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IFSC check (India)

ifsc_check
Read-onlyIdempotent

Validate an Indian IFSC by RBI structure (BBBB0NNNNNN; 5th character always 0).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ifscYes11-character Indian Financial System Code.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolNo
scopeNo
validYes
reasonYes
countryNo
normalizedNo

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds genuinely useful behavioral context beyond annotations: the exact structural rule applied (11 characters, 5th character forced to 0, BBBB0NNNNNN pattern), which tells the agent precisely what criterion 'validates' means here. 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.

Conciseness5/5

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

A single sentence with zero filler: verb first, resource second, the decisive format rule third. Every element earns its place and the most decision-relevant detail (the 0 requirement) is included without bloating the text.

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

Completeness5/5

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

For a single-required-parameter validator with an output schema and safety annotations, the description is complete. The agent has everything needed to invoke it correctly: one fully documented parameter, the validation rule, and read-only/idempotent behavior from annotations. Return-value details are the output schema's job, and nothing relevant is missing.

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

Parameters4/5

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

Schema coverage is 100%, giving a baseline of 3. The description adds meaning beyond the schema's '11-character Indian Financial System Code' by specifying the positional structure (BBBB0NNNNNN and the 5th-character-is-0 rule), which is material validation knowledge an agent would not infer from the schema alone.

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

Purpose5/5

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

The description uses a specific verb ('Validate') plus a clearly bounded resource ('Indian IFSC') and the governing standard ('RBI structure'). The format hint (BBBB0NNNNNN; 5th character always 0) removes any ambiguity. It differentiates cleanly from sibling format validators like iban_check, swift_bic_check, and aba_routing_check, since it is explicitly scoped to India's IFSC.

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

Usage Guidelines4/5

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

The 'Indian IFSC' qualifier gives clear selection context: this is the tool for Indian IFSC validation, distinct from the sibling checks for other instruments and jurisdictions. It does not explicitly name alternatives or state when-not-to-use (e.g., 'for SWIFT/BIC use swift_bic_check'), so it stops short of full routing guidance.

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

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TDQS

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct identifier type or data source: every checksum validation is for a specific standard (IBAN, LEI, VAT, etc.), and the on-chain and rental tools are clearly separate domains. There is no ambiguity between tools; even similar-sounding checks like 'luhn_check' and 'ean13_check' are distinct algorithms with explicit descriptions.

Naming Consistency3/5

Most validation tools follow a 'X_check' pattern (iban_check, swift_bic_check, ein_format_check), but others deviate: 'company_number_format' uses a noun_noun structure, 'block_info' is noun_noun, and 'batch_validate' and 'context_distill' use verbs. While the pattern is not uniform, the names are readable and the convention is understandable, just not fully consistent.

Tool Count2/5

With 28 tools, this server exceeds the typical 3-15 well-scoped range and even the 16-25 heavy range. The server covers multiple unrelated domains (identifier validation, blockchain queries, rental fraud, text processing), which inflates the count. While each tool is individually justified, the overall surface feels overly broad for a single MCP server.

Completeness4/5

For each sub-domain, coverage is strong: identifier validation includes a wide range of international standards, on-chain queries cover balances, activity, and settlement history, and rental tools provide risk, verdict, and deposit guard. Minor gaps exist (e.g., no country-specific tax IDs beyond what's listed, no transaction history for arbitrary tokens), but the visible coverage is comprehensive for the stated purposes.

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