EMpulse Street FX Index

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 does disclose the access tier (Pro/Enterprise) and the returned components (day's range, source count, confidence class, dollar-leg cross rate, corridor premium), including the sign convention for the premium. It does not mention rate limits, error behavior, or explicitly state read-only status, but for a read-style market-data query it supplies substantial 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?

It is a single dense sentence with no filler; the core rate definition is front-loaded before the supporting return fields. The parenthetical and multi-clause construction reduce scanability slightly, so 4 rather than 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?

Given a three-parameter tool with 100% schema coverage and an output schema, the description supplies the key invocation semantics: currency direction, data source type, returned metrics, premium interpretation, and key tier. It lacks alternative-tool routing, but the structured fields cover the rest adequately.

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 a, b, and lang. The description adds economic meaning and direction beyond the schema by defining the quote as 'units of b per 1 a' and tying a/b to two emerging-market countries; it does not add lang semantics, but that is already in the schema.

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

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

The description names the specific resource—the rate between two emerging-market currencies from public exchange listings—and the exact orientation (units of b per 1 a), plus the derived cross rate and corridor premium. That is more specific than the title, though it does not explicitly contrast the tool with siblings such as get_rate_stack or get_street_rate, 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?

It gives no when-to-use or when-not-to-use guidance and names no alternatives among the many sibling rate tools. The only usage-adjacent sentence is an access constraint ('Pro and Enterprise keys'), not selection guidance.

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

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

With no annotations at all, this description carries the full behavioral burden and does a fair job: it discloses that results are quotations with public source links, that the feed is bounded by the plan's latest available day, and that free plans incur a 48-hour delay. It stops short of stating pagination/volume limits, what an empty result looks like, or whether the feed is strictly read-only, 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?

Two sentences, front-loaded with what the feed contains before moving to filtering and plan mechanics. The em-dash enumeration of event types is informative but slightly long; overall tight with little wasted 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?

An output schema exists, so return structure needn't be spelled out, and the description still sketches the item shape (quotation plus source link). Plan-tier delay and filtering are covered. Minor gaps remain: behavior when both country and currency are supplied, and whether the event-type list is exhaustive.

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: 'filter by country or currency' signals these are alternative narrowing dimensions rather than combinable ones, and 'days back from the latest day of your plan' clarifies that the window is anchored to the plan's most recent data rather than to today — a nuance the schema's '1–90, default 7' 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-like resource: a dated feed of FX-moving events in emerging markets, with concrete examples (devaluations, withdrawal limits, stablecoin bans, currency controls, payment outages) and the return form (short quotation plus source link). It is clear what an agent gets back, but it never distinguishes itself from nearby siblings such as get_stress_signals or get_rail_incidents, which plausibly overlap with 'payment outages'.

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

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

The description gives operational context — filter by country or currency, and `days` counted back from the latest day of the plan, with free tier limited to a 48-hour delay — which implies when the tool is useful (recent country/currency-specific news events). However, it offers no explicit when-to-use or when-not-to-use guidance versus get_stress_signals, get_rail_incidents, or get_rate_history, leaving the agent to infer 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 does well: it discloses the return composition (vwap, high, low, hours, busiest hour), that each hour carries a component label (transaction_based / multi_source / combined) and quality flag, and that coverage is limited to currencies with hourly market data plus a paid-key requirement. Missing only pagination/volume and error behavior for out-of-coverage currencies.

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?

Effectively one long sentence with the key scoping facts front-loaded: per-hour rate, then the day summary, then coverage and key tier. Dense but no filler; the nested parenthetical lists make it slightly harder to scan than it could be.

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 read tool with a full schema and an output schema, this is nearly complete: scope, granularity, coverage, and access tier are all stated. The only gap is guidance on choosing it over the sibling rate tools.

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 (date as UTC YYYY-MM-DD defaulting to today, currency as ISO 4217) are already documented in the schema. The description reinforces the UTC-day semantics but adds no syntax or edge-case detail beyond that, 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: hourly street rate for one currency on one UTC day, plus the day's summary aggregates. That is clearly distinguishable from get_street_rate (spot) and get_rate_history (historical series), though no sibling is named 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?

