AgentsToolsHub

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 genuinely useful operating context: the computation is stateless, the reference date defaults to today in UTC (adding the timezone the schema omits), and the call is paid via x402 at $0.01 USDC on eip155:8453 — a cost/payment disclosure an agent must know before invoking. It does not cover error behavior for malformed or future dates, which keeps it out of the top band.

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 short sentences, front-loaded with the computation and its output, with the payment note last. The middle 'Use this when...' sentence is redundant with the opening and contains a grammatical slip ('needs to exact age'), a small amount of waste in an otherwise tight definition.

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 compensates by specifying the return shape (years/months/days plus total days lived). Combined with the default-date and pricing details, an agent has what it needs to call the tool; only input-validation/error semantics for invalid dates are unaddressed.

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 both parameters, so the baseline is 3. The description restates the default reference date ('defaults to today (UTC)') and the semantic role of 'birth', adding only the UTC qualifier beyond what the schema already documents.

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 and resource ('Calculate a person's exact age... from their date of birth') and even enumerates the output units (calendar years, months, days, total days lived). It is unambiguous on its own, but it never differentiates itself from the nearest sibling, calculators_date_difference_calculator, which an agent could easily mistake for the same computation.

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?

'Use this when an agent needs to exact age in years, months and days' is essentially a restatement of the purpose sentence rather than new routing guidance. There is no when-not condition and no mention of the alternative (date_difference_calculator) for non-person date spans, so usage is only implied.

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

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

No annotations are provided, so the description carries the full burden. It usefully discloses cost and payment rail ($0.01/call, USDC, eip155:8453) and, since there is no output schema, the WHO category and healthy-range return values. It says nothing about validation, unit errors, or edge cases (e.g., zero/negative height).

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 first sentence is well front-loaded and earns its place, but the second sentence is garbled filler that duplicates the purpose, and the pricing clause is tacked on mid-sentence rather than structured separately.

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 calculation tool with no output schema, the description covers inputs, returned values, and cost. Only the broken usage sentence and absent validation/error context keep it from being fully 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% and both parameters ('Height (cm)', 'Weight (kg)') are documented there. The description repeats the same unit semantics without adding format, range, or boundary detail, 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 verb and resource ('Calculate Body Mass Index') plus the inputs and derived outputs ('WHO weight category', 'healthy BMI weight range'). This is clearly distinguishable from siblings like calculators_age_calculator or calculators_compound_interest_calculator.

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 second sentence ('Use this when an agent needs to body Mass Index with WHO category') attempts a when-to-use clause but is a broken, garbled restatement of the purpose rather than real guidance. No alternatives, no exclusions, no preconditions are offered.

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 does disclose a non-obvious behavioral trait — the x402 payment requirement, price ($0.01/call), currency (USDC) and chain (eip155:8453) — which an agent must know before calling. However it says nothing about return format, rounding/precision, error cases, or idempotency.

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 price are front-loaded and useful, but the middle sentence ('Use this when an agent needs to future value with any compounding frequency') is redundant filler and is also grammatically broken. Roughly one of three sentences does not earn 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 simple 4-param calculator with 100% schema coverage and no output schema, the description covers inputs, the payment model, and gestures at the output ('total interest earned'). It still leaves the exact response shape (principal + interest breakdown vs. single total) unspecified, which an agent would need for downstream use.

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, but the description adds real meaning by decoding the enum: annual=1, semi-annual=2, quarterly=4, monthly=12, weekly=52, daily=365. The raw enum values are unlabeled strings '1','2','4','12','52','365', so this mapping is genuinely useful rather than duplicative.

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 ('Project the future value of a deposit with compound interest') plus the configurable dimension (compounding frequency) and the deliverable (total interest earned). It is clearly distinguishable from siblings like finance_cagr_calculator or crypto_apr_apy, though it never names or contrasts any sibling.

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

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

The only usage sentence is 'Use this when an agent needs to future value with any compounding frequency,' which largely restates the purpose rather than giving conditions, prerequisites, or alternatives (e.g. simple-interest vs. CAGR vs. loan-payment tools). Implied usage is there, but no when-not or routing 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 burden. It does add genuine behavioral context by disclosing a paid x402 endpoint at $0.01/call in USDC on eip155:8453, and it describes the three output formats. It omits what happens if end precedes start, timezone assumptions, and any error behavior.

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 first sentence is front-loaded and information-dense, but the second sentence is a redundant, ungrammatical restatement of the same idea and could be replaced with routing guidance. The pricing note is compact and useful.

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-annotation, no-output-schema tool, the description covers the return shape (total days, weeks+days, years+months+days) and the payment requirement, which is what an agent most needs. Remaining gaps are edge-case behavior rather than core calling information.

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 both parameters already carry "ISO format YYYY-MM-DD" descriptions, so the schema does the heavy lifting. The description adds no additional meaning about start/end semantics (ordering, inclusivity of endpoints).

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 (count days between two dates) and enumerates the three breakdown formats returned. It is clearly distinguishable from a plain age calculator or a business-days tool, but it never names which sibling to prefer for related needs.

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?

"Use this when an agent needs to days, weeks and calendar time between two dates" gives implied usage, but the sentence is grammatically broken and simply restates the purpose. No exclusions are offered, e.g. that business-day counting belongs to live_business_days or that durations belong to dev_iso_duration.

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

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

No annotations are provided, so the description carries the full burden. It does add two useful non-obvious facts: output includes the working, and each call costs $0.01 USDC on eip155:8453. It says nothing about rounding, currency assumptions, or error behavior for invalid inputs.

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 actual capability, which is good. The middle sentence is redundant with the first and grammatically broken, so it does not earn 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 pure-computation tool with full schema coverage and no output schema, the definition covers what it computes, what it returns, and even the call cost. Only edge-case behavior for malformed input is unaddressed.

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% (both parameters documented as 'Original price' and 'Discount %'), so the baseline is 3. The description's 'price and percent-off discount' phrasing confirms the percent basis but adds no unit, range, 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?

States a specific verb and resource: computes final sale price and savings from price and percent-off, plus 'with the working shown'. This is distinguishable from the sibling percentage_calculator and vat_calculator by the percent-off/sale-price framing, though the description never names those neighbors to make the boundary explicit.

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 second sentence, 'Use this when an agent needs to sale price and savings from a percent off,' is an ungrammatical restatement of the purpose rather than genuine guidance. There is no when-not, no prerequisite, and no named alternative for the closely related tip/percentage/VAT calculators.

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 behavioral burden. It usefully discloses the x402 call price of $0.01/call, but it does not explain the calculation output format or how the split is computed, and it calls cost splitting optional even though the schema requires a 'people' parameter.

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

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

The description is front-loaded and reasonably short, covering the calculation, the use case, and the call price. It contains minor awkwardness and a typo ('splitable'), plus some repetition between the calculation sentence and the 'Use this when...' sentence.

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 names the main outputs (liters and total cost) and covers the key inputs, which is adequate for a simple calculator with no output schema. However, it leaves ambiguity around the required 'people' parameter and the optional-splitting claim, so an agent lacks complete guidance for correct 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?

The schema already documents all four parameters at 100% coverage, including units for distance, consumption, and pricePerLiter. The description adds some meaning by mentioning passenger splitting, but it explicitly calls splitting optional while 'people' is a required parameter, which can lead an agent to omit a required input.

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: calculate fuel liters and total trip cost from distance, consumption, and price per liter. It clearly distinguishes this calculator from sibling calculators such as dev_llm_cost_calculator or crypto_gas_fee_calculator by naming the fuel-cost 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?

It gives an explicit use case: 'Use this when an agent needs to trip fuel and cost, splitable between people.' That is clear context, but it does not state when not to use it or name any competing alternative tool.

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 whole burden, and it delivers meaningful extras: the payment model (annuity formula), the full result set (monthly payment, total repaid, total interest) despite no output schema, and the commercial behavior (x402 price $0.01/call, USDC on eip155:8453). It still omits rounding/currency conventions and error behavior on invalid inputs, so it is not fully complete.

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 computation and outputs, then the usage clause, then the pricing note — an efficient ordering with no filler. It loses a point for the garbled clause "needs to monthly payment," which briefly obscures the intent.

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 stateless three-parameter calculator with no annotations and no output schema, the description supplies the formula, the three return values, and the payment model, which is enough to call it correctly. Minor gaps remain around rounding, currency, and when to prefer the amortization-schedule sibling.

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 three parameters are already documented as principal, annual rate %, and term in years. The description adds only the unit conventions (annual rate, term in years) already implied by 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 (compute a loan's fixed monthly payment) and names the exact inputs and derived outputs, plus the annuity formula used. It is clear and self-contained, but never distinguishes itself from nearby siblings like finance_amortization_schedule or calculators_compound_interest_calculator, which an agent may reasonably consider for the same request.

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?

"Use this when an agent needs to monthly payment, total cost and interest for any loan" merely restates the purpose rather than giving selection criteria. No alternative (amortization schedule, compound interest) is named, and no exclusions or edge conditions (e.g. zero-rate loans) are stated, so routing must be inferred.

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 it does disclose two non-obvious traits: output includes 'step-by-step working shown', and the call is metered ('x402 price $0.01/call (USDC, eip155:8453)'), which tells the agent a payment/auth path is involved. It does not state that the calculation is deterministic and side-effect free, but for a pure arithmetic utility the payment and output-format disclosures are the meaningful ones.

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 and compact: capabilities first, then the when-to-use clause, then pricing. It is only slightly over-stuffed — the 'Use this when' sentence repeats the operation list, and there is a grammatical slip ('needs to percent of a number') that adds no 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 three-parameter arithmetic tool with no output schema and no annotations, the description covers all three modes, the parameter roles, the fact that working is returned, and the pricing model. Precision/rounding behaviour of the returned numbers is the only notable omission.

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 nominally 100% but the schema's own descriptions are uninformative ('X', 'Y', 'Operation'). The description supplies the missing meaning by defining the role of X and Y under each mode (X% of Y, X as a percent of Y, change between two values), which is genuine semantic value beyond the enum labels.

