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Secret & Credential Leak Scan

dcl_evaluate_secrets

Scans agent responses for exposed API keys, tokens, private keys, and other credentials, then blocks commits if any secrets are detected.

Instructions

POST-ACTION Secret & Credential Leak Scan ($0.02). Regex-based scan across 8 categories (API keys, cloud credentials, tokens/JWTs, private keys, DB URLs, connection strings, env assignments, webhook secrets, internal endpoints with auth). Any finding results in NO_COMMIT.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesIdentifier of the agent that produced the response.
responseYesThe text to scan for exposed API keys, tokens, private keys, DB URLs, and other credentials.
payment_idNoOptional payment identifier returned by a previous call when payment is required

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tx_hashYesHash of this record in the tamper-evident audit chain.
verdictYesCOMMIT if nothing was found, otherwise NO_COMMIT.
findingsYesAll matches found. Empty list if verdict is COMMIT.
seal_textYesHuman-readable Leibniz Layer verification seal.
timestampYesUnix timestamp when this record was sealed.
input_hashYesHash of the scanned text (raw content is never stored).
risk_scoreYes0.0-1.0 risk score based on number and severity of findings.
verify_urlYesPublic URL to independently verify this seal.
chain_indexYesSequential index of this record in the audit chain.
detection_countYesNumber of findings.
categories_clearYesCategories with no findings.
categories_checkedYesAll checklist categories that were scanned.
Behavior4/5

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

The description discloses the regex-based approach, the eight categories, the $0.02 cost, and the critical consequence that any finding produces NO_COMMIT. This goes beyond annotations and provides useful behavioral context.

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 a single, information-dense sentence. It front-loads the action and cost, and includes a comprehensive list of categories without unnecessary elaboration.

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?

With an output schema and complete parameter descriptions, the description covers the tool's purpose, scope, and a key outcome. It is sufficient for this scan tool, though it lacks explicit cross-referencing to sibling tools.

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?

Since the schema already provides 100% parameter descriptions, the description does not need to add param details. It does not, but the schema fully covers the semantics, so the baseline score of 3 is appropriate.

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 secret and credential leak scan, listing eight specific categories it checks. It distinguishes itself from sibling evaluation tools (like dcl_evaluate_pii) by focusing on credentials and adding the NO_COMMIT consequence.

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 'POST-ACTION' label indicates when the tool should be used, and the scan categories imply the type of content to check. However, it does not explicitly name alternatives or state when not to use it, so it misses a full usage guide.

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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