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join-swap-share-amount-out

Calculate token input needed to receive exact LP shares in Osmosis pools. Specify maximum token amount and get precise swap parameters for liquidity provision.

Instructions

Join pool by specifying exact LP shares to receive

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mnemonicYesBIP-39 mnemonic phrase for signing the transaction
poolIdYesPool ID to join
tokenInDenomYesDenomination of token to swap in
shareOutAmountYesExact LP shares to receive
tokenInMaxAmountYesMaximum token amount to swap in
gasNoGas limit (default: auto-estimate)
gasPriceNoGas price (default: 0.025uosmo)
memoNoTransaction memo
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It implies a write operation ('Join pool') but fails to mention critical behaviors: that it requires signing with a mnemonic (a security-sensitive action), involves swapping tokens (implied by 'swap' in the name but not explained), or has transaction costs (gas). The description is minimal and misses key operational context.

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 a single, focused sentence with zero wasted words. It front-loads the core purpose ('Join pool') and specifies the key constraint efficiently. Every word earns its place, making it easy to parse quickly.

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?

For a complex tool with 8 parameters (including sensitive ones like 'mnemonic'), no annotations, and no output schema, the description is inadequate. It doesn't cover the tool's behavior (e.g., transaction signing, swap mechanics), error conditions, or return values, leaving significant gaps for an AI agent to understand and invoke it correctly.

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 parameters are well-documented in the schema itself. The description adds no additional semantic context beyond restating 'exact LP shares to receive' (which matches the 'shareOutAmount' parameter description). It doesn't explain relationships between parameters (e.g., how 'tokenInMaxAmount' relates to 'shareOutAmount') or provide usage examples, so it meets the baseline but doesn't add value.

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 ('Join pool') and specifies the key constraint ('by specifying exact LP shares to receive'), which distinguishes it from generic pool-joining tools. However, it doesn't explicitly differentiate from its sibling 'join-swap-extern-amount-in' (which likely specifies token input amounts rather than shares), leaving room for improvement in sibling distinction.

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 like 'join-swap-extern-amount-in' or 'join-pool', nor does it mention prerequisites (e.g., needing a mnemonic for signing) or typical use cases (e.g., liquidity provision with precise share targets). This lack of contextual guidance could lead to misuse.

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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