NythosX Market Data

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: one-minute polling cadence, single-fire behavior, HMAC-SHA256 signing with the exact header format and key source, TTL defaults/bounds, and a per-call cost with payment protocol. This is far beyond what a bare name implies.

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

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

Purpose is front-loaded in the first clause, followed by tightly packed operational details. The signing sentence is dense but each clause carries non-redundant information; 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?

No output schema and no annotations, yet the description covers firing behavior, signing, TTL, cost, and status-check path. It stops short of describing the event payload shape or webhook retry/failure behavior, which an agent 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 coverage is low (40%), so the description must compensate, and it adds the ttl_hours default (168) and the webhook_url signing contract. price/direction/symbol semantics remain unelaborated, though they are largely self-evident from the enum and type.

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 ('Arm a price trigger with webhook delivery') plus the mechanism (polling + signed POST). It also distinguishes itself from the sibling get_trigger_status by noting status checks are free at a separate endpoint.

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 operational context: single-fire semantics, first-crossing-only firing, and where to check status instead of re-arming. It does not explicitly state when arming is inappropriate or contrast with any other arming alternative.

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 verdict is rules-based, the possible verdict values are enumerated, invalidation conditions are included, and each call costs $0.01 USDC via x402. It omits latency and whether a funded wallet/setup is prerequisite, but the payment and determinism disclosures are solid value beyond structured fields.

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 deliverable in the first fragment, then a single dense sentence covering outputs and price. The factor enumeration is long but each item conveys what feeds the verdict; 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?

No output schema exists, and the description adequately compensates by listing the verdict categories and result fields. No annotations either, and it covers cost and invalidation; the remaining gap is orchestration guidance relative to sibling analysis 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% with enums for both symbol and tf, so the schema fully documents the inputs. The description adds no parameter-level meaning (the factor list describes outputs, not inputs), 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 (rules-based trade verdict) plus its concrete outputs: verdict enum, score, confidence, entry/stop/target/RR plan, factors, and invalidation conditions. That content profile distinguishes it from siblings like get_market_regime or get_support_resistance, though it never names those alternatives 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?

Usage is only implied — an agent can infer this is the tool that produces a full trade recommendation, but there is no statement of when to call it versus get_target_probability, get_market_regime, or get_support_resistance. The $0.01 USDC note is useful but is a cost precondition, not usage 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 disclose meaningful operational facts: data granularity (hourly candles) and a paid invocation model ($0.005 USDC per call via x402), which tells the agent this call has a real cost and requires payment handling. It does not cover rate limits, error behavior, or data freshness, so the disclosure is strong but not 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?

Two sentences, front-loaded with the purpose and then the exact computed signals, with the cost caveat last. Every clause carries information; nothing is redundant padding.

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 well by enumerating the indicators returned (trend, volatility bucket, RSI, EMAs) and noting granularity and cost. It falls short only in omitting usage context relative to sibling analysis tools and any freshness/caching notes.

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 (symbol) at 100% schema description coverage, with a full 13-value enum in the schema. The description adds nothing about the symbol parameter, so the schema does all the work; 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 names the resource (market regime) and enumerates exactly what is computed: trend up/down/range via EMA50 vs EMA200, volatility bucket via ATR%, RSI, and EMAs, all from hourly candles. That level of specificity clearly separates it from siblings like get_support_resistance or get_target_probability, 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?

There is no guidance on when to call this tool versus the other market-analysis siblings (get_support_resistance, get_advisor_verdict, get_target_probability). The description is purely descriptive of output content and never states a use case or exclusion.

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 the pricing model ($0.005 USDC per call via x402), the output volume cap (five levels per side), the derivation methods (clustered daily swing pivots, high-volume nodes, round numbers), and the per-level fields including strength scale and touch count. It omits caching, latency, or failure behavior, but the payment and derivation context is unusually informative.

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 ordered as what-it-is, what-it-returns, what-it-costs; every clause carries information and nothing is redundant.

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 takes on the return-value burden and does so thoroughly by listing the level fields and the nearest-level-each-side addition. The main shortfall is that it never explains how a caller should act on the result or the resolution/timeframe of the levels, but it is sufficient to invoke correctly.

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

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

Only one parameter exists and schema description coverage is 100%, with the enum enumerating every supported instrument, so the schema does the heavy lifting. The description adds no syntax, timeframe, or formatting meaning beyond what the schema already provides, which lands at the baseline 3.

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

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

The description names a specific resource (support and resistance levels) and details exactly what the output contains, so an agent knows this computes technical levels rather than a regime or probability verdict. It does not explicitly contrast itself with siblings like get_market_regime or get_target_probability, which keeps it at a 4 rather than 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?

There is no statement of when to reach for this tool versus the other analysis tools in the family, and no prerequisites or exclusions are given. Usage is only implied by the technical-analysis nature of the resource.

