Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate

Quantify values with uncertainty bounds. Use when estimating metrics, calculating risk scores, assessing magnitude, or measuring any quantifiable property.

Assign labels or categories to items based on characteristics. Use when categorizing entities, tagging content, identifying types, or labeling data according to a taxonomy.

Watch and report current state of a target system, process, or entity. Use when monitoring status, inspecting live systems, checking current conditions, or observing runtime behavior.

Change persistent state with checkpoint and rollback support. Use when modifying files, updating databases, changing configuration, or any operation that permanently alters state.

Create representation of current world state for a domain. Use when modeling system state, building world models, capturing entity relationships, or establishing baseline snapshots.

Forecast future states or outcomes based on current data and trends. Use when estimating future values, projecting trajectories, forecasting outcomes, or anticipating system behavior.

Define how state changes over time through rules, triggers, and effects. Use when modeling state machines, defining workflows, specifying event handlers, or documenting system dynamics.

Establish cause-effect relationships between events or states. Use when analyzing root causes, mapping dependencies, tracing effects, or building causal models.

Execute a composed workflow by name. Use when running predefined workflows, orchestrating multi-step processes, or delegating to workflow templates.

Anchor claims to evidence from authoritative sources. Use when validating assertions, establishing provenance, verifying facts, or ensuring claims are supported by evidence.

Enforce policies, guardrails, and permission boundaries; refuse unsafe actions and apply least privilege. Use when evaluating actions against policies, checking permissions, or reducing scope to...

Run what-if scenarios to explore outcomes and test hypotheses. Use when evaluating alternatives, stress-testing designs, exploring edge cases, or predicting system behavior under different conditions.

Check correctness against tests, specs, or invariants; produce pass/fail evidence. Use when validating changes, testing hypotheses, checking invariants, or confirming behavior matches expectations.

Fetch known facts or data from specified sources with citations and evidence pointers. Use when you know what you need and where to find it. Emphasizes provenance and verifiable references.

Convert data between formats, schemas, or representations with explicit loss accounting and validation. Use when reformatting data, mapping between schemas, normalizing inputs, or translating structures.

Identify capability gaps and propose new skills with prioritization. Use when analyzing missing capabilities, planning skill development, performing ontology expansion, or assessing coverage.

Safely undo changes by restoring to a checkpoint. Use when verify fails, errors occur, or explicit undo is requested. Essential for the CAVR pattern recovery.

Execute the Debug Code Change workflow end-to-end with safety gates. Use when debugging code changes, investigating issues, or performing root cause analysis with audit trail.

Retrieve prior decisions, rationale, and learned patterns from memory to apply consistently. Use when needing context from previous interactions, looking up past decisions, or ensuring consistency...