chronosync-mcp

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

Describes core batch conversion behavior, but with no annotations, missing details on output format, error handling, or limits (e.g., max timezones). Adequate but has gaps.

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 succinct sentences with front-loaded comparison. 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?

While input is well-specified, absence of output schema and any description of return structure leaves agents guessing about result format. Lacks completeness for a batch operation.

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 has 100% description coverage; description does not add extra meaning beyond what schema already provides. Baseline score 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?

Description clearly states it converts a single instant into many target timezones, distinguishing it from sibling convert_timezone. The 'world-clock views' example reinforces 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?

Implicitly contrasts with convert_timezone and suggests use case ('Ideal for world-clock views'), but does not explicitly state when not to use or mention alternatives beyond the sibling comparison.

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 explains input formats and output fields but does not disclose side effects (likely none), error handling, or limits. The behavior is adequately described for a read-only conversion, but no explicit mention of non-destructive nature.

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?

Single sentence that is efficient, well-ordered (input, then output), and front-loaded with the core action. Every word adds value; no 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?

Despite no output schema, the description explains the return values (converted datetime, offset, abbreviation, DST flag). It covers essential aspects for a simple conversion tool. Could mention that the output format is ISO 8601 or similar, but not critical.

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 description adds meaningful detail beyond the schema: it provides examples of natural language ('next Tuesday 3pm') and clarifies the datetime parameter's flexibility. This helps an agent understand valid inputs better than the schema alone.

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 converts a date/time from one IANA timezone to another, specifies accepted input formats (ISO 8601 or natural language), and lists output fields (converted datetime, offset, abbreviation, DST flag). This distinguishes it from sibling tools like now_in or tz_offset.

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?

No guidance on when to use this tool over alternatives. For example, it does not mention that list_timezones can be used to find valid timezone names or that convert_batch is for multiple conversions. The description lacks context about prerequisites or 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?

The description discloses key behaviors like DST handling ('days are calendar-based, hours/minutes are absolute') and the two operation modes, but lacks details on error handling, return format, or edge cases. With no annotations, this is moderately transparent.

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 well-formed sentence that front-loads the main purpose, making it efficient. However, it could benefit from slight restructuring for clarity on the two modes.

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 nested operation object and two modes, the description covers the core functionality but omits output format and details about diff result (e.g., units returned). No output schema further increases the burden, so completeness is moderate.

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 does not add extra semantics beyond the schema parameters; it only summarizes overall functionality.

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 performs addition/subtraction with DST awareness and difference computation between datetimes, distinguishing it from siblings like convert_timezone or find_meeting_slots.

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 implies usage for date arithmetic with DST, but does not explicitly state when to use this tool versus alternatives such as convert_timezone for simple zone conversions or list_timezones for listing.

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 provided, so the description must disclose behaviors. It mentions weekend and holiday exclusion but does not explain ranking, output format, or default working hours, leaving some behavioral aspects opaque.

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

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

Two sentences efficiently convey the core functionality and key exclusions without any fluff.

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 tool lacks an output schema, and the description omits details like default working hours, limit default, and ranking criteria, making it somewhat incomplete for a moderate-complexity 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 75% for top-level parameters. The description adds context about the country field for holidays, but does not fully compensate for the missing participants property description.

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 suggests the best overlapping working-hour slots for meetings across timezones, and distinguishes from sibling tools like convert_timezone or is_holiday by focusing on meeting scheduling.

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 implies usage for finding meeting slots and mentions holiday exclusion with country code, but lacks explicit contrast with alternative tools or when-not-to-use guidance.

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

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

No annotations exist, so the description carries full burden. It discloses the data source (Nager.Date) but omits details like whether regional holidays are included, rate limits, or what happens for invalid input. More behavioral context would be helpful.

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 of 18 words that front-loads the purpose and key details. Every word earns its place, with no redundancy or 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?

For a simple boolean check with two well-documented parameters, the description is nearly complete. It could explicitly state the output (boolean) but overall provides sufficient context for an agent to understand and invoke the tool.

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

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

Schema description coverage is 100%, so baseline is 3. The tool description adds no additional meaning beyond the schema's parameter descriptions, which already define 'date' and 'country_code' with formats and examples.

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 uses a specific verb ('Check') and resource ('public holiday') and clearly distinguishes from sibling tools like convert_timezone or date_math by specifying the exact functionality and data source (Nager.Date).