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 meaningful traits: a per-call cost of $0.005 USDC via x402 (a real invocation constraint) and the underlying method (14-day ATR normal approximation, touch ≈ 2x close-beyond). It does not describe error handling, symbol coverage limits, or response shape.

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

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

Front-loaded with the core purpose, and the methodology and cost details are compressed into a parenthetical. The opening two sentences partially restate each other ('probability of reaching a target price' vs 'probability that the price closes beyond a target'), which is minor redundancy.

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

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

No output schema exists, so the description must convey returns, and it does: close-beyond probabilities at three horizons plus a touch probability. Combined with the cost disclosure, an agent has enough to call and interpret it, though nothing is said about invalid symbols or failure modes.

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 schema already defines symbol and target. The description adds only implicit context that target is evaluated against closes at 1/7/30-day horizons, which is the baseline level of added value when the schema does the heavy lifting.

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

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

The description states a precise computation: the probability that price closes beyond a target at 1, 7 and 30 days, plus a touch probability. It is clearly distinct from siblings like get_support_resistance or get_market_regime, though it never explicitly contrasts itself with them.

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

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

There is no statement of when to use this tool versus alternatives such as get_support_resistance or get_advisor_verdict, and no prerequisites or exclusions. The only guidance-like content is the per-call cost.

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 and does so well: it discloses the paid-call requirement ($0.005 USDC via x402), the optionality of the symbol filter, and the statistical caveat that same-day verdicts on one instrument are correlated so independentSamples counts distinct instrument-days. It does not state whether the call is read-only or whether results are cached, which keeps it short of a 5.

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

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

The metric list is dense but every item is meaningful and the purpose is front-loaded in the first sentence. The trailing cost sentence is also load-bearing; only the sheer number of metrics makes it slightly heavy.

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 must describe returns, and it does so thoroughly (metric names, per-bucket/per-verdict/per-symbol breakdowns, interval type). Payment terms are covered; what remains thin is any statement of access/auth flow beyond the x402 fee.

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

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

Schema coverage is 100% and the single enum parameter is already documented in the schema, so the baseline is 3. The description adds only that the symbol acts as an optional filter ('Optional symbol filter'), which is marginal value beyond the schema's 'Instrument symbol'.

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 and scope: graded accuracy of past Advisor verdicts, with the exact metrics returned (hit rate, average return, Wilson intervals, Brier score, independentSamples). This clearly separates it from get_advisor_verdict, which returns the verdict itself rather than its realized performance, 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?

Usage is implied by the framing (use it to check how the Advisor has performed historically, optionally narrowed by symbol), but there is no explicit statement of when to prefer this over get_advisor_verdict or other siblings, and no 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 carries the full burden of behavioral disclosure. It usefully notes that the tool is free and tied to triggers created by arm_price_trigger, but it does not confirm read-only behavior, describe error cases, or explain what the status response contains.

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 that front-loads the resource and scope with zero wasted words. It is appropriately sized for a simple status lookup tool.

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 read tool with no output schema, the description gives the essential scope and cost. It falls short by not describing the return value at all, which is important because no output schema exists to document it.

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

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

The schema has 0% description coverage for the single required 'id' parameter, so the description must compensate. It implies the id refers to a trigger armed with arm_price_trigger, but it never explicitly mentions the parameter, its expected format, or how to obtain the id.

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 the resource (a trigger) and the scope (armed with arm_price_trigger), and names the sibling tool that creates it. It is clear what the tool retrieves, though it does not spell out what fields the status includes.

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

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

The phrase 'armed with arm_price_trigger' implies the tool is used after calling arm_price_trigger, giving implicit context. However, there is no explicit when-to-use guidance, no exclusions, and no mention of alternative tools for other trigger types.

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 return contents and notes the call is '(free)', implying no credit or cost is incurred, which is genuine behavioral context. It does not state that it takes no arguments or that the catalog is static, so it stops short of full transparency.

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

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

A single front-loaded sentence that lists the payload without filler. Every clause carries information and nothing is padded.

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

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

With no output schema, the description must convey what comes back, and it does so by naming the four returned data categories. The phrase 'tool prices' is slightly ambiguous (cost per tool call versus asset prices), which is the one small gap for a zero-argument, annotation-free listing 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The schema confirms an empty object, so no additional parameter detail is required or missing.

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 (List) and enumerates the resources returned: supported symbols, timeframes, tool prices, and the payment network. That is far more informative than a tautology, but it does not distinguish itself from the sibling tools or explain why a trading agent would call this discovery endpoint rather than one of the analysis 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?

There is no explicit when-to-use guidance and no mention of alternatives among siblings such as get_market_regime or get_support_resistance. The only implied usage is that it is a lookup/discovery call, which the agent must infer on its own.

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