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Glama

get_tax_rules

Fetches YAML-driven tax rules for a given assessment year, including slabs, deduction caps, and holding periods, to validate Indian income-tax documents.

Instructions

Return the YAML-driven tax rules (slabs, deduction caps, holding periods) for an assessment year.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "assessment_year": "<assessment_year>",
      "rule_type": "<rule_type>"
    },
    "name": "get_tax_rules"
  }
}

Input Schema

NameRequiredDescriptionDefault
rule_typeYes
assessment_yearYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden. It conveys that the output is static configuration data (read-only by implication) sourced from YAML, but it says nothing about what happens for an unsupported assessment year or rule_type, whether results are cached/versioned, or whether any authentication or file access is required.

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

Conciseness4/5

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

One front-loaded sentence with the resource and the scope up front and no filler. It is appropriately sized, though the space saved could have been spent on rule_type semantics.

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

Completeness3/5

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

An output schema exists, so return structure needn't be explained, and a two-parameter retrieval tool is not complex. However, the complete absence of rule_type vocabulary leaves a real gap for an agent deciding how to invoke it.

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

Parameters2/5

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

Schema description coverage is 0% and neither parameter carries a description; rule_type has no enum or examples at all. The description never explains what valid rule_type values exist or what a rule_type selects, which is the single most important thing an agent needs to call this correctly. assessment_year's format is only covered by the schema pattern and example.

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

Purpose4/5

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

States a specific verb and resource ('Return the YAML-driven tax rules') and names the content categories (slabs, deduction caps, holding periods). This clearly distinguishes it from sibling compute_* tools, which calculate rather than retrieve rules. It stops short of 5 only because it doesn't name an alternative it competes with.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to call this versus compute_tax, compute_deductions, or compute_capital_gains, even though those siblings plainly depend on rule data. The agent must infer that this is the lookup step preceding computation. No exclusions or prerequisites are given.

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