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mansanitizer

Fabits MCP Server

by mansanitizer

fabits_redeem

Sell mutual fund units from your Fabits portfolio. Specify fund ID and units or amount for partial or full redemption.

Instructions

Redeem (sell) mutual fund units.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idYesUnique identifier for the user (e.g., WhatsApp phone number). REQUIRED for all requests to maintain user session state.
fund_idYesFund ID to redeem from
unitsNoNumber of units to redeem (for partial redemption)
amountNoAmount to redeem in rupees (alternative to units)
redemption_typeNoType of redemption (default: PARTIAL)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('redeem/sell') but lacks critical details: it doesn't specify if this is a financial transaction with irreversible effects, mention authentication requirements (implied by user_id), discuss rate limits, or describe the expected outcome (e.g., confirmation, funds transfer). This is inadequate for a mutation tool with zero annotation coverage.

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?

The description is extremely concise—a single, clear sentence that states the core purpose without any fluff. It's front-loaded with the essential action and resource, making it efficient and easy to parse. Every word earns its place.

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

Completeness2/5

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

Given the complexity of a financial redemption tool with no annotations and no output schema, the description is incomplete. It fails to address behavioral aspects (e.g., transaction finality, error handling), usage context, or expected results. For a 5-parameter mutation tool in a financial domain, this leaves significant gaps for an AI agent to operate safely and effectively.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't clarify the relationship between 'units' and 'amount' as alternatives). With high schema coverage, the baseline score of 3 is appropriate as the description provides minimal value over structured data.

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 action ('redeem/sell') and resource ('mutual fund units'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this from sibling tools like 'fabits_cancel_sip' or 'fabits_get_portfolio', which also involve fund operations but serve different purposes.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing existing holdings), exclusions (e.g., not for SIPs), or compare to siblings like 'fabits_invest_lumpsum' for opposite actions. Usage is implied but not explicitly stated.

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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