Jeeva Jyotish

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

No annotations are provided, so the description carries the burden. It accurately describes the non-destructive read operation but does not mention error behavior (e.g., if slug is not found) or any other behavioral traits.

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 with no unnecessary words. Every sentence adds value: the first states the action and result, the second provides context for usage.

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 retrieval tool with two parameters and no output schema, the description covers the main points: what it retrieves, what data is included, and where to get the input. It does not mention error cases or optional parameters, but is generally 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?

Schema coverage is 50% (only locale has a description). The description does not explain the locale parameter or its effect on the response. For a required parameter, more detail would be helpful.

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 'Fetch', the resource 'full reference record for a factor by its slug', and specifies the included data (effects and source.url). It also distinguishes from siblings by indicating that slugs come from 'search_effects' or 'lookup_combination'.

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 explains when to use this tool: after slugs are obtained from 'search_effects' or 'lookup_combination'. It provides clear context but does not explicitly state when not to use or mention alternatives.

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?

Describes what the tool returns (factors, effects, source citation) and implies read-only behavior via 'Fetch'. No annotations provided, so description carries the burden; it adequately discloses core behavior but lacks specifics on idempotency or caching.

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 front-loads the purpose and includes examples. Slightly run-on with dashes, but no unnecessary words. Efficient for the information conveyed.

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 (2 parameters, no output schema), the description sufficiently explains the return structure and key components. Lacks discussion of error conditions or limitations, but adequate for a straightforward fetch 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?

Provides a concrete example for the slug parameter, adding meaning beyond the schema. However, the locale parameter is not mentioned in the description, and schema coverage is 50%. The description partially compensates for the undocumented slug but does not cover locale.

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?

Clearly states it fetches a full reference record for a per-lagna placement by slug, with specific examples and included components. Distinguishes from sibling tools like 'get_factor' and 'get_yoga' by focusing on placement records.

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?

Implied usage context (fetching a placement record) but no explicit when-to-use or when-not-to-use guidance. Does not mention alternatives like 'lookup_combination' or 'search_effects', leaving the agent to infer appropriateness.

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 carries the full burden. It clearly states that the tool returns component factors, effects, and a citation, which is appropriate for a read operation. No contradictions or hidden behaviors are indicated.

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 concise sentence that is front-loaded with the key action and resource. It wastes no words and is easy to parse.

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 lack of an output schema, the description adequately explains what the tool returns (component factors, effects, citation). For a fetch operation, it is complete enough, though additional context about what a 'yoga' is might be helpful but not necessary.

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 description adds meaning to the 'slug' parameter by stating it is used to identify the yoga. However, it does not mention the 'locale' parameter, which is described in the schema. With 50% schema description coverage, the description partially compensates but is not fully comprehensive.

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 it fetches a full reference record for a named yoga by slug, including component factors, effects, and citation. It distinguishes from siblings (e.g., get_factor, search_effects) by specifying the scope and detail of the returned data.

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 fetching a yoga record but does not explicitly state when to use this tool versus siblings like lookup_combination or search_effects. No alternatives or exclusions are mentioned.

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 bears the full burden. It accurately describes a read-only listing operation with no side effects. However, it does not explicitly confirm idempotency or lack of mutations, and it omits any mention of return format or potential delays.

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 sentence (12 words) that immediately conveys the tool's purpose. It front-loads the verb 'List' and specifies the exact count (14) and context (Jyotish). No extraneous information.

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 (no parameters, no output schema, trivial operation), the description is nearly complete. It tells the agent exactly what is returned—a list of 14 life domains. It could clarify the output format (e.g., names, IDs) but is sufficient for selection.

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 has zero parameters, so the schema coverage is trivially 100%. According to the guidelines, 0 parameters earns a baseline of 4. The description adds no parameter details, but none are needed.

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's action ('List') and the specific resource ('the 14 Jyotish life domains the effects are organised by'). This is unambiguous and distinguishes it from sibling tools like get_factor or search_effects, which perform different tasks.

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 no guidance on when to use this tool versus alternatives. It merely states what it does without mentioning prerequisites, when to prefer it, or when not to use it. Siblings exist but are not referenced.

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 must bear the full burden of behavioral transparency. It mentions returning 'matching factor(s) and their effects, with citations,' which implies a read-only operation. However, it does not explicitly state that the tool is non-destructive or disclose any other behavioral traits (e.g., rate limits, authentication needs). Given the lack of annotations, more clarity would improve 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?

The description is extremely concise: two sentences that front-load the main verb and resource. Every word carries weight, with no redundancy or extraneous information.

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 and the presence of an example, the description is mostly complete. It covers the operation, required parameters, and return content. However, without an output schema, it would be helpful to describe the return structure more explicitly (e.g., format of citations).

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 description adds significant context beyond the schema: it clarifies that graha is required and exactly one of bhava, rashi, or nakshatra must be provided, and it gives the range for bhava (1-12). Schema description coverage is only 20% (only locale has a description), so the description compensates well. However, it does not explain the meaning of each enum value.

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's purpose: looking up what a specific placement means, with examples (e.g., Mars in 7th house) and specifying required parameters (graha and one of bhava/rashi/nakshatra). It distinguishes itself from sibling tools by focusing on combination lookups.

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 explicit usage guidance: 'Provide a graha and exactly one of bhava (1-12), rashi or nakshatra.' This tells the user how to call the tool correctly. However, it does not mention when to prefer this tool over siblings like get_placement, so not 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?

With no annotations provided, the description carries the burden. It discloses the return structure (ranked effects, domain, weighting, citation) and multi-language support. Does not explicitly state read-only nature or potential rate limits, but as a search tool the behavioral profile is mostly clear.

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 core action and outputs, followed by a necessary usage instruction. 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 4 parameters and no output schema, the description adequately covers the tool's purpose, input types, and key return fields (ranked effects, weighting, citation). Could optionally detail pagination or ordering, but the essentials are present.

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 adds context about the corpus and citation requirement but doesn't enhance parameter understanding beyond what the schema already provides (e.g., 'default 10' for limit, 'restrict to one domain' for domain).

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 searches a specific corpus (Jeeva Jyotish) by keyword or question, returns ranked effects with domain, weighting, and citation. This verb+resource definition is distinct from sibling tools that handle factors, placements, yogas, etc.

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?

Explicitly states when to use: for searching effects by keyword/question. Provides a 'must do' instruction about citing the source. Lacks explicit exclusions or comparisons to siblings, but the context of search vs. direct lookups is implied.

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