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Estimasi Slippage Order Book

estimate_slippage
Read-only

Hitung avg fill price, slippage %, dan impact cost buat mengisi target notional USD dari order book depth yang di-supply caller (BUKAN fetch sendiri -- pass bids/asks dari binance_get_order_book_depth). BUY jalan-kan asks (naik), SELL jalan-kan bids (turun).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asksYesLevel ask [priceStr, qtyStr], urutan naik (best ask duluan).
bidsYesLevel bid [priceStr, qtyStr], urutan turun (best bid duluan).
sideYesBUY = isi dari asks (naik), SELL = isi dari bids (turun).
symbolYesSimbol pair Binance Futures, contoh: BTCUSDT, ETHUSDT. Harus pair perpetual yang terdaftar di Binance USDS-M Futures.
targetNotionalUsdYesTarget notional USD yang mau diisi.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds meaningful behavioral context: it is a pure calculation over caller-supplied depth, walks prices in the appropriate direction, and reports three result metrics. It does not cover edge cases like insufficient depth, but it transparently describes the core behavior.

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?

A single dense sentence conveys the purpose, inputs, computation direction, and source dependency with no wasted words. The most important constraint (not fetching its own data) is front and center.

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?

Given there is no output schema, the description usefully names the three return values (avg fill price, slippage %, impact cost). All required inputs are documented. It does not state behavior when order book depth is insufficient to reach the target notional, which is the main completeness gap for a tool of this kind.

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 already well documented. The description reinforces the side semantics and data provenance (bids/asks from binance_get_order_book_depth), but adds little beyond what the schema already states.

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?

The description names a specific verb ('Hitung'), the resource (order book depth), and the exact outputs: avg fill price, slippage %, and impact cost. It also explicitly distinguishes itself from binance_get_order_book_depth by stating it does NOT fetch data itself, which clearly differentiates it from the sibling tool that supplies its inputs.

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?

The description gives explicit usage direction: the caller must supply bids/asks from binance_get_order_book_depth rather than having this tool fetch them. It states the side-specific walking logic (BUY uses asks, SELL uses bids) and the goal (filling a target notional USD), so an agent knows exactly when and how to invoke it.

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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TDQS

A3.7/5.0
Disambiguation4/5

Most tools map to a distinct Binance metric or analytic concept, and descriptions explicitly contrast near-neighbors (spot vs futures, snapshot vs delta, 'BEDA dari...' notes). A few pairs could still be confused—`binance_get_basis` vs `binance_get_basis_history` and `binance_get_agg_trades` vs `binance_get_recent_trades`—but their purpose differences are explained well enough for careful agents.

Naming Consistency4/5

The dominant pattern is `binance_<verb>_<object>` in snake_case, with consistent complementary pairs like `get_*` and `get_*_history`. There are minor style breaks: `orderbook` vs `order_book`, the `whalescope_*` prefix, and `whalescope_full_pipeline` which lacks a verb, but the overall structure is readable and predictable.

Tool Count1/5

56 tools cross the explicit '50+ tools' extreme threshold. Although the Binance Futures domain is broad, many tools are single-endpoint or single-metric wrappers—multiple klines variants, order book variants, and ticker variants—that could be consolidated into parameterized composite tools. The surface is far too large for most agents to navigate efficiently.

Completeness4/5

The public market-data and analytics surface is remarkably complete: klines, funding, open interest, long/short ratios, top-trader data, liquidations, basis, order book behavior, regime detection, and full pipeline scoring are all covered. The main gaps are documented limitations such as unavailable liquidation-by-price data and non-public account/execution tooling, but agents can work around them without dead ends.

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