Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
日本語の概要は準備中です。原文の説明を表示しています。
Shared loop-engineering reference for COG skills - the agent loop, deterministic verifiers, termination conditions, in-loop context management, and named patterns. Invoke when designing or debugging a skill that iterates (search-verify-retry, scan-until-dry, fetch-retry-gate).
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
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.
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.
┌──────────────────────────────────────────────┐
│ 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.
A robust loop needs several exits so it always halts:
| Exit | What it is | Example |
|---|---|---|
| Deterministic verifier | A mechanical pass/fail that confirms the goal | "Publication date is within 7 days" |
| Hard iteration cap | Max passes, no matter what | "Stop after 5 searches per topic" |
| Budget guard | Max time / tool calls / tokens | "Stop after 20 fetches total" |
| No-progress detection | Recent passes changed nothing | "2 searches in a row found nothing new" |
| Human escalation | Hand a stuck loop back to the user | "Asked twice, still unclear: ask the user" |
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.
COG is verification-first: no hallucinations, sources required. Inside a loop that means:
Long loops fill the window with old tool output and start to drift ("context rot"). Counter it:
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.| Pattern | Shape | Where COG uses it |
|---|---|---|
| Act-observe (ReAct) | reason → act → observe → repeat | base of every COG loop |
| Reflect-retry (Reflexion) | on failure, write the lesson, retry differently | url-dump / scout fetch retries, daily-brief re-search |
| Plan-execute-verify | plan steps, run them, verify each | knowledge-consolidation passes |
| Evaluator-optimizer | generate, score against criteria, repeat until it passes | daily-brief item verify, url-dump quality gate |
| Orchestrator-workers | split into subtasks, run in fresh windows, synthesize | team-mode scans, auto-research threads, team-brief |
| Loop-until-dry | keep going until K passes in a row surface nothing new | knowledge-consolidation theme extraction |
| Human-in-the-loop | escalate or ask when the loop is stuck or the call is the user's | weekly-checkin reflection, onboarding |
| Failure | Fix |
|---|---|
| Context overflow / drift | compact, prune, externalize to vault, isolate sub-agents |
| Silent infinite loop | no-progress detection plus a hard cap |
| Hallucinated success | trust the deterministic verifier, never self-report |
| Compounding errors | verify early and every pass, not only at the end |
| Cost blowup | budget guard, and stop at "good enough", not "perfect" |
| Goal drift | keep the goal and stop conditions written at the top of the loop's state |
A skill's ## Loop Engineering section should be short and concrete. It names:
It does not restate this skill. It points here.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
日本語の概要は準備中です。原文の説明を表示しています。
Quick capture of raw thoughts with intelligent domain classification and competitive intelligence extraction
日本語の概要は準備中です。原文の説明を表示しています。
Run one task through the V-model verification loop: CP-2 plan → CP-3 build → CP-3v component verify → CP-4 integration verify (full lane) → CP-5 acceptance. The worker never grades its own homework; evidence rows trace back to AC-n. Opt-in: invoke with /closed-loop or by asking for the closed loop, proper verification, or an evidence trail. Ordinary work does not run this.
日本語の概要は準備中です。原文の説明を表示しています。
Deep-dive 7-day analysis across all data sources for weekly reviews, board prep, and strategic planning
日本語の概要は準備中です。原文の説明を表示しています。
Autonomous content pipeline - scout announcements in your field, triage by trend momentum and personal angle, produce posts/blogs/videos in your voice with ledger-based dedup, hard volume caps, and screenshot-verified publishing
日本語の概要は準備中です。原文の説明を表示しています。
Create user stories with duplicate checking across any project tracker (Linear, GitHub Issues, Jira)
日本語の概要は準備中です。原文の説明を表示しています。