.

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 'text' parameter, so the baseline is 3. The description adds only that 'text' holds the instruction ('Arahan dalam "text"'), which is marginal value over the schema's own 'Teks input' description and gives no length, language, or formatting guidance.

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 verb 'Jana kandungan' (generate content) is followed by concrete output types — captions, product descriptions, emails, ideas — so the agent knows exactly what the tool produces. It is clearly distinct from siblings like terjemah (translate) or ringkas (summarize), though it never names a sibling to reinforce that boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It tells the agent where to put the request ('Arahan dalam "text"') and what kinds of content are in scope, which implies when to use it. There is no explicit when-not guidance, no mention of alternatives to terjemah/ringkas for adjacent tasks, and no prerequisites beyond the payment note.

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 behavioral burden and does well: it declares the utility deterministic, states a price ($0.0050 USDC per call), payment protocol (x402), HTTP method and endpoint, and notes data is direct. It still omits rate limits, error behavior, and full output formats.

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 dense but front-loads the core operations and separates commercial/execution details with '||'. Every part earns space for an agent that must know both capability and payment/endpoint requirements, though the endpoint and price could be considered non-selection metadata.

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 4 parameters, no output schema, and no annotations, the description supplies enough context to select and call the tool: operations, input mapping, holiday constraints, price, payment method, and endpoint. It partly describes output formats (SHA-256 hex, unix + ISO UTC), but not return shapes for every operation.

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 already 100%, so the baseline is 3. The description goes further by mapping input to operation types: 'op' plus 'text' for encode/decode/hash, or year/country for holidays, and adds constraints like max 20 holidays and 100+ countries not present in the schema.

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

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

The description names the tool's deterministic utility purpose and lists specific operations: base64 encode/decode, SHA-256 hash, UUID v4, current time, and public holidays. This is far more than a restatement of the title, but it does not explicitly differentiate itself from any sibling tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It lists supported operations and states the input shape, but gives no when-to-use guidance, prerequisites, or alternatives among the many sibling tools. The user must infer that this is the tool for generic utility conversions.

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 behavioral burden and does so well: it discloses a 10-minute cache, the exact filter threshold, sort order, the $0.0100 USDC per-call price, the x402 payment/auth mechanism, and the POST execution URL. It does not cover failure modes or rate limiting, so it falls short of a full 5.

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 purpose and filter constraints are front-loaded in the first clause, and the price/execution metadata is clearly separated by '||'. It is dense but every element (filters, cache, price, endpoint) earns its place; only the Malay prose style slightly obscures the reading order.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only lookup tool with no output schema, the description covers source, filtering, sorting, caching and payment, which is most of what an agent needs to call it. The only gap is the shape of the returned data (fields per pool), which the description leaves unspecified.

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 both parameters (jumlah, stabil) are already documented in the schema with the same 1-10 / default-5 and stablecoin-only semantics. The description adds no format or behavioral detail beyond the schema, so the baseline 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?

States a precise verb+resource+scope: highest-APY DeFi pools across all chains via DefiLlama, filtered to TVL ≥ $10M and sorted by APY. This is specific enough to distinguish it from siblings like peluang, banding-token or risiko.

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 filter criteria (TVL ≥ $10M, sorted by APY) and the 'stabil' toggle imply when the tool is relevant, but there is no explicit when-to-use / when-not-to-use statement or any routing against sibling tools that may overlap. Usage is implied rather than 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 and does well: it discloses the $0.0050 USDC per-call price, the transport (POST to a specific x402 endpoint), and that data is live. It stops short of stating auth/payment mechanics or latency, but per-call pricing and protocol are meaningful 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?

Purpose and outputs are front-loaded, and the price/implementation trailer is compact and actionable. Slightly dense but every clause (returns, optional input, price, endpoint) 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?

No output schema exists, and the description compensates by listing the return fields (tip stats, cost estimate, TPS). Payment and endpoint are covered, and the single optional param is explained, leaving only minor gaps like exact response shape.

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

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

Schema coverage is 100% and the single parameter is already documented verbatim, including the empty-default behavior. The description restates but adds no syntax or format detail beyond the schema, so the 3 baseline for high coverage 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?

States a specific resource (Solana network fee) and enumerates exactly what is returned: priority tip distribution (min/median/p75/p90/max), cost estimate for a 200,000 CU transaction, and network TPS. This clearly separates it from siblings like harga and fx-kadar.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains the optional 'akaun' input improves estimation accuracy, which implies when to supply it, but gives no explicit when-to-use vs sibling guidance and no exclusions. Usage is implied rather than spelled out.

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