Desic Terminal

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AI Automation

Profiles, wake conditions, Skill versioning, multi-agent orchestration, reviews and iteration.

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Keep the market watched, decide on evidence, execute and review in the background — Desic Terminal's AI automation freezes "model + account + permissions + rules + wake conditions" into a reproducible run.


1. Core Concepts#

ConceptMeaning
ProfileOne automation configuration: model, permission mode, bound account, watched symbols, scan interval, Skill set with versions, wake conditions, agent team
RunOne full execution triggered by a wake condition or manually: read evidence → analyze → decide → execute → save summary and the next observation set
Wake conditionA typed trigger such as schedule, price, volume, order book, order, position, opportunity or intelligence event
SkillA rules package (Markdown spec) injected into the model context, defining tool usage, trading philosophy and evidence interpretation
ReviewAfter a position closes, a layered evaluation of decision, execution and outcome against the market path before/during/after the trade

A full loop:

Flow
flowchart LR
  Wake[Wake condition hit] --> Run[Profile run]
  Run --> Evidence[Read market / account / intelligence evidence]
  Evidence --> Decide[Decision: opportunity / order / observation set]
  Decide --> Execute[Bounded execution + audit]
  Execute --> Summarize[Save summary and next observation set]
  Summarize --> Review[Position review after close]
  Review --> Improve[Skill suggestion → user confirms → new version]

2. Permission Modes#

The Profile's permission mode defines what it can do, not what the prompt says:

ModeRead market & accountTrade opportunitiesExternal trade side effects
advisorYesNoForbidden
copilotYesCreate, edit, reuseUser approval required
limited_autoYesFrozen-candidate submissionProfile-authorized scope only

Every layer is checked in order: sidecar tool visibility → agent runtime policy → Rust account/environment binding → contract parameter validation → trade prechecks → live confirmation → idempotency control → persistent audit.


3. Create Your First Profile#

Go to AI Automation → Profiles and create a new one:

  1. Basics
    • Name: identifies the Profile in runs and notifications.
    • Permission mode: start with advisor.
    • Bound account and environment: demo / live.
    • Watched symbols: the Profile only reads and writes on these contracts.
    • Scan interval: the cadence of background runs (minutes).
  1. Model and reasoning depth
    • Pick the model this Profile uses (independent of the chat assistant).
    • Reasoning depth trades evidence chain length against time; keep the default at first.
  1. Skills
    • The four system Skills are always loaded (see section 5).
    • Custom Skills are selected individually; each Skill is pinned to a specific version.
  1. Agent team
    • Single agent by default; switch to multi-agent for complex tasks (see section 6).
  1. Wake conditions
    • Skip for the first run and use Run manually to validate one full execution (see section 4).
  1. Save and enable. The list shows status, next wake-up time and the latest run summary.

4. Wake Conditions#

A Profile's watch plan is a set of typed wake conditions, each with an explicit type, parameters and expiry.

Condition types

TypeMeaningExample
ScheduleRepeat on an interval or at a specific timeEvery 30 minutes; daily at 08:00
PricePrice crosses a thresholdBTC breaks 120,000
VolumeTrading activity changes1-minute volume exceeds 3x average
Order bookBook structure changesBest-bid depth spikes
OrderOrder status eventsLimit order filled / cancelled
PositionPosition state changesPosition reaches a take-profit target
OpportunityOpportunity status changesNew opportunity enters approval
IntelligenceIntelligence eventsSmart Money signal changes

Combination and lifecycle

  • Combine multiple conditions with any or all matching.
  • Each condition can set an expiry time and expires automatically.
  • At the end of a run, the agent can save a next observation set (agent-sourced), which forms the watch plan together with your manually created (user-sourced) conditions.

5. Skills and Version Snapshots#

Skills are rule specs injected into the model context. A Profile stores immutable version snapshots — editing a Skill never changes the rules historical runs used.

Four system Skills (always loaded)

SkillResponsibility
desic-core-operationsTools, permissions, opportunities, contract units and execution rules
trading-philosophyEvidence, market regimes, invalidation conditions, risk and review principles
okx-news-intelligenceNews, events, sentiment, macro and market reactions
okx-smart-money-analysisSmart Money, OI, taker flows, crowding, funding and basis

Custom Skills (Settings → Skills)

  • Three sources: built-in editor / local import / Git repository install (Git install works without local Git, see Getting Started).
  • Pin by version inside a Profile; publishing a new version requires a manual upgrade of the snapshot — historical runs stay untouched.

6. Multi-Agent Orchestration#

Complex tasks can assemble an expert team. A scheme defines each sub-agent's role, responsibility and read-only scope:

  • Typical experts: market structure, intelligence flows, account risk, devil's advocate.
  • All experts work in parallel and are read-only: no opportunities, notifications or trades.
  • A single main agent aggregates the evidence and owns the final decision.
  • A devil's-advocate veto must be backed by deterministic precheck results, so empty objections cannot stall the flow.

7. Run Records and Audit#

The Runs list records every wake-up and manual run:

FieldMeaning
StatusRunning / finished / failed
SummaryThis run's decisions and conclusions
Action countsOpportunities created, orders placed, notifications sent
Token usagePer-run usage; unreported usage is never disguised as zero
Next wake-upThe next trigger in the watch plan
ErrorFailure reason with diagnostics

Open a run's session to inspect every message, tool call and approval. Trade actions go through the same idempotent execution and audit chain as manual orders — one reconciliation mechanism for everything.


8. Position Reviews and Optimization Suggestions#

Position reviews: after a position fully closes, it becomes a Position Episode and is reviewed against the market path before, during and after the trade. Three layers:

LayerEvaluatesNotes
Decision qualityWhether the entry thesis heldRules vs evidence consistency
Execution qualityFills, slippage, notificationsOperational issues unrelated to the decision
Random outcomeSingle-trade P&LP&L alone is not interpreted as rule quality

Optimization suggestions: only raised when evidence points to a reusable, verifiable Skill defect:

  1. Each suggestion ships with line-by-line before/after diffs.
  2. You confirm before it is published as a new Skill version.
  3. Profiles never auto-upgrade version snapshots.

9. Notifications#

Configure a Feishu bot in Settings → Notifications to receive:

  • Profile run summaries and anomalies
  • Opportunity creation and approval requests
  • Completed position reviews
  • Published optimization suggestions

Turn on everything live-related; during demo validation, in-app notifications alone are fine.


10. Best Practices#

  1. Start with advisor: let a read-only Profile observe for a while and check what it sees and how it reasons.
  2. Validate everything on demo: sizes, margin, stops, notifications and reconciliation before going live.
  3. One responsibility per Profile: a focused Profile (e.g. "BTC breakout watch") is far easier to audit than an all-purpose one.
  4. Always set wake expiry: prevents stale conditions from firing repeatedly in volatile markets.
  5. Version every Skill change: publish a new version with the motivation, so reviews can attribute outcomes.
  6. Review runs regularly: read the errors and summaries of failed runs, not just the completion count.

11. FAQ#

Q: Does a Profile auto-upgrade Skills? No. Profiles freeze version snapshots; you upgrade manually and historical runs keep their rules.

Q: Can the agent add its own wake conditions? At the end of a run the agent can save a next observation set, still bound by account/symbol rules and expiry; you can delete them anytime.

Q: How much does multi-agent cost? Each expert is a model call per run. Enable per need and periodically evaluate whether the expert count pays for itself in decision quality.

Q: Why can't I enable my live Profile? Live activation requires: bound account read/trade permissions, conflict review against other automation/strategy Profiles on the same account, and explicit confirmation. Check the error shown in the run list.

View source on GitHub