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Loop Mode

Loop mode is Inferoa's loop-engineering surface for recursive long-horizon work. Run /loop to define the outcome once; Inferoa keeps inspecting, changing, testing, verifying, deciding, and continuing until the work is proven.

Use it when a task may span multiple turns, context compaction, tool failures, verification passes, or a later resumed session.

When To Use It​

Use loop mode when the desired outcome is clear but the work is long:

  • the agent needs to keep working until an objective is complete;
  • progress needs an internal checklist, evidence, and status;
  • completion should not depend on a single assistant turn;
  • you want the session to preserve the objective across interruptions.

Do not use loop mode as a substitute for planning ambiguous scope. If the task needs approval before edits begin, start with Plan mode.

Basic Commands​

/loop Improve the docs site and verify the Docusaurus build.
/loop mode auto Improve the docs site and verify the Docusaurus build.
/loop mode focus Fix the failing parser test and verify it.
/loop mode explore Improve this package and handle related high-value issues.
/loop mode timebox 2h Audit this repository and improve the highest-value rough edges.
/loop mode research Reduce benchmark latency without hurting accuracy.
/loop mode research explore Find and validate latency improvement hypotheses.
/loop status
/loop pause
/loop resume
/loop drop

/loop status displays the active loop, current loop task, attempts, verification, skills, pending review state, and latest loop decisions.

Kind And Approach​

Bare /loop <objective> starts a task loop with automatic approach selection. Inferoa first runs loop task 0 orientation, then decides how broadly to pursue the objective.

Loop kind:

  • task is the default for ordinary implementation, investigation, and verification work.
  • research is for metric-driven experimental loops that need benchmark harnesses, hypotheses, runs, and metric evidence.

Approach:

  • auto lets Inferoa choose after orientation.
  • focus keeps the work scoped to the current objective.
  • explore allows related high-value directions.
  • timebox keeps working until a time checkpoint, then records a loop decision.

Use /loop with no arguments to open the creation flow. If no loop is active, Inferoa asks for the objective, loop kind, and approach.

How It Works​

The active loop stores:

  • the original objective;
  • loop kind (task or research);
  • an internal loop task plan and step status;
  • the current loop task, starting with loop task 0 orientation;
  • attempts, which are runs interpreted as work on the loop task;
  • verification records from commands, research metrics, checker runs, human review, or structured model evidence;
  • an inferred or selected approach (auto, focus, explore, or timebox);
  • a candidate ledger of open, completed, and rejected work;
  • notes, resources, tool traces, skill snapshots, token usage, tool usage, and time usage;
  • the latest loop decision.

The agent should keep step status and evidence current while working. An empty checklist is not enough to finish the loop.

Decisions And Completion​

When the current loop task appears exhausted, Inferoa runs an internal decision pass. The decision pass steps back from the current plan and asks whether more work is needed to satisfy the original objective.

The decision has three useful outcomes:

  • expand: open a new loop task with concrete steps that materially affect the original objective;
  • done: record evidence-backed semantic completion;
  • blocked: pause because user input or an external state change is required.

For broad loops, completion is also gated by the candidate ledger. If a decision says done while high-value candidates remain open, Inferoa expands the next loop task instead of silently finishing.

Loop completion is gated by verification and loop decisions. A loop is not done because the checklist is empty; it is done after verification records evidence-backed semantic completion.

Research Loops​

Research loops reuse the same loop supervisor, but each loop task is shown as a research cycle. A research cycle can create, continue, complete, or reject multiple experiments. Each experiment represents one hypothesis or solution line, and each run records benchmark output and parsed METRIC name=value evidence.

Research completion requires logged metric evidence. The loop cannot complete while a benchmark run is pending, and a done decision should cite run history, the best observed metric, and guardrail or regression evidence.

Self-Improve​

/self-improve and inferoa self-improve turn verified loop evidence into a reviewable workspace skill proposal. The first implementation uses structured replay/gating over recorded evidence rather than a live model rerun:

/self-improve status
/self-improve propose
/self-improve run --replay
/self-improve report
/self-improve adopt

Self-improve artifacts are stored under .inferoa/self-improve/, and adopted skills are written under .inferoa/skills/.

Relationship To Other Modes​

Use Plan mode before loop mode when the scope needs approval.