I Ching MCP Server by RoxyAPI

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

With readOnlyHint=true and destructiveHint=false in annotations, the safety profile is already established. The description adds valuable behavioral detail beyond annotations: the three-coin methodology, line values 6-9, changing lines, and the return of both primary and transformed hexagrams. It is transparent about how the reading is produced and what is returned.

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 and front-loaded with the core purpose, followed by mechanics, return contents, and use cases. Every sentence contributes useful information without redundancy or marketing fluff. It is appropriately sized for the tool's 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?

There is no output schema, so the description compensates by clearly stating what the tool returns: primary hexagram, line values, and optional transformed hexagram. Parameter details are fully covered by the input schema, and annotations cover the read-only behavior. An agent has enough information to select and invoke the tool 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?

Schema description coverage is 100%, so the schema already documents lang, seed, and compact thoroughly. The description adds only a brief mention of seed reproducibility, but this largely duplicates the schema field description. Baseline 3 is appropriate because the description does not materially enrich parameter understanding.

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 generates an I-Ching reading via the three-coin casting method, which is distinct from sibling tools focused on hexagram lookup or random hexagram selection. It also specifies the output: primary hexagram, changing lines, and transformed hexagram. This is a specific verb-plus-resource definition with no ambiguity.

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 identifies clear contexts like divination apps, oracle features, and decision-making tools, and explains the casting method that distinguishes it from lookup-oriented siblings. It does not explicitly name alternatives or state when not to use the tool, so it falls short of full explicit 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered structurally. The description adds useful behavioral context: the result contains Chinese names, English translations, trigram compositions, and follows the traditional King Wen ordering. This goes beyond the schema and annotations by describing the catalog's organization and content.

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 first two sentences front-load the essential details: what is returned, what fields are included, and the ordering. The final sentence about 'profound wisdom' is a rhetorical flourish that does not help an agent select or invoke the tool, but it does not significantly bloat the description. Overall the description is compact and well-structured.

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 read-only catalog endpoint with complete schema documentation, the description covers the main expected content and ordering. There is no output schema, but the description names the key fields, and the query parameters are fully documented elsewhere. A slightly richer mention of pagination defaults would be nice, but it is not essential for correct 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%, so all four parameters (lang, limit, offset, compact) are already fully documented in the schema. The description adds no parameter-specific guidance beyond the high-level 'browse all' framing, which is acceptable given the schema's completeness. This is 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 states a specific verb ('Browse') and resource ('all 64 I-Ching hexagrams') and clearly distinguishes this catalog tool from sibling tools like get_iching_hexagrams_random or get_iching_hexagrams_lookup by emphasizing the complete set and King Wen ordering. The title and first sentence together make the tool's scope immediately obvious to an 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?

The intended use case is implied by 'Browse all 64' and 'catalog' — an agent can infer this is for listing the full catalog rather than fetching one hexagram or a random one. However, the description never explicitly says when to prefer this over siblings or when not to use it, so the guidance is implicit rather than stated.

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 description only needs to add meaningful behavior beyond that. It provides concrete examples showing that '111111' returns Hexagram 1 and '000000' returns Hexagram 2, clarifying the mapping. It does not describe the full return shape, but for a simple lookup this is a minor gap.

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 compact and front-loaded, stating the core action in the first sentence. The use-case guidance and examples are relevant and economical, with no filler or redundant claims.

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 read-only lookup tool with one required parameter, the description plus schema covers the essential calling context: input format, orientation, language option, and compact output. The main omission is a description of the expected response structure, but the examples and annotations keep this from being a significant gap.

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 all three parameters, including the line pattern semantics. The description repeats the bottom-to-top convention and adds examples, but does not add significant meaning beyond what the parameter descriptions already provide. 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 a specific verb and resource: 'Find an I-Ching hexagram by its binary line pattern.' It clearly distinguishes this tool from siblings by emphasizing binary line-pattern lookup rather than casting, numbering, or random selection. Examples further reinforce the intended operation.

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 says when to use it: 'for custom divination interfaces where users input their own line configurations, or to find hexagrams matching specific trigram combinations.' However, it does not name alternative sibling tools or state when those should be preferred instead.

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 description doesn't need to cover mutation safety. It adds useful payload context such as translations, judgment text, and changing line meanings, but it doesn't disclose further behavioral traits like error handling, language fallback behavior, or response size implications.

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 purposeful sentences. It front-loads the action and identifier, then enumerates the returned content and a use case. There is no filler, redundancy, or unnecessary 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 read-only detail endpoint with no output schema, the description explains the core input, enumerates the returned fields, and gives a concrete use case. It is slightly less complete in not explicitly positioning against related hexagram tools like random or lookup, but the schema and annotations cover the remaining essentials.

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 all parameters. The description reinforces the number parameter's range (1-64) but adds no new semantic meaning for lang or compact 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?

The description uses a specific verb and resource: 'Retrieve complete I-Ching hexagram details by King Wen sequence number (1-64)'. It clearly identifies the lookup key and gives a sense of the full response payload. It doesn't explicitly contrast with sibling tools like get_iching_hexagrams_lookup, but the 'by number' qualifier largely disambiguates it.

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 a concrete invocation context: 'Use this to display detailed hexagram information after casting or for educational reference.' This tells an agent when the tool is appropriate, but it doesn't name alternatives or exclusion conditions, leaving some routing decisions to inference.

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 the operation read-only and non-destructive. The description adds behaviorally relevant context: the call returns a random selection, not a query result, and includes judgment, image, domain interpretations, and all six changing-line meanings. It does not fully describe data shape, but the safety profile is covered by 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 short sentences: the first states the function, the second gives use cases, and the third details return content. No repetition of schema fields, 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?