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 concrete operations (X% of Y, what percent X is of Y, percent change) which map cleanly onto the three-valued 'op' enum, so an agent can immediately tell this apart from calculators_discount, calculators_vat or calculators_tip. It is specific but never explicitly contrasts itself with those neighbouring calculators, so it stops short of full sibling 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?

There is an explicit routing clause: 'Use this when an agent needs to percent of a number, ratios and percent change.' That gives a clear use context, though the phrasing is grammatically broken and largely restates the operations already listed, and no exclusions or named alternatives are offered.

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

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

No annotations exist, so the description carries the full burden, and it does add real value by disclosing the paid x402 call ($0.01 USDC, eip155:8453) and the 200 wpm default. However, it also claims the speed 'defaults to 200 words per minute' when the schema marks wpm as required — an agent following the description would omit wpm and fail validation, which is a materially misleading behavioral claim.

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 short and front-loads the core purpose and default speed, but the third sentence contains a grammatical error ('needs to how long a text takes') and the pricing note is appended without structure. Nothing is bloated, but the prose is loose rather than tight.

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-annotation, no-output-schema tool, the description covers inputs and a default but never states the return shape (minutes, seconds, formatted string). That is the main unresolved question an agent would have before calling.

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

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

Schema coverage is 100% and the schema itself explains the wpm scale (200 silent, 130 aloud), so the baseline would be 3. But the description's only parameter-related content — the 200 wpm 'default' — directly conflicts with wpm being a required parameter, which degrades rather than adds meaning.

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: estimate reading time from a word count, at a configurable reading speed. That is distinct enough from the other calculators (tip, VAT, BMI) that an agent won't confuse it, though it never acknowledges dev_readability, which overlaps most closely.

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 offers a use condition ('when an agent needs to know how long a text takes to read, by word count'), which is implied routing rather than explicit when/when-not guidance. No alternative is named and no exclusions are given, so the agent must infer that dev_readability is a different tool.

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

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

No annotations are provided, so the description must carry behavioral context. It discloses the default 15% tip and the x402 pricing, but omits rounding/precision behavior and whether the calculation is pure/deterministic.

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

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

Front-loads the core calculation and is appropriately sized. There is slight redundancy between the first sentence and the 'Use this when...' sentence, but no major 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?

No output schema exists, but the description sufficiently states the return values: tip amount, total, and per-person split. It could mention rounding or precision, but is otherwise complete for a simple calculator.

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 all three parameters (bill, tipPercent, people) are already documented. The description does not add syntax or format details beyond the schema, making baseline 3 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?

States a specific verb and resource: calculate tip, grand total, and per-person split for a bill. The purpose is unambiguous and clearly distinguishable from sibling calculators like discount or VAT.

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 a clear context: 'Use this when an agent needs to tip amount, total and per-person split.' It does not name when-not-to-use or direct alternatives, but the use case is well defined.

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, so the description carries the full burden. It usefully discloses built-in standard rates, custom-rate override, and even the x402 price/currency/chain (USDC, eip155:8453). It says nothing about error behavior for unsupported countries, rounding rules, or precedence when both country and rate are supplied.

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 behavior and the pricing note is worth its place, but the third sentence duplicates the first almost verbatim, wasting ~25% of the text.

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

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

For a four-parameter, no-output-schema calculator the description covers what the tool computes, the two operating modes, the rate-override rule, and the cost of a call. Only the precedence between country and rate, and failure handling, remain unstated.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds one useful semantic hint — that rate overrides the built-in country rate — but leaves the required-list/schema mismatch unaddressed (rate is listed as required yet described as optional).

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?

Names a specific operation pair (add VAT to net / remove VAT from gross) plus the resource scope (built-in rates for 36 countries, custom override). An agent can immediately distinguish this from the sibling geo_time_eu_vat_validate, which validates rather than computes.

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?

'Use this when an agent needs to add or remove VAT at standard rates for 36 countries' restates the first sentence rather than giving a use/avoid condition. No alternative tool or edge condition (e.g. non-standard VAT regimes, EU VAT validation) is named.

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

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

No annotations exist, so the description carries the full behavioral burden. It does add genuinely useful non-schema context: the tool is paid via x402 at $0.01/call in USDC on eip155:8453, so an agent knows to expect a payment step. It says nothing about conversion precision, rounding, case sensitivity of units, or error behavior, so meaningful gaps remain.

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?

Short and front-loaded with the core purpose, but one of three sentences is garbled to the point of being unparseable ('needs to square meters, feet, acres, hectares'), and the pricing sentence, while useful, reads as bolted on. Waste is low but polish is poor.

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 3-parameter pure conversion tool with full enum coverage, the description covers what it does, which units are supported, and the payment cost. The only meaningful omission is that with no output schema present it never states the shape of the returned converted value, though that is easily inferred.

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

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

With 100% schema description coverage and enums on both 'from' and 'to', the schema already does the heavy lifting, so baseline 3 applies. The description's spelled-out unit names loosely map to the enum values but don't add syntax guidance, and the mismatch (mm2 listed, absent from enum) slightly weakens the mapping.

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 ('Convert') and resource ('area units') and enumerates the unit families, which cleanly separates it from sibling converters like converters_length_converter or converters_volume_converter. The list is slightly out of sync with the schema enum (square millimeters and square miles are named but the enum has no mm2 entry), which keeps it 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 second sentence attempts a usage cue ('Use this when an agent needs to square meters, feet, acres, hectares') but is grammatically broken and names no alternative tool or condition for choosing among the other converter siblings. Usage is implied rather than stated, which is the textbook 3.

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

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

No annotations are provided, so the description carries the full burden. It does disclose a genuinely useful behavioral trait beyond the schema — the x402 payment requirement and price ($0.01/call USDC, eip155:8453) — but says nothing about side effects, precision/rounding of results, or what the caller should expect alongside the converted value.

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?

Reasonably short and the unit scope is front-loaded, but the second sentence is a malformed clause ('needs to decimal ... and binary ... units') that costs the reader more than it saves. The pricing token is useful; the broken guidance sentence is not.

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 three-parameter pure converter with no annotations and no output schema, the essentials are mostly covered: units, conversion bases, and cost. Missing is any indication of the return shape or precision, which matters when no output schema exists to answer it — 'both systems side by side' hints at this but does not pin it down.

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 schema descriptions are placeholders ('From', 'To', 'Value'), so the description is doing real work by explaining that KB/MB/GB are ×1000 decimal and KiB/MiB/GiB are ×1024 binary, which tells the agent how to pick between the two enum families. It loses a point for claiming 'bits' support that the enum does not contain.

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 (Convert) and resource (digital storage units) and enumerates exactly which units are supported, splitting decimal (KB/MB/GB) from binary (KiB/MiB/GiB) — enough to separate it from siblings like dev_number_base_converter or converters_length_converter. Minor flaw: it advertises 'bits', which is not in the schema enum, so the stated scope is slightly wider than reality.

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 second sentence attempts guidance ('Use this when an agent needs to decimal (KB/MB/GB) and binary (KiB/MiB/GiB) units') but is grammatically broken and reads as a truncated sentence, so the triggering condition is only implied. No alternatives or exclusions are named, though the unit-family list does implicitly scope the tool to storage units.

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. It usefully discloses the x402 payment requirement ($0.01/call, USDC, eip155:8453), which is real context an agent needs, but says nothing about rounding/precision, invalid-unit handling, or error behavior.

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 capability and unit list, then the usage cue. No padding, though the trailing payment clause is boilerplate rather than substantive.

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 and no annotations, so the description should say more about the result (unit of returned value, precision). For a simple stateless conversion it is adequate, but return-format expectations are left to inference.

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 parameter descriptions are placeholders ('To', 'From', 'Value'), so the description's expansion of enum abbreviations into full unit names (km=kilometers, um=micrometers, nmi=nautical miles) is the main source of meaning. It adds modest value beyond the abbreviations.

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 (convert length units) and enumerates the full unit set, which cleanly separates it from sibling converters (area, weight, temperature, speed). An agent can identify it immediately.

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 gives a when-to-use cue ('when an agent needs to metric and imperial distance units, instantly'), though the sentence is grammatically broken and vague. It never names alternatives or exclusions, so routing among the many sibling converters is only implied by the unit list.

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 does add real behavioral context by disclosing input validation behavior (rejects non-standard forms like IIIM or VX), the accepted range, and the paid-call cost (x402 $0.01 USDC on eip155:8453). However, it says nothing about what an invalid input returns or what the response payload looks like, leaving the error/response profile opaque.

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 validation detail are correctly front-loaded, but the middle sentence is redundant, ungrammatical, and repeats the same content, and the pricing sentence sits awkwardly at the end. Two of three sentences partly duplicate each other.

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 carry the whole contract; it covers operation, range, validation, and cost but never indicates the return shape (e.g., a string result) or error behavior for out-of-range input. Adequate for a simple two-parameter converter, but not complete.

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

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

Schema coverage is 100%, so baseline is 3, but the description adds a constraint the schema lacks: the numeric value must fall in 1–3999, and validation rejects non-canonical numerals. That meaningfully sharpens how the 'value' parameter may be populated for both op directions.

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 bidirectional verb+resource ('Convert numbers to Roman numerals ... and Roman numerals back to numbers'), bounds the input domain (1–3999), and specifies validation strictness with concrete rejected examples (IIIM, VX). Nothing in the sibling list overlaps with Roman numeral conversion, so an agent can select it unambiguously.

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 only guidance sentence, 'Use this when an agent needs to numbers ↔ Roman numerals, with validation,' is grammatically broken and essentially restates the purpose rather than adding selection criteria. No alternatives are named and no when-not conditions are given.

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

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

No annotations exist, so the description carries the full burden. It does disclose a genuinely useful behavioral trait the schema cannot express: a payable x402 cost of $0.01/call in USDC on eip155:8453. However, it says nothing about output format, precision/rounding behavior despite claiming "exact definitions", or how errors (e.g. unsupported combinations) are handled.

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 units are correctly front-loaded, and the pricing disclosure is compact. But the middle sentence is garbled filler that consumes space without information, weakening an otherwise terse definition.