The 'Pro and Enterprise keys' note gives a real access prerequisite, and 'for every currency with hourly market data' implies a coverage boundary. However, there is no explicit when-to-use-this-vs-get_street_rate-or-get_rate_history guidance, which matters given 15 sibling tools with overlapping rate concepts.

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 format ('as markdown') and enumerates the substantive content areas covered, which is useful behavioral context. It does not explicitly state that the operation is read-only or static, but that is strongly implied by a documentation getter.

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

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

A single dense sentence is front-loaded with the core purpose and then lists the covered topics and output format. There is no redundant or filler 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?

Given a zero-parameter documentation tool with an output schema, the description is complete enough: it tells the agent what the markdown contains and that citation format is included. No additional parameter or return-value explanation is needed.

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

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

There are zero parameters, so the baseline is 4. The description correctly implies that no inputs are needed to retrieve the methodology.

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 exact resource (the methodology for how the EMpulse Street FX Index is computed) and specifies its scope: components, confidence classes, outliers, revisions, coverage rules, and citation format. It is unmistakably a documentation tool and clearly distinct from the sibling data-retrieval tools.

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

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

The description implicitly tells the agent this is the place to learn computation details and citation format, but it never states when to use it versus alternatives or when not to use it. For a zero-parameter documentation endpoint, the intended use is easy to infer, but explicit routing guidance is absent.

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 so well: it discloses tier gating (free level is one day behind; Pro keys of EM FX News & Sentiment unlock the score, 90-day norm, article count, early signal, topics, and predictive links), plus a confidence qualifier on the correlation figures. Missing only error/empty-data behavior and freshness beyond 'one day behind'.

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

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

Front-loaded with the core purpose, then cleanly split into no-currency and with-currency branches. The Pro-feature enumeration is long but each item is a genuinely distinct output field, so little is wasted; a slight trim of the trailing list would tighten it.

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?

Although an output schema exists and return values need not be explained, the description still surfaces the Pro/free split that the schema cannot express, which is critical for correct invocation. Gaps are minor: no guidance on invalid currency codes, coverage boundaries, or what happens when a currency has no recent articles.

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

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

Schema coverage is 100%, so baseline is 3; the description adds value by explaining what the `currency`-absent branch actually returns (a ranked map of the 7-day fall in tone) rather than just restating 'omit for the map'. The `lang` parameter is left entirely to the schema, which is acceptable given its full description there.

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 (what the news says about a currency's country, day by day) and immediately distinguishes two distinct outputs: the ranked coverage map without a currency, and the per-currency daily reading with it. No sibling tool overlaps this, so an agent can select it from the name plus first sentence alone.

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 tells the agent when to omit `currency` (get the map) versus supply it (get the latest day), which is the primary routing decision for this tool. It does not, however, contrast itself with adjacent siblings like get_stress_signals or get_official_vs_street, nor state prerequisites for Pro-only fields.

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 access-tier requirement ('Pro and Enterprise keys'), which is valuable and non-obvious. It omits freshness/update cadence, whether the call is read-only (inferable from the name), and any rate limits or failure modes.

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

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

A single sentence, front-loaded with the metric definition, with zero filler. It reads as a sentence fragment and could open with a verb for clarity, but nothing is wasted.

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

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

The output schema exists, so enumerating return fields is redundant though harmless, and the key tier info is a genuine addition. However, a low-complexity lookup tool still lacks any usage context or coverage notes (which currencies are supported), leaving it only minimally 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%, with both currency (ISO 4217, examples EGP/NGN/ARS) and lang fully documented in-schema. The description adds nothing beyond that, so the baseline 3 applies.

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

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

The description defines the specific metric computed (street rate vs. official central-bank rate) and enumerates the resulting fields, which implicitly separates it from get_street_rate (street only). It never states a verb like 'get' or 'compute', so the purpose is clear but slightly implied rather than asserted.

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

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

There is no guidance on when to use this versus get_street_rate, get_rate_history, or get_stress_signals, all of which overlap on FX data. The only routing signal is the implicit 'this one includes the official rate'.

