loop-engineering

COG Loop Engineering

TL;DR: Some COG skills are not one-shot prompts. They are loops: act, observe, verify, decide whether to continue. This skill is the shared vocabulary those skills use. The iron rule: trust deterministic checks, never the agent's own "looks done" self-report. Every loop must declare its verifier, its stopping conditions, and which pattern it follows.

This is a reference and design aid, not a content-generating workflow. Skills that loop (daily-brief, knowledge-consolidation, url-dump, weekly-checkin, and research/triage skills like auto-research and scout) link here instead of restating the rules. Invoke it directly when you are building or fixing an iterative skill.

Why loops

A chain runs fixed steps: A then B then C. A loop is dynamic: the agent takes an action, reads real feedback (a fetched page, a date stamp, a file count), reasons about it, and repeats until a goal is met or a stop condition fires. Most knowledge-work that "keeps going until good enough" is a loop, and COG benefits from naming the loop explicitly rather than hoping a single prompt nails it.

The COG loop

   ┌──────────────────────────────────────────────┐
   │  1. Gather    pull context (vault + sources)   │
   │  2. Act       one step: search / fetch / scan  │
   │  3. Observe   read the real result             │
   │  4. Verify    run the deterministic check      │
   │  5. Update    write progress to a vault file   │
   │  6. Decide    continue?  → loop                │
   │               stop?      → finish + report     │
   └──────────────────────────────────────────────┘

Step 4 is the load-bearing one. A loop without a verifier is just a chain that repeats.

Termination conditions (use layers, never one)

A robust loop needs several exits so it always halts:

Pick the verifier plus at least one safety exit (cap or budget) for every loop. No-progress detection is what stops the quiet infinite loops that a cap alone misses.

Verification first (COG's rule, applied to loops)

COG is verification-first: no hallucinations, sources required. Inside a loop that means:

• Prefer mechanical checks. A date comparison, a source count, a "required field is non-empty", a "file marked consolidated" check cannot be gamed and cannot be hallucinated.
• Reserve judgment-based checks for the genuinely unquantifiable (is this theme actually new? is this summary faithful?). When you must use judgment, state confidence and link evidence.
• Never accept the agent's own "I think this is complete." That is the single most common way loops produce confident garbage.

In-loop context management

Long loops fill the window with old tool output and start to drift ("context rot"). Counter it:

• Externalize state to the vault. Write progress to the output file as you go. The vault file is the memory; the conversation is scratch.
• Compact and prune. Summarize finished passes into a line or two. Drop raw page text once you have extracted what you need.
• Isolate sub-agents. In agent_mode: team, give each worker only the slice it needs and take back only its conclusion, so one subtask runs in a clean window. Never paste one worker's raw output into the next worker's prompt.

Named patterns

Failure modes and fixes

How skills use this

A skill's ## Loop Engineering section should be short and concrete. It names:

1. The loop in one or two lines (what repeats).
2. The verifier (the mechanical pass/fail).
3. The termination conditions (verifier plus safety exits).
4. The pattern(s) from the table above.

It does not restate this skill. It points here.