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 states the tool's purpose but provides no explicit guidance on when to use it versus alternatives, nor any exclusions or prerequisites. While sibling tools are different, no direct comparison or selection criteria are given.

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

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

No annotations provided. The description indicates a read-only operation but does not disclose default behavior (e.g., returns all timezones if no query), pagination, or rate limits. Basic transparency is present.

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, front-loaded sentence with no wasted words. It conveys the core purpose and usage efficiently.

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

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

For a simple tool with one optional parameter and no output schema, the description is largely complete. It could mention default behavior when query is omitted, but overall it provides sufficient context for an agent.

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 single parameter 'query' has 100% schema coverage with a description. The tool's description adds concrete examples ('kolkata', 'america') and clarifies the filter is by substring, adding value beyond the schema's minimal description.

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 lists or searches IANA timezone names with a specific verb ('List or search') and resource ('IANA timezone names'). It also mentions filtering capability, distinguishing it from sibling tools like convert_timezone or lookup_timezone.

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 implies usage for finding timezones by location substring with examples, but does not explicitly state when to use this versus alternatives like lookup_timezone, nor does it mention when not to use it.

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 bears full responsibility for behavioral disclosure. It mentions resolving to 'timezone(s)' implying possible multiple results, but does not clarify handling of ambiguous or no-match cases, nor any side effects or prerequisites. For a read-only resolution tool, this is minimally adequate but could be improved.

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 with no wasted words. The first states the purpose and benefit, the second provides a clear example. 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?

Given the tool's simplicity (1 required parameter, no output schema), the description is mostly complete. However, it lacks information about the return format (e.g., string or array of strings) which would be helpful since no output schema is provided. Still, it's sufficient for basic understanding.

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%, providing baseline 3. The description adds value by giving a concrete example ('Delhi' -> Asia/Kolkata), which clarifies usage and expected input format beyond the schema's 'City or country name, or ISO country code.'

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 verb 'resolve' and resource 'city or country name to IANA timezone(s)', solving the problem of not needing the exact identifier. The example 'Delhi -> Asia/Kolkata' reinforces the purpose and distinguishes it from sibling tools that convert, list, or compute timezone offsets.

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 implies use when you have a city/country name instead of an exact timezone identifier. However, it does not explicitly state when not to use it (e.g., if you already have the IANA timezone) or mention alternative tools like list_timezones for listing all timezones. The context is clear but lacks explicit exclusions.

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

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

With no annotations, the description carries the full burden. It clearly states the output includes local time, UTC offset, abbreviation, and DST flag, which are all behavioral aspects. It does not mention any side effects or prerequisites, but for a simple read-only tool, this is sufficient. A minor gap is not specifying the output format (e.g., string vs object), but it's still transparent.

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 short sentences, front-loading the purpose and ending with a usage tip. Every word earns its place with no redundancy. Highly concise.

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 (one parameter, no output schema, no annotations), the description covers the core functionality and return values. It lacks explicit mention of output structure (e.g., JSON object fields), but the listed components (offset, abbreviation, DST flag) provide enough context. For a tool of this complexity, it is nearly 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?

The input schema already provides a description for the only parameter 'timezone' with examples. The tool description reinforces that it uses an IANA timezone but does not add new semantic meaning beyond the schema. With 100% schema coverage, 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 explicitly states it returns 'current local time in an IANA timezone, with UTC offset, abbreviation and DST flag', which is a specific verb+resource. It clearly distinguishes from sibling tools like 'convert_timezone' (which converts a specific datetime) and 'list_timezones'.

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 ends with 'Use whenever you need to know "now"', which provides a clear usage context. However, it does not explicitly mention when not to use the tool or name alternatives, leaving the agent to infer from sibling names.

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 provided, so description carries burden. It mentions DST awareness and fractional offsets, but does not disclose error handling, default behavior for missing instant, or any limitations.

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 efficient sentences, front-loaded with key information. No redundancy or fluff.

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?

Adequate for a simple tool with two parameters, but missing description of output format (e.g., returns offset string like '+05:30'). Could mention return type.

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 covers 100% of parameters with descriptions. Description adds context like 'defaults to now' and 'IANA timezone', but does not significantly extend 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?

Description clearly states the tool returns exact UTC offset for a timezone at a given instant, with DST awareness and support for fractional offsets. This distinguishes it from siblings like convert_timezone or now_in.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies usage for offset queries at specific instants but lacks when-not-to-use or comparisons.

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