loomdesk

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only describes what data the book contains rather than how the tool behaves. It does not state whether the data is a live snapshot, whether calling is read-only, whether permissions are needed, or what the response format is. The only behavioral hint is the daily 18:00 UTC payout timing embedded in the content list.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The entire description is a single front-loaded sentence that names the resource first and then lists its key components in one breath. There is no filler, repetition, or buried context. It is compact while preserving the important 18:00 UTC payout detail.

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

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

For a no-parameter, no-output-schema status tool, the description covers the main informational needs: what the book is, what components it reports on, and the payout schedule. It does not describe the response structure or format, but that is less critical given the simple nature of the tool. The main missing piece is usage/selection context, which is already accounted for under usage_guidelines.

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

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

The tool has zero parameters, so there are no parameter semantics to document. The schema is empty and the description appropriately focuses on what data the tool exposes. This exceeds the baseline for a no-parameter tool because it clarifies the meaning of the returned status components.

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

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

The description identifies the resource precisely as the protocol-owned liquidity book and enumerates its contents: value, positions, fees collected, pending payout, and paid LOOM. This clearly differentiates it from sibling tools like my_positions and list_pools. It lacks an explicit action verb such as 'get' or 'list', but the tool name and title make the status semantics reasonably clear.

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

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

The description gives no guidance on when to use this tool instead of get_pool, list_pools, my_positions, or quote_position. It does not state prerequisites, exclusions, or a recommended selection path. An agent must infer from the resource name that this is the protocol-level book view.

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

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

With no annotations, the description carries the behavioral disclosure burden. It provides meaningful selection behavior: a symbol resolves to LoomDesk's own pool if available, otherwise the deepest pool, and a pool id can be passed directly. It does not mention failure modes or return format, but for a read-style getter the key behavioral nuances are disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The entire description is one dense sentence that packs the core purpose, the differentiator from list_pools, and the accepted identifier forms. It is front-loaded with the most important information and contains no filler or repeated schema details.

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

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

For a single-argument getter with no output schema, the description is largely sufficient: it names the target, the accepted inputs, and the added value over list_pools. Minor gaps remain, such as what 'deepest' precisely means and the schema's additional 'address' form, but these do not prevent an agent from invoking the tool correctly.

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

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

The schema already covers the parameter well with 100% coverage, describing it as a stock symbol or pool id/address. The description adds value beyond the schema by explaining the symbol resolution rule (own pool vs. deepest) and the v4 pool key enrichment. This extra context lifts it above the baseline of 3.

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

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

The description clearly identifies the action: retrieve the full record for a single pool, including the v4 pool key, and distinguishes it from list_pools by focusing on one pool. The target is specified via symbol or pool id, making the resource unambiguous. It lacks an explicit verb like 'retrieves' or 'returns', but 'Everything list_pools knows about one pool' conveys the intended operation strongly.

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

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

The description implies this is the single-pool counterpart to list_pools and explains how a symbol is resolved. However, it does not explicitly state when to prefer this tool over list_pools or the other sibling tools, and it offers no when-not-to-use guidance. Usage context is present but mostly inferred rather than prescribed.

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

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

With no annotations provided, the description carries the full behavioral burden. It discloses a key semantic nuance: rates are measurements of the past week, not forecasts, and clarifies that 'keep' is fees retained after arbitrage and that a tenth of swap fees from own pools pays the LoomDesk book. It does not describe pagination or output format, but those are less critical given the rich return-field explanation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Three dense sentences, each earning its place: the first defines scope and fields, the second explains the own-pool distinction, and the third disambiguates measurements from forecasts. No filler or repetition of the schema.

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

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

For a list endpoint with four optional parameters and no output schema, the description covers the returned fields, ownership semantics, and a critical temporal caveat. It is missing explicit guidance on sort behavior and response shape, but the schema already documents defaults and constraints for the parameters.

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

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

Schema description coverage is only 50%, so the description must compensate. It adds meaning to sort values like weekly_at_10 via the ±5/10/15/25% range mention, and to own_only by explaining what 'own' means for Earn positions. However, it does not directly clarify the sort parameter's options or limit, leaving some of the gap unfilled.

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

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

The description names a specific verb ('List') and resource ('Tokenized stock pools on Robinhood Chain'), then enumerates the exact output fields: weekly rate, keep, depth, and 24h flow. It also distinguishes LoomDesk's own pools from all pools, so an agent can tell it apart from siblings like get_pool or quote_position.

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

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

The description provides useful context—own pools are the ones Earn opens positions in—which implies when this tool matters for LoomDesk. However, it never explicitly says when to use list_pools versus get_pool, book_status, or quote_position, and it offers no exclusions.

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

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, but it only lists returned fields. It does not state whether the operation is read-only, what errors can occur, whether results are paginated, or how current the data is.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single sentence that front-loads the core resource and scope, then lists the useful output fields. Every word earns its place; there is no filler or repetition of the title.

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

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

For a one-parameter listing tool with no output schema, the description covers the main entity and return fields, which is adequate but not rich. It lacks any usage guidance or behavioral context, leaving the agent to infer when and how safely to invoke it.

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

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

Schema coverage is 100% and the only parameter, address, is already described as 'The wallet address'. The description adds no new semantic detail beyond confirming that the wallet is the subject, so the baseline score of 3 applies.

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

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

The description identifies a specific resource (a wallet's Uniswap v4 positions opened through LoomDesk Earn) and enumerates the returned data fields, which distinguishes it from sibling tools like list_pools and quote_position. However, it is a noun phrase with no explicit verb such as 'list' or 'get', so it stops short of a fully specified action.

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

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

No guidance is given about when to call this tool instead of siblings such as list_pools or quote_position, and no exclusions or prerequisites are stated. The intended use is only implied by the tool name and title, not explained.

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

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

With no annotations, the description carries the full burden and does so well: 'Nothing is sent: the caller signs and sends them from its own wallet within 20 minutes' discloses the side-effect-free nature, execution handoff, and time validity. It also clarifies that transactions are 'minted to the sender's wallet' and warns about price movement in shallow pools.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Three dense sentences cover the output list, the no-send behavior, and a safety warning. The description is front-loaded with what the tool returns and contains no filler or repetition of schema fields that are already clear.

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

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

Despite no output schema, the description enumerates the main returned items: fee, stock, ticks, weekly earnings, and the approve/open transactions. Combined with the 20-minute validity, the no-send guarantee, and the deposit warning, an agent has enough to invoke the tool correctly and interpret its results.

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

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

Schema coverage is 100% and the schema already explains pool, usdg, and range_pct, so the baseline is 3. The description adds useful context beyond the schema by linking usdg to the 1% fee, framing range_pct as a range 'around the current price,' and warning that deposit size matters in shallow pools.

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

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

The title says 'Quote a position and build the transactions that open it,' and the description expands with a concrete verb-resource pair: it returns a fee, stock amount, ticks, weekly earnings, and transactions. It is clearly distinct from sibling tools like list_pools, get_pool, book_status, and my_positions because it both quotes and constructs transactions rather than listing or inspecting pools.

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

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

The opening 'For an amount of USDG and a range around the current price in one of LoomDesk's own pools' provides clear context for when to call it. It also gives practical guidance like 'Keep a deposit under maxSensibleDepositUsdg' and warns about shallow-pool price impact, though it does not explicitly name alternative tools or exclusions.

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