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 three-parameter, enum-driven converter with no output schema, the definition covers units, enum expansions, and the payment requirement — enough for an agent to invoke it correctly. The only real omission is stating the expected numeric unit/format of the return value and rounding 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 coverage is nominally 100% but the schema descriptions are placeholders ("To", "From", "Value"), so the real semantics live elsewhere. The description usefully expands the cryptic enum values (kmh=kilo meters per hour, kn=knots, fts=feet per second), which an agent otherwise has to guess. It does not clarify the numeric units of "value" (implied to be in the `from` unit).

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 ("Convert speed units") and enumerates the exact unit set, which distinguishes it from sibling converters like length, temperature, and volume. The malformed follow-up sentence ("Use this when an agent needs to km/h, mph, m/s, knots and ft/s") adds noise but does not obscure the core purpose.

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 "Use this when..." clause is grammatically broken and merely restates the unit list rather than describing a scenario, trigger, or alternative. No guidance on when to prefer this over sibling converters, and no prerequisites or exclusions are given.

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

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

With no annotations, the description adds useful behavioral context: exact formulas, reference points, step-by-step working, and a per-call x402 price. It still does not describe return shape, rounding behavior, validation errors, or other operational details.

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

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

The description is short and front-loads the core conversion purpose. The second sentence is awkwardly worded, but the overall structure is efficient and does not waste space.

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 three-parameter converter with no output schema, the description covers purpose, output flavor (formulas and steps), and payment terms. It is largely complete, though it could specify the return value more explicitly.

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

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

Schema coverage is 100%, so the from/to enums and value parameter are already documented in the schema. The description adds that conversions work both ways and mentions the units, but does not supply parameter syntax or constraints 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 names the resource and operation: converting among Celsius, Fahrenheit and Kelvin. It is distinguishable from sibling converters by temperature domain, though it does not explicitly contrast with 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?

It provides an implied usage condition: 'Use this when an agent needs to celsius, Fahrenheit and Kelvin, both ways.' However, the sentence is malformed and gives no when-not guidance or alternative tools to use.

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

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

With no annotations, the description carries the full burden and does real work: automatic millisecond detection, rejection of invalid dates with clear errors, and the x402 payment requirement ($0.01/call USDC on eip155:8453) an agent must know before invoking. It omits return-format specifics and range/edge-case behavior (e.g. pre-1970 negatives), 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?

Four short sentences with the core conversion purpose front-loaded and no filler. The pricing sentence is distinct in purpose but earns its place as invocation-critical information; the overall text is appropriately sized for a two-parameter utility.

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 annotations and no output schema, so the description must stand alone for a stateless converter — and it does, covering input directions, output domain (ISO/UTC), auto-detection, error behavior, and payment. Only explicitly-noted return shape and unusual-input handling 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% and the enum on op is self-explanatory, so the baseline is 3. The mention of both directions loosely maps to the op enum values, but the description adds no format or syntax detail (accepted date strings, seconds-vs-milliseconds input convention) beyond what the schema already conveys.

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 (Convert) plus both resources (Unix epoch timestamps and ISO/UTC dates) and the bidirectional scope. Among the converters_* siblings this is the only epoch/time conversion tool, and the description makes that domain unambiguous without the agent needing to open the schema.

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?

"Use this when an agent needs to epoch seconds ↔ human dates, both directions" gives a clear selection context, which is helpful against neighbors like dev_natural_date or live_timezone_convert. It stops short of naming an alternative or stating when-not to use it, so it is strong context without explicit exclusions.

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

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

With no annotations, the description must carry behavioral weight, and it does disclose the x402 payment model ($0.01/call, USDC on eip155:8453), which is real context the schema cannot provide. However, it says nothing about rounding/precision, accepted unit casing, or error behavior for invalid units — meaningful gaps for an unannotated 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 unit list is front-loaded and efficient, but the second sentence is grammatically broken and appears to be damaged boilerplate that consumes space without conveying information. The pricing sentence is useful but tacked on.

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 3-parameter arithmetic tool with no output schema, the description covers the domain surface and payment model adequately, but an agent still cannot predict precision, rounding conventions, or which conversion standard (US vs imperial) applies to units like 'gal' and 'pt' — a real ambiguity given the tool also lists liters.

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, but the description adds genuine value by decoding the enum abbreviations into full names (m3=cubic meters, gal=US gallons, qt=quarts, pt=pints, floz=fluid ounces, tbsp=teaspoons vs tsp), which the terse schema descriptions ('To', 'From', 'Value') do not. It still doesn't explain that value is numeric or how to handle ambiguous units like 'cup'.

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 (Convert) and resource (cooking and liquid volume units) and enumerates the exact unit families covered, which distinguishes it from converters_weight_converter, converters_temperature_converter and converters_area_converter at a glance. It stops short of explicitly naming those siblings as boundaries, so it lands at 4 rather than 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 only usage sentence is broken: 'Use this when an agent needs to liters, gallons, cups, milliliters.' — it lacks a verb and adds no actionable condition. There is no guidance on when to prefer this over the other converters, and no exclusions or prerequisites beyond the price 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?

No annotations are provided, so the description carries the burden. It usefully discloses a per-call x402 price ($0.01 USDC on eip155:8453) and claims 'exact international definitions', but says nothing about output precision, rounding, or return format for a numeric conversion.

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 first sentence is well-formed and front-loaded, but the second is an incomplete/broken sentence ('needs to kilograms, pounds, ounces and more') that wastes space, and the pricing sentence is appended awkwardly. There is real editorial 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 simple three-parameter converter with full enum coverage and no output schema, the description covers scope, units, and cost adequately. It is nearly complete, lacking only output/precision notes that a caller of a numeric converter might want.

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 both from/to enums are fully documented, so the schema already does the heavy lifting. The description merely restates the unit list and adds no syntax or semantics beyond what the enum already provides; 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?

States a specific verb+resource ('Convert between weight and mass units') and enumerates the exact unit set (t, kg, g, mg, lb, oz, st), which cleanly separates it from the length, volume, and temperature converter siblings. An agent can pick this tool without opening the schema.

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 only usage sentence is garbled and incomplete ('Use this when an agent needs to kilograms, pounds, ounces and more'), which conveys no real when-to-use condition and no alternatives. There is no guidance on when another converter (e.g. length or volume) would be the right pick.

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 the error policy ('never guesses — an invalid checksum is an error, not a silent fix'), what gets returned (the canonical checksummed form), and flags broken-checksum input. It even surfaces the x402 cost ($0.01/call, USDC on eip155:8453). Only the mutability/side-effect profile is left implicit (though validation is inherently 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?

Front-loads the core action well, but the fourth sentence is a tautological restatement of sentence one ('eIP-55 checksum check + canonical form') and the pricing sentence is meta rather than behavioral. Roughly one of the four sentences does not earn 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 one-parameter validation tool with no output schema and no annotations, the description covers what it does, how it fails, and what it returns, which is close to sufficient. Minor gaps remain around exact output shape, but the return behavior is adequately described.

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

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

Schema coverage is 100% with a single required 'address' parameter, so the schema is the primary source. The description adds only domain framing ('EVM address') and no syntax/format detail beyond what the schema already conveys; 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?

States a specific verb (validate) and resource (EVM address) and specifies the exact mechanism: syntactic checks plus the EIP-55 keccak-256 checksum test. An agent can distinguish this from siblings like crypto_ens_resolve (name resolution) without opening either schema.

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 only guidance sentence, 'Use this when an agent needs to eIP-55 checksum check + canonical form,' simply restates the first sentence. It names no alternatives, no exclusions, and no conditions that would steer an agent away from a sibling tool.

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. It usefully discloses that the math is deterministic closed-form with no approximations and states the x402 price ($0.01/call, USDC on eip155:8453), but it never describes the return value (an APY %) or handling of edge cases like rate=0 or negative rates.

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 conversion, then determinism and pricing. The "Use this when an agent needs to nominal rate → effective yield" sentence largely restates the opening and is slightly garbled, costing a little efficiency but not much.

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, fully-schema-documented pure-math tool with no output schema, the description covers purpose, determinism, and cost. It leaves the output form (APY %) and the title's implied bidirectional '↔' conversion unexplained, 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%, so the schema already documents ratePct (APR %) and the compounding enum. The description's mention of "any compounding frequency including continuous" marginally reinforces the enum but adds no syntax or format 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 verb (Convert) and resource (APR to APY) with scope (any compounding frequency including continuous), and it clearly distinguishes itself from generic siblings like calculators_compound_interest_calculator by framing the DeFi yield-decisions use case.

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?

"Use this when an agent needs to nominal rate → effective yield, any compounding" gives clear triggering context. However it names no alternatives or exclusions, so the agent is not told why to pick this over compound_interest_calculator or crypto_yield_pools.

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 traits: the data source (viem over public Ethereum mainnet RPCs), the L1-scoping caveat, and a pay-per-call model ($0.02/call USDC on eip155:8453). It stops short of covering failure behavior (unresolved names), rate limits, or confirmation/latency characteristics.

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

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

Three sentences, front-loaded with purpose before the operational caveat and pricing. The 'ENS name ↔ address, bidirectional' clause partially restates the opening sentence, and the stray lowercase 'eNS' is sloppy, but overall it is tight and every sentence 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 2-parameter tool with no output schema, the description covers what it produces (addresses or ENS names), the network/source, the payment model, and the L1 caveat. Nothing critical is missing for correct invocation, though error/edge behavior is left implicit.

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

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

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning the schema lacks: it maps the two enum values to their directions ('resolve' = name → address, 'lookup' = address → ENS name), which the schema only labels as 'Operation'. This resolves ambiguity about what each op accepts for the loosely-named 'value' parameter.

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 (resolve ENS names to addresses), names the reverse direction explicitly (address → ENS name), and specifies the mechanism/network (viem against Ethereum mainnet). This is clearly distinguishable from neighboring crypto tools like crypto_address_validate or crypto_tx_explain.

