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Token DCA orders

get_token_dca_orders
Read-only

PUBLIC, on-chain DCA (dollar-cost-average) orders open against this token — who ELSE in the market is accumulating it on a schedule. ⚠️ NOT the user's own DCAs — those come from get_my_dca_schedules. The two are unrelated datasets that both use the word 'DCA'. This is public market data about the whole market — it is NOT about the user's own wallet or holdings. Tools whose names start with get_my_ are the ones that return the user's own data.

Input Schema

NameRequiredDescriptionDefault
sizeNoMax rows to scan, 1-500.
networkNosolana
order_byNoamount
token_addressYes
order_directionNodesc

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds genuinely useful context that this is public on-chain market data unrelated to the user's wallet, but it says nothing about result limits, recency, or why idempotentHint is false on a read tool.

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 exclusion is front-loaded and the warning marker draws attention to the key disambiguation. However, the 'not your own DCA' point is restated three separate ways, which is more repetition than the disambiguation requires.

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?

An output schema exists, so return values need no explanation, and the read-only annotations cover safety. The remaining gap is parameter-level guidance for sorting and result sizing, which an agent would need to call this effectively.

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?

Schema description coverage is only 20% — only `size` is documented. The description never explains `order_by` (usd_per_min/created/amount/percent_filled), `order_direction`, or `network`, so four of five parameters carry no semantic guidance anywhere. It only implies that `token_address` is the subject token, which is already evident from the name.

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?

States a specific verb+resource with scope: public on-chain DCA orders open against a token, described as what 'who ELSE in the market' is doing. It explicitly contrasts with the sibling get_my_dca_schedules and even names the `get_my_` naming convention, so an agent can disambiguate without opening a schema.

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

Usage Guidelines5/5

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

Explicit when-to-use (market-wide DCA activity for a token) and when-not-to-use (the user's own DCAs), naming the alternative tool by name. The `get_my_` prefix heuristic generalizes the rule to the rest of the toolset.

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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