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

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

With no annotations, the description carries the burden and does well: it discloses the four possible statuses, what each entry contains (time began, ready citation), and a real access constraint (free level is one day behind and limited currencies; Pro keys unlock today/every currency/index/availability/supply). It stops short of explicit auth mechanism or rate-limit 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-loads the purpose in the first clause, then the status/coverage framing, then the tier distinction. The long enumerations (method classes, statuses) are dense but each clause carries information; no filler 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?

An output schema exists, so return values need not be spelled out, yet the description usefully previews the shape and the free/Pro data boundary. Combined with full schema coverage, an agent has enough to invoke it correctly; only sibling routing is missing.

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

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

Schema description coverage is 100%, and both currency (ISO 4217) and lang (ISO 639-1) are fully documented in the schema. The description adds no parameter-level meaning beyond establishing that a single country/currency is the subject.

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: which payment methods work in a country today, broken down by method class and direction, with statuses. An agent can tell it apart from incident/stress siblings conceptually, but no sibling is named for explicit contrast.

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

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

Usage context is implied through the free-vs-Pro tier framing (free = free currencies one day behind; Pro keys = today, every currency), but there is no explicit 'use this when X, use get_rail_incidents when Y' routing against the numerous siblings.

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

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

With no annotations, the description carries the burden well: it discloses default and max window, ordering (newest first), the output shape (one-line summary with timestamps), and an access requirement (Pro keys of the Rail Health Index). It does not state pagination limits, rate limits, or what is returned when nothing occurred in the window.

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

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

A single dense sentence that front-loads the scope (all status changes), then window, ordering, output example, currency option, and access tier. The inline example earns its space by showing the exact result shape.

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?

An output schema exists, and the description still gives a representative record, so an agent knows exactly what it will get. Window bounds, ordering, scoping, and access tier are all covered for a simple 2-parameter, zero-required read tool.

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

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

Schema coverage is 100% and already documents the 1–90 bound, the default of 30, and the ISO 4217 currency code. The description only restates the default window and that currency is optional, adding no format or matching semantics 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 precise verb+resource: every status change (degraded, outage, healthy) of a payment method class, newest first, over `days`. The "change of status" framing distinguishes it in spirit from snapshot siblings like get_rail_health, but that sibling is never named, so the differentiation is left implicit.

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

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

Implies the use case (reviewing rail outages/incidents over a recent window) and notes optional currency scoping, but gives no explicit when-not-to-use and does not name get_rail_health or get_fx_events as the alternatives for current state or event timelines.

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

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

With no annotations provided, the description carries the full burden and does well: it discloses the inclusive UTC day semantics, a hard 400-day-per-call limit, the default date range tied to the user's plan, and the shape of returned data (rate, buy, sell, confidence per day plus summary). It omits rate limiting, error behavior, and exact plan-tier constraints, 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?

Two dense sentences, front-loaded with the core purpose, followed by limits and defaults. Every clause (inclusive/UTC, 400-day cap, output fields, default range) adds actionable information with no filler.

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

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

An output schema exists, so return values needn't be spelled out, yet the description still summarizes them usefully. With 100% schema coverage and only four parameters, the definition is nearly complete; the remaining gap is the absence of any routing to sibling tools for current-rate or comparison use cases.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema: it clarifies that from/to dates are inclusive UTC days, that a single call may cover at most 400 days, and that omitting both dates yields a default 30-day window up to the latest day of the plan.

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 ('Daily street rates of a currency') with clear scope (between two dates, inclusive, UTC, max 400 days) and lists the returned fields. It implicitly distinguishes itself from get_street_rate by offering a daily history rather than a single current rate, but never names the sibling 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?

The description explains defaults (last 30 days up to the latest day of your plan) but gives no guidance on when to use this tool versus alternatives like get_street_rate for a current rate or get_official_vs_street for comparisons. There are no explicit when/when-not conditions.

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

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

With no annotations, the description carries the behavioral burden and does well: it discloses the free-tier delay, paid-tier coverage, confidence classes, citation behavior, and what happens when a country does not publish a rung independently. It stops short of stating read-only behavior, rate limits, or error handling explicitly.

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 dense but front-loaded, opening with the core concept and then adding access-tier context. The long first sentence is information-rich and every element is relevant, though it is close to being overloaded.

