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albeorla

financial-agent

by albeorla

detect_drift

Detects evidence-backed drift in financial obligations, such as missing payments, stale estimates, amount discrepancies, and unexpected charges, ordered by severity.

Instructions

Detect evidence-backed drift findings, ordered by severity.

Finds missing expected obligations (past due, no matching transaction), stale estimates (review date passed), amount changes (charge happened but differs materially), and unexpected recurring charges (discovered by onboarding but not yet modeled). Deterministic and idempotent. When persist is true, findings are upserted and disappeared ones marked resolved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_of_dateYes
optionsNo
persistNo
db_pathNo
Behavior4/5

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

The description discloses key behavioral traits: determinism, idempotency, ordering by severity, and persistence behavior ('findings are upserted and disappeared ones marked resolved'). Since no annotations are provided, the description compensates well. However, it does not specify the return format (e.g., list of objects) or effects when persist is false.

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 concise (5 short sentences) and front-loads the main purpose. It avoids unnecessary words. Minor improvement could be to structure parameter explanations separately, but current form is efficient.

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?

The description covers the purpose, drift types, and key behavioral aspects. However, missing parameter semantics, no output schema, and lack of usage guidance leave completeness gaps. For a tool with four parameters and complex behavior, more context is needed.

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?

The description mentions only the 'persist' parameter and its effect. With 0% schema coverage, the description must explain all four parameters but fails to clarify 'as_of_date', 'options', and 'db_path'. It adds no meaning for three out of four parameters.

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?

The description clearly states the tool detects 'evidence-backed drift findings' and lists specific types of drift. It uses a specific verb-resource combination ('detect drift findings'). However, it does not explicitly contrast with sibling tools like 'list_drift_findings' to make the distinction obvious, though the purpose is otherwise clear.

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?

The description implies when to use (to find drift) but provides no explicit guidance on when not to use or alternatives. It notes the tool is 'Deterministic and idempotent', which advises repeated use is safe, but does not compare to any sibling tools (e.g., when to use 'apply_guardrail_rules' instead).

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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