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decker.validate_intent

Pre-trade gate check for a proposed order intent. Call this BEFORE placing any order through any execution tool (e.g. a broker MCP's review→place flow). Checks the intent (symbol + side) against Decker's deterministic market state: engine action_gate (GO/WATCH/HOLD — a transition posture, not an order command), current structural state, and the active signal's direction / invalidation (stop) coordinates. Returns a stance reading, NOT an approval or rejection: the vocabulary is the engine gate as-is plus a mechanical side_alignment (aligned/opposed vs the active signal's direction). covered=false means the engine does not emit state for this symbol — treat as unknown, not as HOLD. top-level action_gate can be null even when covered=true — this is not a missing field, it means the current bar has no fresh trigger reading; check gate_null_reason ('no_gate_available' = neither the current bar nor the carried-forward signal had a gate at all, vs 'signal_stale' = a value existed but the underlying signal exceeded the staleness threshold and was deliberately suppressed rather than served as a confident-but-old answer). The order decision and responsibility remain with the calling agent/user. Every check is persisted to an auditable decision ledger (check_id). signal.object_context (W1-C1 standard object block, present when a recent trigger bar exists): my_anchor/opp_anchor(reversal destination)/judgment_ref/geometry/why(action_gate+trigger_kind only, reason codes scrubbed)/reverse_branch context (object_context.reverse_direction_conflict is present only when a local reversal shows stage='confirmed' but the swing's confirmed direction still disagrees — read it before treating reverse_branch.stage='confirmed' as a swing-level reversal) — null when there is no active signal or no trigger bar.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sideYesProposed order direction (buy/long = +, sell/short = -).
symbolYese.g. BTCUSDT, SILVER, 테슬라 — aliases resolve to the engine symbol (XYZ_SILVERUSD, XYZ_TSLAUSD, …).
timeframeNoGate horizon. Omit = your open position's entry TF if you hold one on this symbol, else decker.get_assembly's entry TF (the single judgment authority's current best-path TF), else the engine's default action TF (4h).
order_typeNoOptional, informational (market/limit/…) — recorded in the ledger, does not change the state verdict.

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries full disclosure burden and excels: it explicitly states it returns a stance, not an approval; explains 'covered=false means ... treat as unknown, not as HOLD'; and details top-level action_gate null semantics with 'gate_null_reason' distinguishing 'no_gate_available' vs 'signal_stale.' It also reveals persistence of every check to an auditable ledger (check_id) and warns about reverse_direction_conflict. This is far more than a typical description and prevents many misinterpretations.

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 description is long and dense, but it front-loads the purpose and timing in the first two sentences, then methodically addresses critical edge cases: covered=false versus HOLD, null action_gate with gate_null_reason, the non-authoritative stance, the ledger persistence, and object_context nuances. Every sentence earns its place by clarifying a distinct behavior that could otherwise be misread. It is not merely verbose; it is information-dense. A slight deduction for a single unwieldy final block that could be structured into clearer sub-bullets.

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

Completeness5/5

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 must and does explain the full range of response semantics: the stance vocabulary, side_alignment, coverage flag, null action_gate with its two reasons, and the entire signal.object_context structure, including the obscure reverse_direction_conflict condition. It even specifies when object_context is null. This fully equips an agent to call the tool and correctly interpret any permitted response. Nothing needed for correct invocation or understanding is missing.

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 coverage is 100% and each parameter (side, symbol, timeframe, order_type) already has a detailed schema description, including alias resolution and timeframe precedence. The main description adds the conceptual role of symbol+side in the gate check and references how the timeframe default is derived, but these are already present in the schema. Thus the description adds modest incremental value beyond the structured fields, meeting the baseline for high-coverage schemas.

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 clearly identifies the tool as a 'Pre-trade gate check for a proposed order intent' with the explicit purpose of validating symbol and side against Decker's deterministic market state. It distinguishes itself from order execution by stating 'Call this BEFORE placing any order' and clarifies it returns 'a stance reading, NOT an approval or rejection,' separating it from decision-making and state-query tools. This is a specific verb+resource with unambiguous contrast to siblings.

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

Usage Guidelines4/5

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

The description provides an explicit temporal context: 'Call this BEFORE placing any order through any execution tool,' including an example flow ('a broker MCP's review→place flow'). It also sets boundaries on result interpretation: 'NOT an approval or rejection' and 'the order decision and responsibility remain with the calling agent/user.' While it doesn't enumerate alternative sibling tools to avoid, the when-to-use is unambiguous. A deduction for not naming explicit exclusion or alternative tools for other needs.

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

A4/5.0
Disambiguation5/5

Each tool targets a distinct purpose: state readings (raw vs. view vs. AI-synthesized), signals vs. historical triggers, execution (place/close/update stops), pre-trade validation, and skill management. Cross-references between tools (e.g., get_signals vs. get_trigger_history) explicitly clarify boundaries, leaving no ambiguity about which tool to call.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with the 'decker.' prefix: get_* for reads, place/close/update for actions, set_* for settings, and validate_* for checks. This uniformity makes the tool surface predictable and easy to navigate.

Tool Count5/5

14 tools is well-scoped for a comprehensive trading engine MCP, covering state observation, signal generation, execution, risk management, and user configuration. Each tool earns its place and there are no redundant or missing core functions.

Completeness5/5

The tool surface covers the full trading lifecycle: reading market state (multiple layers), obtaining signals and historical triggers, checking positions, opening/closing positions, updating protective stops, validating intent before orders, and managing skill overlays. The absence of a cancel_order tool is explicitly justified (only market orders), and the domain shows no obvious gaps.

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