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

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

The sentence 'Use this when an agent needs to ENS name ↔ address, bidirectional on Ethereum mainnet' gives a clear usage context plus the network scope, and the note that ENS data lives on L1 regardless of wallet's active chain is a useful usage signal. However, it names no alternative tool or when-not-to-use condition.

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 usefully discloses the calculation method, exact BigInt wei math, and x402 payment cost. It still omits response shape/detail and input validation behavior, keeping 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 definition is front-loaded with the core calculation, then adds exactness, usage, and pricing in compact form; no sentence is wasted. Minor grammar aside, it is appropriately sized.

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 calculator with no annotations or output schema, the description supplies the formula, units, exact-math note, and payment context. It could specify returned fields more explicitly but is nearly complete for 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 coverage is 100%, so baseline is 3, but the description adds the relationship among gasUnits, gweiPrice, and ethPriceUsd via the formula and output units. It does not add ranges or edge-case 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 ('Calculate a transaction's gas fee') and gives the exact formula, so the purpose is unambiguous. It does not explicitly name sibling alternatives such as crypto_gas_price or crypto_wei_eth_converter, so it falls short of the top score for sibling 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?

The sentence 'Use this when an agent needs to transaction cost in ETH and USD from gas × gwei' gives a clear triggering condition. It offers no when-not guidance or named alternatives, so not a 5.

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

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

With no annotations, the description carries full burden and does disclose meaningful operational traits: no API key required, live on-chain sourcing, and a paid x402 endpoint at $0.02/call (USDC, eip155:8453). It omits rate limits, freshness/caching, and error behavior, but auth and cost — the traits most likely to break an invocation — are covered.

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

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

Front-loaded with the core capability and output format, then supporting details (no key, usage cue, price). Efficient overall, but the sentence "Use this when an agent needs to current gas price" contains a grammatical error that slightly hurts readability.

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

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

For a 2-parameter, no-output-schema tool, the description is nearly self-sufficient: it explains the source, the derived outputs (gwei and USD), the required user-supplied ETH price, and the payment model. Only failure modes and freshness are unaddressed.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds modest value by clarifying that ethPriceUsd is a caller-supplied value ("using your own ETH price input") rather than a fetched one, and by confirming the chain enum scope, but it adds no format or constraint details 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 and resource ("Fetch the live gas price") plus the data source (public RPC nodes) and the two supported chains, and even describes the output shape (wei→gwei with USD estimate for a 21,000-gas transfer). It does not, however, distinguish itself from close siblings like crypto_gas_fee_calculator or crypto_wei_eth_converter, which an agent might reasonably 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?

"Use this when an agent needs... gas price in gwei and USD, straight from the chain" gives clear when-to-use context. There is no when-not guidance and no explicit routing to the gas-fee or wei-converter siblings, so alternatives are left 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 traits beyond the schema: deterministic closed-form computation, a reference-table output, and pricing (x402 $0.01/call in USDC on eip155:8453). Since it is a pure computation there are no side effects to warn about; only the shape of the returned reference table is left unstated.

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?

Efficiently front-loaded: what it computes, then accuracy/use context, then agent guidance and price. Slightly penalized for the garbled 'needs to aMM divergence loss' clause, which costs a reader a pass to parse.

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

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

For a one-parameter calculator with no output schema, the description is nearly sufficient: it names the formula class, the assumption (50/50 constant product), and the reference-table return. It could state the output fields explicitly, but nothing required to invoke 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 coverage is 100% for the single parameter, including the 100 = 2x / -50 = half convention, so the baseline is 3. The description's phrase 'at any relative price move' echoes rather than extends the schema, adding no extra format or range 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?

States a specific verb (compute) and resource (impermanent loss) scoped to a 50/50 constant-product AMM at any relative price move, which no sibling calculator covers. An agent can distinguish it from nearby tools like crypto_apr_apy or crypto_yield_pools without opening a schema.

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 line 'Use this when an agent needs to aMM divergence loss for any price move' restates the purpose rather than giving decision criteria, and it is grammatically broken. There is a real use-case hint ('the exact divergence number an LP should compare against farming rewards') but no explicit when-not or named alternative, so 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 full burden and does disclose meaningful traits: the GeckoTerminal data source, the automatic risk flags, and that the call is metered (x402 $0.02/call USDC on eip155:8453). It omits rate limits, payment flow mechanics, and error/empty-result behavior, so it is good 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?

Purpose is front-loaded, followed by return contents, data source, usage, and price — a logical order with no filler sentences. Marked down slightly because the usage sentence is grammatically broken ('needs to fresh DEX launches') and partly restates the opening scope.

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 paid multi-chain scan tool with no annotations and no output schema, the description carries most of what an agent needs: what is returned, where the data comes from, and the cost. It does not explain pagination against the 'limit' param or what happens when no pools meet the filters.

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 all four parameters (network enum, minLiquidityUsd, maxAgeHours, limit) are already documented in the schema. The description only restates the liquidity/age filtering concept and the network list, adding no syntax, units, or defaults beyond what the schema provides — 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?

States a specific verb+resource ('Scan newly created DEX pools') across named chains, and scopes it with liquidity/age filters. The 'newly created pool' framing implicitly separates it from crypto_yield_pools, but no sibling is ever named, so the differentiation is left 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?

Explicitly says 'Use this when an agent needs to [scan] fresh DEX launches with liquidity, volume and risk flags,' giving clear usage context. However, it names no alternative or exclusion (e.g. how it differs from crypto_yield_pools or crypto_price), so the routing guidance stops short of a 5.

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

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

With no annotations, the description carries the full burden and does well: it discloses a 60-second cache, the underlying provider (CoinGecko), and an x402 paid-access cost of $0.02/call (USDC on eip155:8453). It omits failure behavior and whether tickers are resolved client- or server-side, but the freshness and payment characteristics are valuable 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?

Front-loads the core function and stays compact, but the 'Use this when an agent needs...' sentence is redundant with the opening sentence and could be merged with it. The x402 pricing sentence earns its place as actionable cost 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 2-param read tool with no output schema and no annotations, the description covers source, accepted inputs, returned fields, cache freshness, and cost. Only the exact response shape (e.g., object structure) is left unstated, which is a minor gap given there is no output schema.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema's terse 'Coin ids or tickers' by giving concrete ticker examples (btc, eth, sol…) and clarifying that both ids and tickers are accepted, which reduces ambiguity about the ids parameter.

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 (live cryptocurrency prices), the data source (CoinGecko's public API), the exact outputs (current price in USD/EUR/GBP/JPY plus 24-hour change), and accepted input forms (coin id or common ticker). This makes it immediately distinguishable from sibling tools like crypto_gas_price or crypto_stablecoin_metrics, which cover different crypto data.

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

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

It provides a 'Use this when an agent needs live token prices and 24h change' sentence, but that largely restates the purpose already stated. No alternatives are named (e.g., live_exchange_rates for fiat) and no exclusions are given, so guidance is only implied rather than routing.

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 it does add real behavior: rejection sampling with no modulo bias, plus an operational cost disclosure ($0.01/call, USDC on eip155:8453). However it says nothing about the shape of the returned value per mode, error behavior, or how the seven required parameters interact across modes. Adequate but incomplete 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?

Front-loaded with the capability and three modes in one dense sentence, then the anti-Math.random warning. The third sentence largely restates the first ('Use this when an agent needs to cSPRNG passwords, hex keys and uniform integers'), which is mild redundancy, and the price tag feels appended rather than integrated.

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 is the only place an agent can learn what comes back, and it never describes the return value. It also does not explain that all seven parameters are required regardless of mode (e.g. min/max must presumably still be passed in password mode), which is the main practical trap for a caller.

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

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

Schema coverage is 100% so the baseline is 3, but the description genuinely adds meaning: 'charset rules' glosses the upper/digits/symbols flags, 'hex keys of any byte length' clarifies that length means bytes in hex mode, and the rejection-sampling note characterizes how min/max are honored for int mode. That is a useful lift over the terse schema strings.

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 ('Generate') and resource ('cryptographically secure randomness') and then enumerates the three output families (passwords, hex keys, uniform integers). An agent can distinguish this from siblings like security_password_strength (which measures an existing password) or dev_uuid without opening the schema.

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?

'Use this when an agent needs to cSPRNG passwords, hex keys and uniform integers' is an implied-usage restatement of the purpose sentence rather than routing guidance. There is no when-not clause and no named alternative (e.g. security_password_strength for judging a password the agent already has), so the agent must infer boundaries itself.

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. It does add real value by disclosing the data source, liveness, and an x402 payment requirement ($0.02/call in USDC on eip155:8453). It does not say what happens for a non-stablecoin or unknown symbol, whether results are cached, or what error/empty behavior looks like.

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 payload contents, followed by usage and pricing. Slightly redundant: "due-diligence read before an agent touches a stablecoin" and the following sentence both cover when to use it, but the text stays tight and every remaining sentence adds 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?

With no output schema and no annotations, the description compensates reasonably by listing the returned fields (peg price, depeg distance, supply, backing, chain breakdown) and the payment model. Gaps remain around unsupported symbols and response shape, but an agent has enough to call 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?

Only one parameter (symbol) with 100% schema description coverage and in-schema examples (USDC, USDT, DAI, USDS). The description implies the tool accepts "any stablecoin" but adds no syntax, format, or case-sensitivity detail beyond what the schema already 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 resource (live stablecoin health) and enumerates the exact payload: peg price, depeg distance, circulating supply, backing type, and chain breakdown, plus the data source (DefiLlama). It is clearly distinguishable from the generic sibling crypto_price by scoping to stablecoins and peg-centric metrics.

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

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

"The due-diligence read before an agent touches a stablecoin" and "Use this when an agent needs to peg, supply and chains" give a clear usage context. However, it never names the alternatives (e.g. crypto_price for general token prices, crypto_yield_pools for lending/supply yields), so routing between siblings is left 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 behavioral burden and does reasonably well: it discloses the access mechanism (public RPC eth_call, no key, no indexer), the return shape (raw balance, decimals-applied amount, symbol), and the cost model (x402 $0.02/call, USDC, eip155:8453). It omits rate limits and error behavior, but adds genuine context beyond the schema.