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?

An output schema exists, so the description need not explain return values in full, yet it still covers the key output components and access tiers. It lacks explicit routing guidance versus sibling tools and auth/error details, which keeps it from a 5.

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 schema already documents both the required ISO 4217 currency code and the optional citation language. The description adds no syntax or format details beyond what the schema provides, so baseline 3 is appropriate.

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

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

The description states exactly what the tool returns: the full ladder of rates for one currency on its latest day, including specific rungs, gaps, trends, widening signal, and citation. The enumerated rungs and derived metrics make its scope unmistakable and distinguish it from single-rate siblings such as get_street_rate or get_official_vs_street, even without naming them explicitly.

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

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

It gives useful context that this covers the latest day and explains free versus paid access levels. However, it does not explicitly say when to choose this tool over related siblings like get_street_rate, get_official_vs_street, or get_rate_history, so usage is implied rather than guided.

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 enumerates the returned fields (mid, buy, sell, spread, 1/7/30-day changes, confidence class, citation) and discloses the tiered-access behavior — free data is one day delayed, a Pro key unlocks the current day. It stops short of stating rate limits or the exact auth mechanism.

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

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

Two sentences, front-loaded with the core capability and the source, then closing with the access-tier caveat that affects result freshness. No filler, no repetition of the title.

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?

An output schema exists so return values need not be spelled out, yet the description still previews them usefully. Access tiering is covered. The only missing piece for a 3-parameter lookup tool is any mention of error behavior for unsupported currencies or dates outside plan coverage.

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 date, lang, and currency are already documented in the schema. The description only loosely gestures at them ('the rate on a given day', 'a ready citation'); it adds no format or constraint detail beyond what the schema already 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?

States a specific verb+resource ('latest street exchange rate of an emerging-market currency against USDT') and names the source index, so the agent knows this is a current street-rate lookup rather than history or official rates. It does not explicitly name the distinguishing siblings (get_rate_history, get_official_vs_street), leaving that inference to the agent.

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?

'or the rate on a given day' implies the date-parameter use case, and the free/Pro delay sentence tells the agent when the returned value will be stale. However, there is no explicit statement of when to prefer this over get_rate_history or get_official_vs_street, which are the closest alternatives.

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

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

With no annotations, the description carries the burden well by disclosing the stress conditions, the returned flag levels, the fired rules, and the episode start day. It also mentions access-tier restrictions and scope, though it does not explicitly state read-only behavior, rate limits, 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 description is front-loaded with the purpose, then efficiently packs in criteria examples, return details, scope, and access requirements. Every phrase contributes useful information without 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?

It is nearly complete for a read-oriented analytical tool whose output schema exists: the description explains what stress means, what is returned conceptually, and who can call it. Minor omissions like data freshness or rate limits keep it from a 5.

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 parameter is already fully documented as an optional ISO 4217 code. The description's phrase 'One currency or all' aligns with the schema default but adds no further semantics beyond what is already structured.

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 resource and output: per-currency none/watch/alert stress flags from street-market conditions. It clearly distinguishes this signal-monitoring tool from siblings like get_street_rate or get_rate_history by focusing on early-warning stress episodes rather than raw rates.

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 as an early-warning stress monitor and notes that it works for one currency or all, plus the Pro/Enterprise key requirement. It does not explicitly name when to choose a sibling tool or give exclusions, so it falls 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 and does disclose important behavior: the free level is one day behind, and Pro keys unlock additional fields. It does not mention rate limits or error behavior, but the key freshness and access-tier traits are surfaced.

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

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

The purpose is front-loaded, then the two currency modes are presented in parallel. Despite covering freshness and plan-gated fields, every clause carries useful information and there is no filler.

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

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

The description explains both modes, data freshness, and Pro-level fields, while an output schema exists to document return shape. The only gap is that the lang parameter is not discussed in the description, but the schema covers it.

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

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

Schema coverage is 100%, so the baseline would be 3, but the description adds meaningful semantics for the currency parameter: omitting it returns a ranking, while providing it returns rank and trend for that currency. It does not add detail for the lang parameter, but the schema already covers both.

