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Trade Decision Verifier

dcl_evaluate_trade

Screens trade decisions for guaranteed-return or zero-risk claims and unqualified directives, requiring 'risk' disclosure before approval. Emits an immutable trade receipt for audit.

Instructions

PRE-ACTION Trade Decision Verifier ($0.02). Screens trade-decision language for guaranteed-return claims, zero-risk/"can't lose" framing, and unqualified "buy/sell X now" directives — any match is NO_COMMIT. If no unsafe language is found, COMMIT additionally requires the word "risk" to appear anywhere in the text as a minimum disclosure marker; its absence alone triggers NO_COMMIT with reason noting the missing disclosure. Produces an immutable trade_receipt (tx_hash/chain_hash/chain_depth) distinct from the top-level audit hash, for downstream systems that specifically need a trade-shaped receipt object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesIdentifier of the agent that produced the response.
responseYesThe trade decision or recommendation text to screen.
payment_idNoOptional payment identifier returned by a previous call when payment is required

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonYesHuman-readable explanation of the verdict.
verdictYesCOMMIT if the trade decision's language passed the screen, otherwise NO_COMMIT.
findingsYesAll matched patterns. Empty list if verdict is COMMIT.
timestampYesUnix timestamp when this record was sealed.
confidenceYesConfidence score of the verdict, from 0.0 to 1.0.
input_hashYesHash of the screened text (raw content is never stored).
trade_receiptYesImmutable receipt for this trade-verification record.
Behavior5/5

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

The description goes far beyond the all-false annotations, disclosing cost ($0.02), the exact decision logic, the requirement for 'risk' as a disclosure marker, the output of an immutable trade_receipt, and its distinction from the top-level audit hash. This is rich behavioral transparency.

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 information-dense and well-structured. It leads with the tool's purpose, then details the decision rules and output, with no filler. Every sentence contributes distinct value.

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 the existence of an output schema and the tool's moderate complexity, the description covers all essential aspects: what is screened, the decision criteria, the receipt output, and the cost. It is complete for an agent to select and invoke the tool correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds extra meaning by explicitly linking the response parameter to trade-decision language and by noting the $0.02 cost, which clarifies when the optional payment_id may be required.

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 uses a specific verb ('Screens') and resource ('trade-decision language') and clearly enumerates the unsafe patterns it detects. It distinguishes itself from sibling evaluation tools by focusing on trade decisions and the resulting NO_COMMIT/COMMIT decision.

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 clearly indicates when to use the tool (for screening trade-decision language) and provides detailed behavioral conditions. However, it does not explicitly name alternatives or state when not to use it compared to sibling evaluators, though the trade-specific focus makes the context clear.

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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