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

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

Purpose is front-loaded, but the third sentence is redundant with the first and grammatically broken ('needs to any token balance'), so it does not fully earn its place. The pricing note at the end is useful but tacked on.

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, so the description compensates by describing the returned fields (raw balance, human-readable amount, symbol), which is the key missing piece an agent needs. All required params are covered by the schema, leaving only minor gaps like polling/rate-limit 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 all three parameters are already documented. The description restates the chain options and the notion of a token/holder but adds no syntax or format guidance (e.g. address format, checksum expectations) 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 (read) and resource (ERC-20 token balance) with explicit scope (any wallet on Base or Ethereum). This distinguishes it from nearby siblings like crypto_wallet_snapshot or crypto_price without needing to open the schema.

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 line 'Use this when an agent needs to any token balance for any wallet, via public RPC' is largely a restatement of the purpose (and is grammatically broken). The 'no key, no indexer' phrase hints at the suitable context, but no alternatives or when-not conditions are named.

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 explicitly says nothing is sent (read-only, non-destructive), states that simulation runs against live chain state, and discloses that unlimited-approval warnings appear in the result. It also discloses the x402 price. It does not cover failure modes (reverts, unsupported chains) or latency.

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 is front-loaded in the first clause, followed by usage guidance and price. Each sentence earns its place; only the pricing detail is slightly tacked on.

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 convey the return value. It does so (decoded calldata, simulated outcome, approval warnings). For a four-param read-only tool this is close to complete, with only revert and error handling unaddressed.

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 four parameters are already documented, if terse. The description adds context about what data means (calldata, known ABIs) but not per-parameter semantics such as units, zero-value handling, or chain-specific behavior. 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 specific verbs and a resource: decode calldata and simulate an EVM transaction against live chain state. It also names the techniques (known ABIs, 4byte directory) and the output (outcome plus unlimited-approval warnings), which separates it from siblings like crypto_gas_price or crypto_address_validate.

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

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

It states a clear usage context: "Use this when an agent needs to decode and simulate a transaction — before signing it." No sibling alternative is named, and no explicit exclusions are given, but no other sibling performs simulation, so the routing ambiguity is low.

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 add real context: the data source (Blockscout), the supported chains (Ethereum, Base), the special flags returned, and the x402 cost of $0.02/call with the USDC/eip155:8453 payment rail. It does not state it is read-only or describe failure/rate-limit behavior, so it stops short of full disclosure.

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?

Content is front-loaded with the return payload first, then the positioning statement, then pricing. It is appropriately sized, though the phrase 'on-chain wallet profile' recurs and the final pricing sentence is somewhat tacked on rather than integrated.

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 compensates by enumerating the returned data fields, and it covers the chains, data source, and cost. What is missing is any note on return-time behavior, pagination of the top-holdings list, or error handling, so it is strong but not fully complete.

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

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

Schema coverage is 100% and both parameters (address, chain) are already documented with a chain enum, so the schema does the heavy lifting. The description loosely reinforces this by naming 'Ethereum or Base wallet,' but adds no syntax or format detail beyond what the schema provides, making the baseline 3 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 names a specific resource and enumerates exactly what it returns: native balance, transaction and transfer counts, activity recency, token holdings, counterparties, plus fresh-wallet/high-volume flags. It also explicitly distinguishes itself from raw RPC data and from the token-balance sibling, letting an agent tell it apart from crypto_token_balance without opening a schema.

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 trigger condition clearly: use when an agent needs an on-chain wallet profile (balance, activity, tokens, counterparties). However, it gives no explicit when-not guidance or names the token-balance/validate siblings as alternatives, so the routing is inferred 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.

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

With no annotations, the description carries the full burden and does meaningfully better than nothing: it discloses the exact BigInt arithmetic guarantee, float-free conversion for decimal strings of any magnitude, and the payment model (x402 $0.01/call USDC on eip155:8453). It does not describe return format or handling of malformed/negative inputs, which keeps it out of 5 territory.

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 exactness point is asserted three times ('exact BigInt arithmetic', 'without floating-point error', 'no float errors'), which is redundant. The pricing sentence is useful but tacked on, and the phrasing 'to exact Ethereum unit conversion' is garbled.

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?

Purpose and inputs are adequately covered and the lack of an output schema means the description could have explained the return shape but does not. For a simple 3-param converter it is viable, but return format and error behavior are unaddressed.

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

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

Schema coverage is 100%, so the baseline is 3; the schema already enumerates the units. The description adds little beyond restating them, and its unit labels ('microether', 'milliether') diverge from the schema enum ('microeth', 'millieth'), which could mildly confuse mapping.

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 ("Convert between") plus the exact resource domain (wei/kwei/mwei/gwei/microether/milliether/ether), which cleanly distinguishes it from the many generic converters (area, length, data size) and crypto calculators in the sibling list. An agent can identify this as the Ethereum unit-conversion tool without opening the schema.

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 a clear use condition — 'Use this when an agent needs to exact Ethereum unit conversion — no float errors' — which tells the agent when this tool beats a generic number/unit converter. It stops short of naming an alternative or stating exclusions, so it is clear context but not full when/when-not routing.

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 it delivers more than the minimum: names the data source (DefiLlama), discloses a non-obvious filtering behavior (sane-APY cap that drops runaway incentive numbers), and states per-call cost ($0.02 USDC on eip155:8453). It omits rate limits, freshness/latency of the live data, and whether results are cached.

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 core action and resource, then returns, then usage. The returns clause and usage clause overlap somewhat on filtering terms, costing a little tightness, but nothing is 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?

No output schema exists, but the description enumerates the return fields (project, pair, chain, APY, TVL), so an agent knows the shape of the result. Combined with the disclosed source and cost, a caller has enough to invoke it correctly, though freshness and pagination behavior for the 'top N' list are unstated.

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 all four params are self-described, so the schema does the heavy lifting. The description echoes the same filters (chain, stablecoin-only, min TVL, top-N) without adding units, format, or default semantics beyond what the schema already provides.

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

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

States a specific verb (returns/discovery) and resource (lending/liquidity pool yields from DefiLlama) and names the sibling relationship explicitly — 'the discovery step before reward-rate math' distinguishes it from crypto_apr_apy. An agent can tell it apart from crypto_new_pools and crypto_stablecoin_metrics without opening any schema.

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 a clear when-to-use ('Use this when an agent needs to top APY pools filtered by chain, TVL and stability') and routes to the reward-rate math step as the downstream alternative. No explicit when-not guidance or prerequisites beyond the implied read context.

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

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

With no annotations, the description carries the full burden. It usefully discloses coverage ('all 404 NANP codes in use, including overlays') and pricing ('x402 price $0.01/call (USDC, eip155:8453)'), which is real behavioral context. However, it says nothing about auth requirements, rate limits, error behavior, or what the dual-mode response looks like.

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 first two sentences are tight and front-loaded. The third sentence is syntactically broken ('needs to all 404 NANP area codes → state lookup') and repeats coverage already stated, and the trailing price string is grafted on awkwardly.

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 three-parameter lookup with no annotations and no output schema, the description covers coverage scope, the two modes, and cost. It stops short of describing return shape (state name? list of codes?) or how to disambiguate when both code and state are supplied, leaving gaps an agent would hit at call time.

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's dual-mode framing ('look up ... or list every area code in a given state') corroborates the code/state parameters, but it adds no syntax or format detail beyond the schema and does not address why all three parameters are marked required when the modes appear mutually exclusive.

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: 'look up any US telephone area code to find the state or territory it serves, or list every area code in a given state.' That is clear and distinguishable from calculator/converter siblings. It doesn't explicitly name a sibling to differentiate against, 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 only guidance is the garbled fragment 'Use this when an agent needs to all 404 NANP area codes → state lookup,' which restates the purpose rather than telling the agent when to pick this tool over alternatives. No when-not conditions, no prerequisites, no alternative tools referenced.

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 does disclose a genuine behavioral trait beyond the schema: the x402 pay-per-call cost ($0.01/call, USDC on eip155:8453), which signals a paid endpoint. However, it says nothing about read-only semantics, rate limits, or how the payment/auth flow works, so coverage is partial.

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 field list is stated twice — once cleanly in sentence one and again in the corrupted sentence 'Use this when an agent needs to 250 countries: codes, capitals, currencies, populations' — which is both redundant and syntactically broken, reading like an unfilled template. Good content is front-loaded, but the duplication and malformed sentence waste space and risk confusing the agent.

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's enumeration of returned fields (ISO codes, capitals, regions, population, area, currencies, languages, TLDs, calling codes) is doing real work and is appropriately thorough. Pricing is disclosed and both query modes are mentioned; only the missing payment-flow detail and the garbled usage sentence keep it from being fully 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%, so the schema already documents country, region, and limit, and the enum values for region are fully specified. The description adds only the single-vs-list distinction, which loosely maps to the country and region parameters, so it meets the baseline without exceeding 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?

The opening sentence gives a specific verb+resource ('Reference database of all 250 countries and territories') and enumerates the fields available, so an agent immediately knows what the tool returns. It does not, however, differentiate itself from the one relevant sibling (databases_area_codes), and the purpose statement is undercut by a broken sentence later in the description.

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?

'Look up a single country or list by region' implies the two operating modes, which is useful context. But the explicit 'Use this when...' sentence is garbled ('when an agent needs to 250 countries: codes, capitals...'), and no alternative tool or exclusion is named, so the routing guidance is only partially usable.

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 load and does well: it discloses the repeated-probe behavior, the metric set returned, that it targets GET endpoints, and the $0.02/call USDC price on eip155:8453. It omits failure/timeout behavior and rate limits, but the safety-relevant cost and method are covered.

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

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

The purpose sentence is front-loaded and tight, but the third sentence ('Use this when an agent needs to status and latency stats — test an API before relying on it') is grammatically broken and largely restates the second. The pricing clause is useful but tacked on.

