Astrology Forecast MCP Server by RoxyAPI

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

Annotations already declare readOnlyHint=true and destructiveHint=false. Beyond that, the description adds behavioral detail by explaining the output shape (four windows, count breakdowns, top events) and the summarization behavior, which is consistent with the read-only annotation. No contradiction.

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

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

Three concise, front-loaded sentences: what it does, what it returns, and when to use it. Every sentence earns its place with no redundant 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?

Despite having 8 params, nested objects, and no output schema, the description sufficiently summarizes the return structure (event count, domain/type breakdowns, top events) and its purpose. It could be more explicit about response shape edge cases, but it is complete enough for an agent to decide when to invoke it.

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

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

Schema description coverage is 100%, with each parameter (top, lang, compact, domains, birthData, startDate, domainWeights, minSignificance) already richly described. The tool description adds no extra parameter-level semantics, 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?

The description clearly states the action ('Roll the cross-domain forecast... into four pre-summarized windows') with a specific resource (single birth subject) and output (event count, breakdowns, top events). The use case 'glanceable what-is-coming strip' sets it apart from the sibling timeline/transit 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 tells when to use it ('for a glanceable what-is-coming strip... without scanning the full event list') and implies when not to (when full details are needed). However, it does not explicitly name alternative sibling tools, so it earns a 4 rather than 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?

Annotations already mark the tool as read-only and non-destructive. The description adds meaningful behavior: it filters to high-significance events, defaults to a floor of 70, and explains the output is a short list of meaningful dates. No contradiction with annotations.

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 two sentences, front-loaded with the core purpose, and contains no redundant wording. 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?

The description explains what events are included, the default filter, and intended use. It does not describe the response shape, but the tool is a straightforward filtered list and the schema already documents date-range defaults and language options, making it complete enough for the tool's complexity.

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

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

Schema coverage is 100% and each parameter has a detailed description, so the baseline is 3. The description reinforces the meaning of minSignificance (significance floor) and domains (outer-planet, Vimshottari), but does not add new syntax details beyond schema.

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

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

The description opens with 'Return only the high-significance dates from the merged cross-domain forecast for a single birth subject' and enumerates specific event types (outer-planet exact transit aspects, sign ingresses, retrograde stations, dasha changes), clearly distinguishing it from broader forecast tools like post_forecast_timeline or post_forecast_transits.

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 'Built for what-is-coming highlights, timing alerts, and at-a-glance forecast strips,' providing clear usage context. The default significance floor of 70 implies use when a short, focused list is desired, but it stops short of explicitly naming alternatives or when-not-to-use scenarios.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: it explains the chart is erected for the exact Sun return moment, that it is location-sensitive, that houses and Ascendant shift when relocated, and lists the output contents. This goes well beyond the annotations.

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, information-dense, with no fluff. The first sentence states the core action; the second details the return payload; the third covers location sensitivity and use cases. 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?

With no output schema, the description explains what the chart contains: planetary positions, house cusps, aspects, Ascendant, and Midheaven. It covers purpose, location flexibility, and typical consumers. For a 9-parameter tool with a rich schema, this is a complete and self-contained description.

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 detailed field-level descriptions. The description reinforces the meaning of latitude/longitude via the birthplace-vs-current-city guidance, but this is already covered in the schema. Baseline 3 applies; no additional parameter semantics are needed beyond the schema's thorough coverage.

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 opens with a strong verb-resource pair: 'Cast the solar return chart for one subject and year' and specifies the exact astronomical event. It clearly distinguishes itself from sibling tools like transits or timeline by naming the solar return technique and its 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 closing sentence explicitly states intended use cases: 'Built for year-ahead forecast tools, birthday charts, and annual horoscope features.' It also gives guidance on location choice (birthplace vs. current city) but does not explicitly contrast with sibling tools or say when not to use this 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond the annotations: 'The window is clamped to 90 days and events are capped and scored by significance.' This discloses constraints on the operation that are not in the annotations, though it does not go into details like scoring exact algorithm or cap thresholds.

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

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

The description is three sentences, with the most important action verb front-loaded. Every sentence earns its place: purpose, constraints, and use cases. There is no fluff or repetition of schema details, making it dense but highly scannable.

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 complexity (8 parameters, nested birthData, no output schema), the description provides a solid conceptual overview and key constraints. However, the absence of an output schema means the description should describe the response shape more explicitly; it only vaguely promises a 'time-ordered forecast' of 'events.' This is a clear gap for an agent deciding whether to invoke the tool and how to interpret results.

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

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

The input schema covers 100% of parameters with rich descriptions, so the baseline is 3. The description does not add additional parameter-level meaning; it only summarizes domains at a high level. This is acceptable because the schema already does the heavy lifting for language, dates, domains, birth data, and significance controls.

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 opens with a specific verb and resource: 'Build one time-ordered forecast for a single birth subject by merging upcoming events across three domains.' It enumerates the exact event types (transit aspects, ingresses, stations, eclipses, lunar phases, biorhythm critical days, and vedic dasha boundaries), which clearly differentiates it from siblings like post_forecast_transits or post_forecast_solar_return.

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

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

The description explicitly names target use cases: 'Built for what-is-coming dashboards, daily and weekly forecast feeds, and timing tools.' It implies the tool is the right choice when a merged, cross-domain timeline is needed, but it does not explicitly contrast it with sibling tools or state when not to use it, so it falls one step short of full 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?

Annotations declare readOnlyHint=true and destructiveHint=false, and the description adds behavioral context: a 90-day maximum window, exact instants for aspects, and a time-ordered, significance-scored timeline. It also specifies 'single birth chart' as a constraint not evident from annotations. No contradiction with the safety hints.

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 two sentences, front-loaded with the primary action and resource. The first sentence enumerates event types concisely, and the second states the output and use case. No wasted words.

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

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

Given the complexity (6 parameters, nested objects, no output schema), the description provides a solid high-level overview: what events are included, the return shape ('time-ordered, significance-scored timeline'), and the applicability. It lacks exact output field details, but the schema covers parameters well, and the description is sufficient for selection and initial 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%, with all six parameters clearly documented in the input schema. The description adds minimal parameter-specific meaning beyond aligning with 'birthData' and 'startDate/endDate' via 'single birth chart' and 'window up to 90 days', which is already in the schema. 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 tool forecasts western astrology events for a single birth chart over a 90-day window, enumerating specific event types (aspects, ingresses, stations, eclipses, moon phases). This distinguishes it from siblings like post_forecast_timeline or post_forecast_solar_return by its focus on transit events with refined timing and a scored timeline.

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

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

The description provides clear intended use cases: 'Built for astrology forecast feeds, transit alerts, and timing tools.' However, it does not explicitly say when to prefer this over sibling tools like post_forecast_digest or post_forecast_timeline, so it stops short of explicit alternatives.

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