Get Ayurdaya (longevity) estimates — EXPERIMENTAL, not for predictive use.
The engine computes Pindayu and Nisargayu, but flags the whole section
experimental: the classical methods are textually divergent and the
reduction rules are only partially applied. The disclaimer is returned with
the numbers and must be passed on to the reader, not dropped.
Do not present these as a lifespan prediction.
| Name | Required | Description | Default |
|---|---|---|---|
| chart_id | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden, and it does so thoroughly. It discloses that the methods are textually divergent, reduction rules are only partially applied, and the disclaimer must be propagated to the reader—important behavioral context beyond the simple 'get' verb.
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-loads the most critical warning ('EXPERIMENTAL, not for predictive use'), and each sentence adds meaningful information. The structure moves from purpose to limitations to a hard usage rule without 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 single-parameter tool with no output schema, the description covers the key behavior, return contents (Pindayu, Nisargayu, disclaimer), and cautions. It could be slightly more complete by describing the expected return shape or chart_id provenance, but overall it gives enough context 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 0%, and the description does not mention chart_id at all. The only clue is the parameter name itself, which is reasonably self-explanatory, but the description fails to compensate for the missing schema documentation by explaining how to obtain or use chart_id.
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-resource pair: 'Get Ayurdaya (longevity) estimates.' It further clarifies the two computed values (Pindayu and Nisargayu) and immediately flags the experimental nature, making it easy to distinguish from the many sibling get_* 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 gives clear usage context: this tool returns experimental longevity estimates and must not be used or presented as a predictive lifespan. It does not name an alternative sibling, but it provides strong exclusionary guidance ('Do not present these as a lifespan prediction') and instructs the caller to pass on the disclaimer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool targets a distinct astrological subsystem — positions, houses, aspects, strengths, dashas, transits, yogas, doshas, vargas, karakas, etc. The pairs that could plausibly be confused (calculate_birth_star vs create_chart, get_current_dasha vs get_dasha_periods, get_timeline vs get_transits) are explicitly cross-referenced with guidance on when to use which, so an agent can disambiguate reliably.
24 of 30 tools follow a uniform get_X pattern, and the remaining action tools (create_chart, calculate_birth_star, describe_chart, rectify_birth_time) still use verb_noun. Only health_check and server_stats break the pattern as noun-style names, and the different verbs reflect genuinely different actions rather than inconsistency.
30 tools is on the heavy side and exceeds the comfortable range, even though Vedic astrology is a genuinely broad domain with many distinct subsystems. Some tools are meta or adjacent (get_account_status, health_check, server_stats, get_prompt_library, get_numerology) and a couple could arguably be consolidated (get_current_dasha as a mode of get_dasha_periods), but each tool does carve out a distinct purpose.
The chart lifecycle is fully covered: create_chart produces a cached handle, describe_chart inventories it, and the get_* readers retrieve every section. Timing (dashas, transits, timeline), strengths (shadbala, vimsopaka), yogas, doshas, vargas, compatibility, rectification, and even meta-concerns (account status, health) are all present with no obvious dead ends or missing operations for a computation-cache domain.