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 and no annotations exist, so the description must explain the return; it does so by naming status codes and min/avg/max latency, and it flags cost. That is enough for an agent to call it correctly, though failure modes remain 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 coverage is 100%, so url, runs, and timeoutMs are already documented in the schema. The description adds only framing ('GET endpoint', 'several times') rather than per-parameter meaning, 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 (probe) and resource (a GET endpoint), plus exactly what is reported: status codes and min/avg/max latency. This clearly separates it from overlapping siblings like dev_page_verify or dev_url_reader that fetch rather than measure response behavior.

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

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

Gives a clear use context: verify an API responds before spending money on it, e.g. an API discovered on the x402 Bazaar. It does not name alternatives or state when NOT to use it, so it stops short of full routing 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 burden. It does disclose the x402 pricing model ($0.02/call in USDC on eip155:8453) and what the response contains, which are genuinely useful. It omits auth requirements, rate limits, and failure behavior for invalid or unarchived URLs.

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 purpose well, but the closing sentence 'Use this when an agent needs to how the Internet Archive remembers a URL' is grammatically broken and largely restates the opening. The pricing tail is useful but tacked on.

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's enumeration of returned fields (first archive, latest snapshot, year span, recent captures) usefully fills that gap. For a single-parameter read tool this is nearly complete, only missing error/empty-result 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 coverage is 100% for the single url parameter, so the schema already documents it as 'URL or domain'. The description adds only the vague phrase 'for any URL', roughly matching the schema but adding no format, scheme, or normalization 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?

States a specific verb (Query) and resource (Internet Archive's Wayback index) and enumerates the return payload: first archive date, latest snapshot, year span, recent captures. It does not distinguish itself from plausible siblings like dev_page_verify or live_url_metadata, which query related web-state data.

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

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

Gives use-case context (fact-checking page history, deleted content, due diligence), which implies when the tool helps. However, it names no alternative tool and no when-not condition, so an agent must infer selection from sibling names alone.

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, so the description carries the disclosure burden. It adds useful context—full UTF-8 support including emoji/non-Latin scripts, and pay-per-call pricing ($0.01/call, USDC, eip155:8453)—but says nothing about input size limits, error behavior, or return shape for a tool with no output schema.

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

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

Front-loaded with the core action and kept to four short sentences. However the 'Use this when...' sentence is redundant and the 'uTF-8' typo slightly mars readability, so there is some 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 simple two-parameter conversion utility with no output schema, the description covers direction, encoding coverage, and cost. Return format is not stated, but the operation is simple enough that little else is needed to call 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 coverage is 100% and both parameters (text, direction enum) are documented in the schema, so the description need not repeat syntax. It reinforces the two-direction model but adds no semantics beyond the enum the schema already defines.

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 specific verbs (encode/decode) and resource (base64 text) with bidirectional scope, and notes UTF-8/emoji coverage. An agent can immediately tell what it does and how it differs from neighbors like dev_url_encoder or dev_hash.

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 only guidance is 'Use this when an agent needs to UTF-8 safe base64 in both directions,' which merely restates the purpose rather than naming a condition, alternative, or exclusion. No when-not and no sibling routing is provided.

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

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

With no annotations, the description carries the full burden, and it does disclose two real traits: automatic camelCase boundary splitting and an x402 payment requirement ($0.01/call in USDC on eip155:8453), which is important auth/cost context an agent needs before calling. It does not describe behavior on malformed or empty input, so it stops 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 and the case list, then pricing, with no wasted preamble. The middle 'Use this when...' sentence is largely redundant with sentence one, which costs it the top score.

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, yet the description never says what is returned (converted text) or how errors surface for unsupported input. Payment and case coverage are covered, so it is adequate but leaves a real gap for a tool with zero annotations 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% and the style enum is fully enumerated in the schema, so the baseline is 3. The description mirrors the enum values and adds the boundary-splitting note, but contributes no syntax or format detail beyond the schema itself.

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 ('Convert') and resource ('text') and enumerates the nine target cases, so the agent knows exactly what transformation is performed. It is clearly distinguishable from the unit/format converters in the sibling list (converters_length_converter, dev_number_base_converter, dev_csv_convert).

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 only guidance is 'Use this when an agent needs to camelCase, snake_case, kebab-case and more,' which merely restates the first sentence rather than telling the agent when this tool is preferable to a sibling or when it is inappropriate. No exclusions, prerequisites, or alternatives are named.

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 determinism and a per-call cost/auth model (x402 price $0.01/call, USDC, eip155:8453), which is real context. But it omits what happens on an invalid expression, whether validation failure is an error or a field in the response, and any rate-limit or output-shape detail.

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 capability and kept short. The third sentence ('Use this when...') largely repeats the first, and the pricing sentence is a tacked-on operational detail, but nothing is bloated.

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 does name the three return concepts (plain-English explanation, validation, next execution times), so an agent can anticipate results. The main gap is that it never resolves its overlap with dev_cron_next_runs, leaving routing ambiguous.

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 both parameters (expr, ref) are documented in-schema, so the baseline is 3. The description's cron format note ('5 fields: minute hour day month weekday') duplicates the schema rather than adding syntax nuance such as supported operators or how ref is parsed.

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 specific verbs and resource: turn a cron expression into plain English, validate it, compute next execution times. An agent knows exactly what it does. However, it fails to distinguish itself from the near-identical sibling dev_cron_next_runs, which appears to cover the 'next runs' half of this tool's purpose.

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?

'Use this when an agent needs to explain a cron expression and compute the next runs' essentially restates the purpose rather than giving selection criteria. No conditions, no exclusions, and no mention of dev_cron_next_runs, which the agent must choose between for the overlapping next-runs capability.

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 usefully discloses that timestamps are exact, that the schedule can be computed from now or a reference datetime, and that there is an x402 price, but it does not cover validation errors, timezone handling, count limits, or output 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?

The core purpose is front-loaded and the sibling comparison is useful. There is minor redundancy and a grammatical slip in 'needs to exact upcoming executions,' plus pricing information that is relevant but lengthens 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 simple three-parameter scheduling tool with full schema descriptions and no output schema, the description is mostly complete. It tells the agent what is returned at a high level and which sibling to prefer, though it omits output formatting and timezone details.

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 parameter schema already documents cron, count, and fromIso. The description reinforces the meaning of N executions and reference datetime filtering, but adds no new syntax, format, or constraint detail beyond the schema baseline.

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: list the next N executions of a cron expression with exact timestamps, optionally from a reference datetime. It also explicitly distinguishes this from the sibling dev_cron_describe by saying it complements that tool with concrete upcoming executions.

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 gives clear usage context: use when an agent needs exact upcoming executions for a cron expression, and it names the alternative dev_cron_describe. It does not spell out when-not to use it, but the intended scenario is well specified.

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 fairly well: it specifies the return shape (array of objects keyed by header row), documents RFC 4180 edge case handling (quoted fields, embedded delimiters, escaped quotes, multi-line values), and discloses the x402 pricing/payment rail. It does not cover error behavior, size limits, or header-row requirements when converting back.

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 first sentence is well front-loaded and dense, but the third sentence largely repeats it, and there is a typo ('cSV'). Pricing info is useful but tacked on at the end; the definition could be tighter.

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

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

With no output schema and no annotations, the description correctly compensates by describing the return structure for the CSV→JSON direction and the RFC 4180 quoting guarantees. Minor gaps remain around the JSON→CSV output shape and delimiter semantics, but an agent has enough to call 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 data, delimiter, and direction (with an enum). The description adds no delimiter semantics (e.g., default or accepted values) 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 (Convert) and both resources (CSV and JSON), including the exact output shape ('array of objects keyed by the header row'). This clearly distinguishes it from siblings like dev_json_formatter or dev_yaml_convert, which handle different formats.

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 sentence 'Use this when an agent needs a cSV to array-of-objects and back, with quote handling' restates the capability rather than giving real selection guidance. No alternatives are named and no when-not conditions are given, though the format makes the context fairly obvious.

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

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

With no annotations, the description must carry the full behavioral burden; it does disclose useful traits: determinism, that every issue cites its exact row number, and a per-call price ('$0.01/call, USDC, eip155:8453'). That pricing and determinism detail is genuinely valuable, but the return payload shape (issue list structure, severity, pass/fail signal) is never described and there is no output schema to compensate.

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 check list is dense and front-loaded, and the pricing/cost note is useful. The third sentence ('Use this when an agent needs to structural lint: ragged rows, dupes, quoting issues') largely re-lists issues already enumerated, making it mild redundancy rather than earning 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 validator with no output schema, the description should convey what a caller gets back; it only says issues cite row numbers, leaving the result structure and pass/fail signaling unstated. It also omits how expectedColumns is encoded, which is a real gap given all three params are required.

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 and the baseline is 3. The description adds only marginal meaning, hinting that column counts are checked 'against the header or an expected schema,' which loosely maps to expectedColumns, and implying RFC 4180 delimiter handling; it does not explain the expectedColumns string format.

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 ('Validate CSV structure') and enumerates the exact checks performed: RFC 4180 parsing, ragged rows, column-count consistency, duplicate headers, stray quotes, empty-cell counts. This clearly distinguishes it from sibling validators like dev_json_schema_validator and dev_csv_convert.

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 gives explicit context for invocation ('Use this when an agent needs to structural lint') and the pre-ingestion use case is front-loaded. However, it never names the alternative (e.g., dev_csv_convert) or states when NOT to use it, so routing between the two CSV tools is left 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 well: it discloses the algorithm (LCS), that output is unified-diff style, that the result is deterministic, and even the cost model ($0.01/call, USDC, eip155:8453). It stops short of stating input size limits, rate limits, or auth requirements beyond 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?

The purpose and differentiation are front-loaded, which is good, but the third sentence ('Use this when an agent needs to exact line-level diff with unified-style output') largely restates sentence one and is grammatically awkward, 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 pure-function text tool with three fully documented required params and no output schema, the description covers the essentials, including the return format (unified-diff style) that the missing output schema would otherwise have to explain. Only edge-case behavior (large inputs, encoding) is unaddressed.

