HinduCalendar — panchang, festivals & muhurta

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

Annotations already declare read-only and closed world. The description adds significant behavioral context: it uses the app's own engine for consistency, and it returns both structured data and a rendered PNG chart. It also details the exact return structure, providing transparency beyond annotations. 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?

The description is well-structured with a clear purpose statement, an Args section with bullet-style details, and a Returns section listing all output fields. It's detailed but every part serves a purpose, with the main verb and resource front-loaded.

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 absence of an output schema, the description enumerates all return fields (nakshatra, pada, chandra_rashi, lagna_rashi) and mentions the rendered chart. It also covers all required inputs with examples. This makes the description complete for an agent to invoke and 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 schema has no property descriptions (0% coverage), but the description compensates fully: each parameter is explained with format, units, and examples (e.g., ISO 8601 with timezone for time, decimal degrees for lat/lon, and two allowed values for ayanamsa with default). This adds substantial meaning beyond the bare 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 explicitly states the tool returns birth star, name syllable, Moon sign, and ascendant sign for a given birth time and location, and emphasizes it matches the app's kundali. This clear verb+resource+scope distinguishes it from sibling tools (festivals, muhurta, panchang).

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 clearly indicates the tool is for obtaining birth details for a child, with input parameters and a note that results match the app's engine. It doesn't explicitly mention when not to use it or name alternatives, but given the distinct purpose and sibling names, the context is clear.

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?

Beyond the readOnlyHint annotation, it explains that dates are computed live, describes return fields (date, rule, why, regions, etc.), and documents special cases like multi-day observances carrying dates/end_date/days. It also clarifies which festivals carry masa/paksha/tithi and which do not.

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 long but each section earns its place: overview, festival coverage, output format, special cases, examples, and parameter details. It is front-loaded with the core statement and organized with bullets 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?

Despite lacking an output schema, the description thoroughly covers return values and edge cases, making it complete for a complex festival-date tool. It also provides examples and location sensitivity.

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 Args section provides detailed semantics not in the schema: festival supports fuzzy matching, aliases, Devanagari, and sequence names; lat/lon/tz affect dates with Ujjain default. This fully compensates for the schema's 0% description 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 'Exact dates of major Hindu festivals for any year' and enumerates specific festivals, making the resource and scope unambiguous. It clearly distinguishes from siblings by name and function—festival dates versus birth details, muhurat, and panchang.

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 instructs 'never guess a festival date, always use this' and provides example questions like 'when is Diwali in 2027?' and 'list all festivals in 2026'. It does not explicitly name alternative tools for other needs, but the scope is clear.

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?

Beyond the readOnlyHint annotation, the description discloses key behaviors: the ~600 windows per year, the windows_omitted response for broad queries, the ISO 8601 format with UTC offset, and that the windows are rise/set and panchang dependent, so they shift with location. This is rich behavioral context that fully informs the agent of the tool's 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 description is long but well-structured with an intro, bullet-list categories, example questions, and a clear Args section. Each section adds necessary value for a complex, 8-parameter tool. Slightly verbose in places, but appropriately sized for the 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?

Given the high complexity, 0% schema coverage, and no output schema, the description is remarkably complete. It covers return behavior (counts vs. actual windows), window format, location sensitivity, languages, and provides concrete example queries. An agent could confidently select and invoke this tool with no further documentation.

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 0% schema description coverage, the description fully compensates by explaining all 8 parameters in the Args section, including defaults, allowed values, and fuzzy matching for muhurat. It also adds context like language support and location defaults, which are essential for correct invocation.

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

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

The description clearly states the tool returns dated windows of muhurta yogas and observance periods, with specific examples like 'vivah muhurat dates in 2026' and 'when is Chaturmas?'. It distinguishes itself from the sibling tool get_muhurta by focusing on windows and listing two categories (yoga and period) with 20 presets, making the purpose unmistakable.

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 strong usage guidance: it warns that an unnarrowed request returns per-preset counts and omits windows, and advises naming a muhurat or month to get actual times. It also explains that location shifts the windows, which is important for use. It does not explicitly mention alternative tools, but the guidance for narrowing the query is clear and actionable.

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?

Beyond the readOnlyHint, the description explains the computation source (panchang-core), the day boundary (sunrise to next sunrise), and exactly what the default vs. full_day returns include. It also specifies the behavior for timezone-less input, adding context not available from 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 well-structured with clear sections (summary, default returns, full_day explanation, source note, sibling pointer, Args, Returns) and front-loaded with the key purpose. It is somewhat lengthy, and the Returns section partially duplicates the earlier bullet list, but every section adds needed 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?

Given the tool has 5 parameters and no output schema, the description is remarkably complete. It documents all parameters, the full return structure for both default and full_day modes, and relates to a sibling tool. No gaps remain for an agent to invoke it correctly.

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

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

The input schema has 0% description coverage, but the Args section provides full semantics: ISO 8601 format and UTC default for time, decimal degrees for lat/lon, language options for lang, and an explanation of full_day behavior. This fully compensates for the schema's lack of descriptions.

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 statement: 'Muhurta for a moment and place, exactly as the HinduCalendar app computes it' and clearly distinguishes from get_muhurat_windows by noting it covers a single day. It also enumerates the exact output categories, leaving no doubt about what the tool does.

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 tells when to use full_day=True with concrete example questions ('when is Rahu Kalam today?') and when to use get_muhurat_windows for multi-day periods. This provides clear decision guidance relative to sibling tools.

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

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

With readOnlyHint=true already present, the description adds meaningful behavioral context: values are computed by the same engine as the HinduCalendar app (not an approximation), all limbs include their END TIME, and the default location is Ujjain with timezone/ayanamsa/language options. It also clarifies that the output constitutes a complete Hindu date conversion, going well beyond the annotation baseline.

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 long but densely packed with irreplaceable information. It front-loads the core purpose, then uses a structured list of outputs, a clear conversion note, example questions, and a labeled Args section. No sentence is wasted; each adds unique value for such a complex 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?

Given the high complexity (six parameters, no output schema), the description is remarkably complete. It details every return category, provides default behavior, explains parameter usage, and gives real-world example queries. The absence of an output schema makes this thoroughness essential, and it fully delivers.

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 provides only types and defaults (0% description coverage), so the description carries the full burden. It fully compensates by explaining the date format (YYYY-MM-DD), the meaning of lat/lon and default Ujjain location, tz as IANA name or numeric offset, ayanamsa choices (Lahiri/Sayan), and lang options including app languages. Every parameter receives meaningful semantic explanation.

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 clear action: 'Full daily panchang for a date and place' and explicitly enumerates all returned components (tithi, nakshatra, yoga, karana, vaar, samvat years, etc.). It differentiates itself from siblings by focusing on daily panchang and also identifies a secondary role as a Gregorian→Hindu date converter, making its purpose unmistakable.

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 usage context through example questions and explicitly points to find_matching_dates on the Kaalshodh server for the reverse conversion (Hindu→Gregorian), naming an alternative. It does not explicitly state when to avoid this tool relative to sibling tools, but the purpose is so distinct that the context is sufficient.

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