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 domain resource — unmet payment demand in emerging markets — and precisely distinguishes the two output modes based on whether a currency is supplied. An agent can immediately tell what the tool does and how the response differs by invocation style.

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 invocation context: omit currency for a ranking, provide currency for a specific market's rank and trend. It does not name alternative sibling tools or state when not to use this one, but the parameter-driven usage is explicit enough for correct selection.

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

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

With no annotations, the description carries the full burden. It discloses access tiers (free vs Pro), data freshness (yesterday vs today), and that a citation is included. It does not mention error behavior or explicitly state that the operation is read-only, but the access-level details add meaningful 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?

The description is a single paragraph that front-loads the core purpose, though the opening phrase 'Where and when the dollar actually moves through USDT' is slightly verbose. Both sentences earn their place by covering the core output and access tiers, with no redundant information.

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

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

Given the tool's simplicity (2 parameters, output schema present), the description is largely complete: it explains the main output, the scale, and what Pro adds. It could be improved by explicitly noting that the operation is read-only or by giving a hint about the response structure, but for a simple read tool it is sufficient.

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 fully documents both parameters. The description adds no parameter-specific meaning beyond what the schema provides, so the baseline of 3 is appropriate.

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

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

The description clearly states the resource: the liquidity index of a currency, including its scale (0–100, 50 = 90-day norm) and the inclusion of a citation. It distinguishes itself from siblings by focusing on USDT liquidity, though it does not explicitly contrast with any sibling tool.

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

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

It describes what data is available at the free level versus Pro keys, which implicitly suggests when to use the tool based on access. However, it does not explicitly state when to choose this tool over alternatives like get_street_rate or get_official_vs_street, nor does it mention any prerequisites beyond key level.

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

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

With no annotations, the description carries the burden and does add useful context: the 'coverage in progress while market sources are being added' state and the per-plan coverage flag tell the agent results may be partial and entitlement-gated. It does not state whether authentication is required (the request_free_key sibling implies keys matter) or how large the list is, so 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?

A single dense sentence that front-loads the resource and then the returned attributes. It is tightly packed with no filler, though the run-on list of attributes is slightly harder to scan than a short lead sentence followed by detail.

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

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

For a zero-parameter catalog call with an output schema and no annotations, this is nearly complete: it explains what each entry means conceptually, which the schema's field names alone may not. The main remaining gap is confirming whether an API key/plan is needed 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?

The tool takes zero parameters, so the baseline of 4 applies. The description adds nothing parameter-related and needs nothing.

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 exact resource — every currency of the EMpulse Street FX Index — and enumerates the attributes returned (status, confidence class, source count, coverage since, plan coverage). No sibling tool lists currencies, so differentiation is implicit and unambiguous, though the verb ('list') is only implied by the noun phrase rather than stated.

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

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

Usage is only implied: an agent can infer this is a discovery/catalog call to run before get_street_rate or get_rate_history, but the description never says when to call it or references any sibling as an alternative. 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 carries the full burden and does well: it discloses the 100 calls/day rate limit, the data freshness limitation (up to yesterday), free-tier currency coverage, that the key is both returned and emailed with an example, and that it is sent via the X-API-Key header on this server and the REST API. It does not cover key expiry, revocation, or duplicate-email 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?

A single dense sentence that is front-loaded with the core action and then layers on tier limits, delivery mechanics, and header usage. It is efficient, though the second half could be split for readability.

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

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

Given the presence of an output schema, the description need not explain return values, and it correctly focuses on tier limits, data freshness, key delivery, and how to use the key. Missing only edge-case behavior such as duplicate requests or key expiration.

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 email parameter, so the schema already documents it thoroughly. The description only restates that the key is issued 'for an email address,' adding no extra syntax or format constraints 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 verb (issue) and resource (free EMpulse API key) with the required input (email address). This is clearly distinguishable from all sibling tools, which are data-retrieval endpoints, not key provisioning.

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

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

Explains the offer in practical terms: free currencies, data up to yesterday, 100 calls per day, key returned and emailed. It does not explicitly say when not to use it (e.g., if the user already has a key) or mention alternatives, but the context is clear enough for an agent to act.

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