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 a/b/context are already documented in the schema. The description mentions 'context' only in passing as part of the output and adds no format, range, or default detail for any parameter, so it does not meaningfully exceed the schema's baseline.

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 ('Compare two texts line by line'), names the algorithm (LCS diff), and specifies the output shape (unified-diff style with exact additions, removals and context). An agent can tell at a glance this is a deterministic text-diffing utility, clearly distinct from siblings like dev_text_chunker or dev_text_extract.

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 a clear when-to-use trigger: 'Use this when an agent needs a line-level diff with unified-style output.' It also implicitly contrasts with the alternative of asking a model to find differences ('Deterministic, unlike...'). However, it names no sibling tool and gives no when-not-to-use or input-size caveats.

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 it does disclose significant behavioral facts: the operation is a search/read, results come from two named sources, and it costs $0.02/call in USDC on eip155:8453. Pricing for a paid API is exactly the kind of context annotations would never carry. It doesn't state return shape or pagination, and there's no output schema, so it falls 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 core behavior and price, and every sentence adds something. However, the fragment 'Use this when an agent needs to "I need a tool that does X" → matched paid APIs' is grammatically awkward and the meta-tool sentence partly restates the opening.

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 three-param search tool with no output schema, the description covers what it searches, the two sources, the cost, and when to reach for it. Return format is unstated, but that is the main remaining gap and is not critical for 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 description coverage is 100%, so the schema already documents query, includeBazaar, and limit; baseline is 3. The description only adds that Bazaar inclusion is optional, which the enum already conveys.

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: describe a need, get back matching x402-paid APIs, from a named catalog (54 tools) plus the optional Bazaar. The meta-tool framing clearly separates it from every sibling, which are all concrete capability 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?

"Use this when an agent needs to 'I need a tool that does X'" gives an explicit triggering condition, and "instead of knowing an API exists, ask for the capability" distinguishes it from directly invoking a known sibling. It stops short of naming explicit exclusions or alternatives, so not a 5.

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

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

With no annotations, the description carries the full burden and does well: it discloses the protocol (RDAP), the 404-means-available semantics, the extra return fields (registrar, creation/expiration dates), and the $0.02 x402 payment requirement on eip155:8453. Rate limits and auth expectations beyond payment are not covered, 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?

Purpose is front-loaded, but the phrasing is loose and one sentence is grammatically broken ('needs to is this domain taken?'). Several clauses could be tightened, and the pricing detail is tacked on at the end.

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 and no annotations, so the description must explain returns — and it does (registrar plus creation/expiration dates, 404 semantics). A single-parameter lookup tool is well covered, though error/edge behavior beyond 404 is unstated.

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

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

Only one parameter and schema coverage is 100%, so the schema already documents 'domain'. The description adds the word 'domain name' but no format or validation detail, so the 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?

States a specific verb and resource ('Check whether a domain name is registered or available') and identifies the underlying mechanism (RDAP registry protocol). The clause 'Registry answer, not a landing page' separates it from sibling page/URL tools like dev_page_verify and live_url_metadata.

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 a clear usage scenario ('useful when an agent needs to name a product or verify how long a business has existed') and the trigger question ('is this domain taken?'). It does not, however, name alternatives like security_whois_lookup or live_dns_lookup, so the agent must infer the boundary itself.

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 traits: the two-layer process, that it performs a live network DNS MX lookup, and the x402 payment model ($0.01/call in USDC on eip155:8453). It omits failure/timeout behavior and what a negative result means when the domain is unreachable.

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 method and the value proposition are front-loaded, and the pricing line is a compact, useful addition. The mid-sentence phrasing ("needs to syntax + live MX check") is slightly awkward but the whole is economical.

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 or annotations, the description must stand alone, and it conveys the two validation layers plus the practical meaning of the result ("can this address receive mail?"). A brief note on the failed-lookup case would fully close the 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?

There is one parameter with 100% schema description coverage, so the schema already documents the input. The description adds no format or syntax guidance beyond the schema, leaving the baseline 3 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?

States a specific verb and resource ("Validate an email address") and goes further by naming the two-layer method: RFC-style syntax plus live DNS MX lookup. It distinguishes its approach from "pure regex" tools, though it never explicitly names the overlapping siblings (security_mx_lookup, live_dns_lookup).

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 a clear usage context ("Use this when an agent needs to syntax + live MX check — can this address receive mail?"), which tells the agent the scenario this fits. It stops short of naming alternatives or exclusions, e.g. when a pure syntax check or a bare MX lookup would be enough.

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

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

With no annotations, the description carries the full burden and does meaningful work: server-side fetching, an SSRF guard, support for both RSS 2.0 and Atom dialects, and a stated x402 price of $0.02/call in USDC on eip155:8453. It omits error/timeout behavior and any rate-limit or auth expectations, 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?

Three compact sentences with the purpose front-loaded and the return shape stated early. The marketing-ish aside 'no XML parsing on your side' is slightly redundant with the normalized-JSON claim, but nothing is bloated.

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

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

With no output schema and no annotations, the description does step in to name the returned fields, disclose the payment requirement, and note the security/dialect handling — enough for an agent to call it correctly. It is missing only edge-case behavior such as invalid or unreachable feeds.

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 two simple parameters (url, limit), so the baseline is 3. The description lists returned fields rather than clarifying parameter meaning, and adds nothing about URL formats accepted or how limit bounds the result set.

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 (fetch) and resource (RSS or Atom feed) plus the exact shape of the result (normalized JSON items: title, link, publication date ISO, summary). This clearly separates it from nearby siblings like dev_readability, dev_url_reader, and dev_text_extract, which return page text rather than feed items.

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 a clear usage condition: 'Use this when an agent needs to any feed → clean JSON items, no XML parsing on your side.' It explains the context that selects the tool but never names an alternative or states when not to use it (e.g., non-feed URLs belong to dev_url_reader).

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. It usefully discloses determinism, Web Crypto implementation, verified pure-JS MD5 for legacy checksums, and per-call pricing, but it omits output encoding, input-size limits, error behavior, and any authentication or rate-limit details.

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

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

The description is front-loaded and appropriately short, with each sentence contributing purpose, determinism, usage, or cost. Minor issues include the typo 'sHA-256' and slightly promotional pricing sentence, but it remains efficient.

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

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

For a two-parameter compute tool with no annotations and no output schema, the description is adequate to invoke it but incomplete. It does not explain the digest output format (e.g., hex vs. base64), input-size constraints, or error handling, which an agent may need for correct use.

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

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

Schema coverage is 100%, so the schema already defines the algo enum and text parameter. The description still adds useful meaning by stating the text is UTF-8 and by distinguishing SHA-family Web Crypto hashing from MD5 as a legacy checksum option.

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: compute exact hash digests of UTF-8 text. It enumerates the supported algorithms (SHA-256, SHA-512, SHA-1, MD5), so an agent can distinguish it from unrelated dev tools such as base64_encode or jwt_decoder.

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

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

It explicitly says to use this when an agent needs SHA-256/SHA-512/SHA-1/MD5 exact digests, giving clear usage context. It does not specify when not to use it or name alternatives, so it falls short of a 5.

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

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

No annotations, so the description carries the burden. It discloses the useful extras of access cost ($0.01/call, USDC on eip155:8453) and the returned fields (phrase, category, explanation), but says nothing about result sizing, pagination tied to limit, or behavior when code and category are both supplied.

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 short sentences, core capability front-loaded, price last. The second sentence ("Use this when...") is near-redundant with the first, which slightly dilutes efficiency but not enough to hurt usability.

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?

A simple read-only reference tool with full schema coverage and no output schema or annotations to lean on; the description names the return fields and the two query modes. Missing only edge-case behavior (combined code+category, paging via limit), which is minor for such a 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%, so the baseline is 3. The description clarifies the code-vs-category mode selection (empty code → list by category), which maps to the schema's "Leave empty to list by category" hint but adds no further syntax, ranges, or limit semantics 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?

States a specific resource (HTTP response status codes) and the two supported operations (look up a single code, or list a whole category 1xx–5xx). No sibling tool covers HTTP status codes, so the agent can distinguish it from the surrounding dev_* utilities without opening the schema.

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?

"Use this when an agent needs to look up any HTTP status code's meaning" gives a triggering condition, and the lookup-vs-list duality is mentioned. But it largely restates the purpose line and offers no when-not guidance or alternative for adjacent needs (e.g. security_ssl_inspector for diagnosing a live response).

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 a decent job: it discloses RFC 5545 output behavior (CRLF endings, text escaping, 75-octet folding, required DTSTAMP) and, unusually usefully, a per-call x402 payment cost with chain and currency. Gaps remain around the actual return shape (file vs. string) and error behavior.

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 capability and implementation details, then pricing. The third sentence is largely redundant with the first and contains a casing typo ('jSON'), but overall size is appropriate for the tool's complexity.

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 generator with no output schema and no annotations, the description covers standards compliance, cross-calendar compatibility, and cost. It stops short of describing return format or failure modes, but is otherwise sufficient 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 the two parameters are nominally documented, giving a baseline of 3. The description adds only 'from JSON events', and never specifies the expected shape of the JSON array elements, so it does not meaningfully enrich parameter semantics.

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 ('Generate a valid RFC 5545 iCalendar file from JSON events') plus the concrete standards being implemented (CRLF, escaping, folding, DTSTAMP). Although no sibling is named, the generate direction clearly contrasts with the inverse 'dev_ics_parser' in the sibling list.

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 sentence 'Use this when an agent needs a jSON events → valid .ics calendar file' is essentially a restatement of the stated purpose rather than added routing guidance. It never names the alternative (dev_ics_parser) or any exclusion/prerequisite, so usage 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 burden. It usefully discloses the payment model (x402, $0.01/call USDC on eip155:8453), which is real behavioral context an agent must know before calling. However, it says nothing about failure modes on malformed .ics, how the required 'limit' truncates results, 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?

Three sentences, front-loaded with the core purpose and output fields before the usage note and pricing. Efficient, though the usage sentence mildly restates the purpose sentence.