With no output schema, the description usefully enumerates the returned categories. It is complete enough for an agent to invoke the tool with optional lang and compact; only exact field names and randomness details are absent, which are not required for a correct call.

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 description adds no parameter-specific detail. That is acceptable because lang and compact are fully documented in the schema with enums, defaults, examples, and behavior. 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?

Description opens with the specific operation: 'Receive a random I-Ching hexagram with full interpretation.' It names the resource (hexagram) and the distinguishing behavior (random), and enumerates the returned interpretation domains, so it is clearly separate from lookup, number, trigram, and cast siblings.

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 concrete contexts ('daily oracle features, meditation prompts, or exploring the Book of Changes') and the word 'random' implies use when no specific hexagram is intended. It does not explicitly name sibling tools or exclusion conditions, but the intended use 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that this returns the complete unfiltered set of all 8 trigrams, but it does not disclose response structure, ordering, or other behavioral details; the readOnly annotation lowers the burden somewhat.

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 focused sentences with the action and scope front-loaded in the first sentence. The enumerated trigram names and the hexagram context are useful and not redundant, though the middle sentence is slightly dense.

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 read-only catalog with no required parameters, the description is largely sufficient: it identifies the complete set, explains the domain relevance, and the schema documents the optional parameters. The lack of an output schema is a minor gap but acceptable given the simplicity of expected output.

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?

Input schema description coverage is 100%, with detailed descriptions for both lang and compact. The description does not add parameter-level meaning, but the schema already carries that load, 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?

States a specific verb and resource: 'Retrieve all 8 I-Ching trigrams (bagua)'. The description distinguishes this from hexagram tools by explicitly framing trigrams as the building blocks of hexagrams and enumerating all eight by name, leaving no ambiguity about scope.

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?

Provides contextual rationale ('Understanding trigrams is essential for interpreting hexagram meanings') but does not explicitly say when to choose this over sibling tools such as get_iching_trigrams_id or when not to use it. The usage context is implied rather than stated as a selection rule.

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 does add useful return-content expectations (Chinese name, pinyin, element associations, core attributes, symbolic meaning), but it doesn't disclose behavior for invalid IDs, case sensitivity, or how compact/lang alter the response beyond the schema. With annotation coverage, this is adequate but not rich.

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: the operation is front-loaded, the return contents are summarized, and the use case is placed at the end. Every sentence earns its place with no filler or 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?

For a low-complexity read-only lookup, the description covers purpose, lookup keys, returned content, and an example use case. The schema covers all parameters. It doesn't cover not-found behavior, but that is a minor gap for this simple 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 the schema fully documents id, lang, and compact. The description repeats the id's acceptable values but adds no new semantic detail beyond what the schema already provides, keeping this at the baseline.

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 verb ('Retrieve'), a specific resource ('a specific I-Ching trigram'), and the lookup keys (number or English name). It is clearly a detail-lookup tool, especially when contrasted with the plural sibling get_iching_trigrams, though it doesn't explicitly name that sibling.

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 a concrete use case: 'Use this to understand the component trigrams of any hexagram.' It provides clear context, but it doesn't explicitly state when not to use it or name alternative tools, so it stops short of 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?

Since there is no output schema, the description usefully discloses that the result includes judgment, image, and interpretations for love, career, decisions, and practical advice. It also explains deterministic seeded randomness, going beyond the readOnly/destructive annotations while not contradicting them.

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 compact and front-loaded with the core purpose, followed by deterministic behavior, use cases, and return contents. The closing phrase about ancient Chinese wisdom is somewhat decorative, but the overall description remains scannable and well ordered.

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 an optional-parameter, read-only oracle endpoint with no output schema, the description gives sufficient context: what the endpoint returns, how determinism works, and what use cases it fits. Language fallback and compact-shape details are left to the input schema, which already documents them fully.

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 input schema fully documents all four parameters and their defaults. The description restates the seed-determinism concept from the seed parameter but adds no new parameter-level meaning 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?

The description clearly identifies the resource: a daily I-Ching hexagram. It also adds the key behavioral distinction from random-reading tools by noting that the same seed and day produce the same hexagram. However, it never names a sibling alternative, so it is clear but not maximally differentiated.

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 when to use the tool through phrases like 'perfect for Hexagram of the Day features' and explains the deterministic seed behavior. It does not explicitly say when not to use it or point to alternatives such as get_iching_hexagrams_random or post_iching_daily_cast.

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 establish that this is read-only and non-destructive. The description adds meaningful behavioral context: traditional three-coin method, seeded randomness, determinism with same seed + date, and the presence of changing lines and transformation behavior. 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 compact, front-loaded with the core action, and each sentence earns its place: what it does, how it differs, determinism rule, and use case. There is no filler or 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?

For a tool with no output schema, the description usefully names the key return concepts: line values, changing line positions, and the resulting hexagram. Combined with fully documented optional parameters, this gives an agent enough to understand and invoke the tool correctly, though exact response shape is not specified.

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 100% parameter coverage with detailed descriptions, including the semantics of date, lang, seed, and compact. The description reinforces the seeded-determinism concept but does not substantially add new parameter-level meaning beyond what the schema already provides. 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 uses a specific verb ('Cast') and resource ('complete daily I-Ching reading'), then clarifies the differentiating details: line values, changing line positions, and the transformed hexagram. It also explicitly contrasts with 'the simple daily hexagram', making it easy to distinguish from sibling 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 clearly says this is for a full casting experience with authentic oracle details, and it contrasts with the simpler daily hexagram, implying a choice between this and sibling tools. It does not explicitly name sibling alternatives or state when not to use it, but the use-case guidance is clear enough.

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