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alternative_credit_score

Read-only

Estimate an alternative credit score for Kenyans lacking formal credit history using M-PESA behavioral signals.

Instructions

Estimate an alternative credit score from M-PESA behavioural signals. Western parallel: FICO score / Nova Credit for immigrants with no US history. Inputs are self-reported for demo purposes — a real implementation would connect to licensed M-PESA data-sharing APIs with customer consent. DEMO — not a real credit bureau product.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
months_as_mpesa_userYesHow many months the person has used M-PESA (0-240)
has_regular_income_depositsYesReceives regular deposits (salary, business income) at least twice monthly
pays_utilities_on_timeYesHas paid KPLC or water bills via M-PESA in past 6 months
has_savings_behaviourYesMakes regular small savings (M-Shwari, chama, SACCO, KCB M-PESA)
has_fuliza_debtYesCurrently has unpaid Fuliza (Safaricom overdraft) balance
has_multiple_income_streamsYesReceives income from more than one source (multiple employers, business + salary)
has_loan_default_historyYesHas defaulted on any previous loan (M-Shwari, KCB, bank, chama)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already provide readOnlyHint=true. The description adds context: inputs are self-reported, it's not a real product, and mentions the real implementation would require licensed APIs. This goes beyond annotations.

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?

The description is a few sentences, front-loaded with purpose. It is clear and without waste, though could be slightly more concise.

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

Completeness4/5

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

Given that an output schema exists, the description does not need to explain return values. It adequately covers the demo nature, input self-reporting, and data source considerations, making it complete for the context.

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

Parameters3/5

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

Schema coverage is 100% with all parameters documented. The description does not add extra parameter details beyond the schema, so baseline 3 is appropriate.

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 clearly states the tool estimates an alternative credit score from M-PESA behavioural signals, provides a Western parallel (FICO/Nova Credit), and distinguishes it as a demo. This is a specific verb+resource with useful context.

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 description implies use when needing an alternative credit score for M-PESA users, and explicitly notes it's a demo. It does not directly state when not to use or mention alternatives, but the clarity of purpose effectively guides usage.

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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