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 naming the returned event fields, which is exactly what an agent needs to consume the result. With only two well-documented input params and the pricing disclosed, the definition is nearly complete; only error/limit behavior is unaddressed.

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 two input parameters, so the baseline is 3. The description enumerates output fields, not input semantics, so it adds no meaning beyond the schema for the 'ics' and 'limit' arguments themselves.

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 (Parse) and resource (iCalendar/.ics content) and enumerates the exact output shape (title, start/end, location, organizer, description). This cleanly separates it from the sibling dev_ics_generate, which produces rather than consumes .ics.

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 a clear context sentence ('Use this when an agent needs to turn .ics calendar files into clean event JSON') and lists source scenarios (meeting invites, Google/Outlook exports). It does not explicitly name the opposite sibling (dev_ics_generate) or state when not to use it, so it falls short of a 5.

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

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

With no annotations, the description carries the burden. It discloses bidirectional exactness, week support, component breakdown output, and a per-call x402 price — all useful. But it says nothing about error handling for malformed durations, precision/overflow limits, or response shape beyond the phrase 'component breakdown'.

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 core purpose is front-loaded, but the text is padded with marketing ('The unambiguous duration math agents should use') and a garbled fragment ('Use this when an agent needs to durations ↔ seconds'). The price line is useful; the rest could be trimmed.

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 converter with no output schema, the description covers input format, example, both conversion directions, output shape (seconds plus component breakdown), and pricing. The main gap is error/invalid-input behavior, but the essentials for correct invocation are present.

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 enum target (seconds/iso) is self-explanatory, so the schema does the heavy lifting. The description adds marginal value via the example duration and the 'including weeks' scope note, but nothing about accepted input formats or units. 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?

States a specific verb (Convert) and resource (ISO 8601 durations) with concrete example input (P1DT2H30M) and both directions of conversion. The scope note (including weeks, component breakdown) lets an agent distinguish it from sibling converters like unix_timestamp_converter or number_base_converter.

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 clear use context: 'for retries, TTLs and scheduling instead of mental arithmetic.' That indirectly frames when to reach for it versus doing math, but it names no sibling alternatives or exclusions, so it falls short of a full when/when-not statement.

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 discloses recursion into objects/arrays, that type changes are flagged as changes, deterministic behavior, and the x402 price/per-call cost. It omits behavior on invalid JSON input and ordering guarantees, keeping 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?

Front-loaded with the core capability and output format, then behavioral details, then usage and pricing. Mostly earns its place, though 'Deterministic, unlike eyeballing' partly restates the earlier structural-diff point.

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 describing the return content (added/removed/changed values with JSON Pointer paths). Combined with the two fully-described inputs, it is nearly complete, missing only error/edge-case handling.

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

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

Schema coverage is 100% (both a and b documented as 'before'/'after'), so the schema already handles parameter meaning. The description adds no syntax, format, or encoding detail beyond what the properties already provide, making the baseline 3 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?

States a specific verb (compare) and resource (two JSON documents) with the distinctive output format (RFC 6901 JSON Pointer paths). The phrase 'not a text blob' and the contrast with text diffs cleanly separates it from siblings like dev_diff.

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 says to use it 'when an agent needs to structural diff with exact JSON Pointer paths', giving a clear use context and contrasting it with text diffs. It does not name dev_diff as the alternative or state when not to use it, so it stops short of a full when/when-not guide.

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 adds genuinely useful context via the x402 price ($0.01/call, USDC on eip155:8453) and hints that invalid input yields error messages rather than throwing. However, it never clarifies the failure mode or return shape (does invalid JSON raise, or return a result object?), which is the single most important behavior for a validator.

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 first sentence is well-structured and front-loaded with the primary verb. The second sentence largely duplicates it, and the pricing clause is appended awkwardly, 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 tool with no annotations and no output schema, the description should explain what comes back. It does list some outputs (error messages, top-level type, element counts) and the cost, but omits the critical ambiguity of how validation failure is surfaced, leaving a meaningful 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 both parameters are already documented, establishing a baseline of 3. "with any indent" loosely echoes the indent parameter but adds no format, range, or default 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 three specific operations (validate, pretty-print, inspect top-level type and element counts) on a specific resource (JSON), so an agent knows exactly what it does. It is distinguishable from dev_json_repair and dev_json_schema_validator by implication, though it never names those siblings to draw the boundary 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?

"Use this when an agent needs to validate, pretty-print and inspect JSON" is a near-verbatim restatement of the first sentence, adding no selection criteria. No when-not conditions and no alternatives (e.g. dev_json_repair for malformed input, dev_json_schema_validator for schema checks) are mentioned, leaving the agent to guess at the sibling boundary.

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 disclosure burden, and it does substantial work: the full list of supported defect classes tells the agent what repair scope to expect (including non-obvious truncation recovery and Python-literal coercion), and it discloses the payment/auth requirement ('x402 price $0.01/call (USDC, eip155:8453)'), which is critical operational context. It is silent, however, on the return value and on what happens when input is unrepairable or only partially repairable.

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 verb and the defect list, followed by rationale and a usage condition; nothing is buried. Minor redundancy: 'Built for the most common agentic failure mode — parsing slightly-wrong JSON from an LLM or a human' and 'Use this when an agent needs to fix LLM-mangled, truncated or sloppy JSON' restate the same point in back-to-back sentences.

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, non-nested tool with no output schema and no annotations, the description covers the input domain, defect scope, intended caller scenario, and cost. The one meaningful gap is that, with no output schema present, it never states what comes back (repaired JSON text? a status plus repaired text?), leaving the agent to guess at the result 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?

There is a single parameter ('text') and schema description coverage is 100%, so the baseline is 3. The description adds essentially no semantics about the parameter beyond the schema; it only implies the input is a raw JSON string that may be malformed.

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 ('Repairs broken JSON') and enumerates the exact defect classes handled (trailing commas, single quotes, Python literals, NaN, comments, smart quotes, truncation), which is far more informative than a bare 'fix JSON'. It does not explicitly name or contrast itself with the closely related siblings dev_json_formatter and dev_json_schema_validator, so an agent must infer the boundary between repairing, formatting, and validating.

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 clear usage context twice: 'Built for the most common agentic failure mode — parsing slightly-wrong JSON from an LLM or a human' and 'Use this when an agent needs to fix LLM-mangled, truncated or sloppy JSON.' This tells an agent the triggering condition well. It stops short of explicit exclusions or named alternatives (e.g., 'use dev_json_formatter for already-valid JSON'), which is what a 5 would require.

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 discloses the return shape (valid/invalid plus violations with JSON Pointer locations and messages) and payment terms ($0.01/call in USDC on eip155:8453), but omits rate limits, input-size limits, and explicit read-only/no-side-effect confirmation.

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

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

The description is front-loaded with the core operation and return behavior. The third sentence repeats the usage condition already implied by the first, creating minor redundancy, while the price sentence is necessary for invocation.

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

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

With no output schema and no annotations, the description does real work by explaining return values, version expectations, and payment. It is complete enough for a two-parameter read tool, though edge-case behavior for malformed input is not covered.

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 input schema gives only terse descriptions ('JSON data', 'JSON Schema'). The tool description adds meaningful constraint by specifying draft 2020-12 for the schema parameter, exceeding 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?

States a specific verb, resource, and version: 'Validate a JSON document against a JSON Schema (draft 2020-12).' The purpose is clearly distinct from sibling tools like dev_json_formatter and dev_json_repair.

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?

'Use this when an agent needs to validate JSON against a draft 2020-12 schema' gives a clear usage condition. It does not name when-not conditions or alternatives, but no sibling performs schema validation.

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 the deterministic guarantee, the structural mapping rules, and the x402 payment cost ($0.01/call, USDC on eip155:8453). It stops short of describing failure behavior for invalid JSON, which is a gap for a deterministic transform 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 first sentence is dense and informative, but the usage sentence is awkward ('jSON sample → typed interfaces') and repeats the purpose rather than adding guidance. The stray lowercase 'jSON' typo and a marketing-style fragment reduce polish.

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 tool with no output schema or annotations, the description conveys the transformation contract, determinism, and cost, which is nearly enough to call it correctly. Missing only return-value shape (string vs. file) and invalid-input 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 coverage is 100% with two documented parameters, so the baseline is 3. The description explains the transformation semantics but adds nothing about the 'json' or 'rootName' parameters beyond what the schema already states.

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 (generate TypeScript interfaces from a JSON sample) and goes further by naming the transformation rules (nested objects → named interfaces, arrays → element type, mixed arrays → unions). This clearly distinguishes it from siblings like dev_json_formatter and dev_json_schema_validator.

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 sentence 'Use this when an agent needs a jSON sample → typed interfaces, ready to paste' gestures at usage but largely restates the purpose already given. No alternatives (e.g. json_schema_validator) are named and no exclusions or prerequisites are 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 the full burden and does well: it discloses that signatures are NOT verified, no secret is required, both standard and URL-safe base64 (with or without padding) are accepted, and exp/iat are rendered as dates. It also notes the x402 payment requirement. It omits error behavior (e.g., what happens on a malformed token), which keeps it just 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 compact and front-loads the core purpose, with the most decision-relevant fact (no verification) stated early and the payment note at the end. The 'no verification' idea is repeated in the usage sentence, a minor redundancy that keeps it from 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?

There is no output schema, so the description must describe returns, and it does: header and payload as readable JSON with date-rendered claims. Combined with the encoding and payment notes, an agent has nearly everything needed; only malformed-input behavior is unstated.

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

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

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning by specifying the accepted encodings (standard/URL-safe, padded or unpadded) and the token shape. These are format semantics the bare schema string does not convey.

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 (Decode) and resource (a JWT's header and payload) plus the exact output form (readable JSON). It also delineates itself from the adjacent 'verify' capability, so an agent knows precisely what this tool is and is not. No sibling performs JWT decoding, so there is no ambiguity to resolve.

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 says 'Use this when an agent needs to decode header and payload — no verification,' which gives a clear trigger condition. It lacks an explicit when-not-to-use or a named alternative, but within this catalog no alternative exists, so the guidance is effectively complete.

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