du-dum
Acerca de
La habilidad du-dum implementa una arquitectura de dos relojes para separar la observación continua y económica de la toma de decisiones ocasional y costosa en agentes autónomos. Utiliza un reloj rápido para recopilar datos en un resumen y un reloj lento que solo desencadena acciones costosas (como llamadas a LLM) cuando se encuentra trabajo pendiente. Este patrón es ideal para optimizar el costo y el rendimiento en bucles de agentes donde la mayoría de los ciclos de observación no requieren ninguna acción.
Instalación rápida
Claude Code
Recomendadonpx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/du-dumCopia y pega este comando en Claude Code para instalar esta habilidad
Documentación
Du-Dum: Batch-Then-Act Pattern
Split observe/act → 2 clocks diff freq. Fast (analysis) = cheap → writes digest. Slow (action) = reads digest → acts if pending. Digest empty → exit immediate. Zero cost idle.
Name = heartbeat: du-dum. First beat (du) observes. Second (dum) acts. Mostly only first fires.
Use When
- Autonomous agent budget → observe often, act rare
- Heartbeat calls LLM every tick → waste
- Observe cheap (API read, file parse, log scan), act expensive (LLM, write, notify)
- Decoupled fail → observe fails → last digest still valid
- Cron agent → analysis + action = separate jobs
In
- Required: Data sources fast clock observes (APIs, files, logs, feeds)
- Required: Action slow clock takes when pending
- Optional: Fast interval (default: 4h)
- Optional: Slow interval (default: 1/day)
- Optional: Daily cost ceiling
- Optional: Digest format (md, JSON, YAML)
Do
Step 1: Identify 2 Clocks
Split work → observe (cheap, freq) vs act (exp, rare).
- List every op
- Classify → observe (reads → summary) or act (LLM/write/msg)
- Verify split: observe ≈0 marginal, act = expensive
- Assign freq: fast catches events, slow meets response-time
| Clock | Cost | Freq | Example |
|---|---|---|---|
| Fast (analysis) | Cheap: API read, parse, no LLM | 4-6x/day | GitHub notifs, RSS, logs |
| Slow (action) | Exp: LLM, write | 1x/day | Compose reply, dashboard, alert |
→ Clean split. Every op on 1 clock. Fast = no LLM. Slow = no gather.
If err: op needs both → split. Fast collects raw → digest. Slow summarizes. Digest = boundary.
Step 2: Design Digest Format
Digest = low-bandwidth msg between clocks. Compact, human-readable, parseable.
- Define path + format (md recommended)
- Header: timestamp + source meta
- "Pending" section → items needing action
- "Status" section → current state
- Clear empty indicator (
pending: none)
Example:
# Digest — 2026-03-22T06:30:00Z
## Pending
- PR #42 needs review response (opened 2h ago, author requested feedback)
- Issue #99 has new comment from maintainer (action: reply)
## Status
- Last analyzed: 2026-03-22T06:30:00Z
- Sources checked: github-notifications, rss-feed, error-log
- Items scanned: 14
- Items pending: 2
Empty:
# Digest — 2026-03-22T06:30:00Z
## Pending
(none)
## Status
- Last analyzed: 2026-03-22T06:30:00Z
- Sources checked: github-notifications, rss-feed, error-log
- Items scanned: 8
- Items pending: 0
→ Template w/ clear pending/empty. Slow clock decides by single check.
If err: digest >50 lines → too much raw. Move details to data file, digest = summary + pointers.
Step 3: Fast Clock (Analysis)
Observation scripts on fast schedule.
- 1 script per source (indep failures)
- Each reads, extracts, appends/rewrites digest
- File lock / atomic write → no partial digest
- Log run (ts, items, errs) → separate log
- Never LLM / write beyond digest
# Pseudocode: analyze-notifications.sh
fetch_notifications()
filter_actionable(notifications)
format_as_digest_entries(filtered)
atomic_write(digest_path, entries)
log("analyzed {count} notifications, {pending} actionable")
Cron:
# Fast clock: analyze every 4 hours
30 */4 * * * /path/to/analyze-notifications.sh >> /var/log/analysis.log 2>&1
0 6 * * * /path/to/analyze-pr-status.sh >> /var/log/analysis.log 2>&1
→ Analysis scripts update digest. Indep → 1 fails, others continue.
If err: source down → log + keep prev entries. Never clear on source fail → stale > missing.
Step 4: Slow Clock (Action)
Reads digest, decides act.
- Read digest (Step 0)
- Pending empty/"none" → exit immediate w/ log
- Items pending → exp op (LLM, compose)
- After act → clear/archive processed entries
- Log run (items, cost, duration)
# Pseudocode: heartbeat.sh (the slow clock)
digest = read_file(digest_path)
if digest.pending is empty:
log("heartbeat: nothing pending, exiting")
exit(0)
# Only reaches here if work exists
response = call_llm(digest.pending, system_prompt)
execute_actions(response)
archive_digest(digest_path)
log("heartbeat: processed {count} items, cost: {tokens} tokens")
Cron:
# Slow clock: act once per day at 7am
0 7 * * * /path/to/heartbeat.sh >> /var/log/heartbeat.log 2>&1
→ Script exits <1s idle. Active → processes + clears.
If err: LLM fails → no clear. Items retry next cycle. Consider retry counter → no infinite retry.
Step 5: Idle Detection
Savings = idle detect. Distinguish "nothing"/"something" min overhead.
- Idle check = single fast op (file read + str check)
- Verify idle path: 0 ext calls (no API/LLM/net)
- Measure duration <1s
- Log idle differently from active
# Minimal idle check
if grep -q "^(none)$" "$DIGEST_PATH" || grep -q "pending: 0" "$DIGEST_PATH"; then
echo "$(date -u +%FT%TZ) heartbeat: idle" >> "$LOG_PATH"
exit 0
fi
→ Idle = 1 file read + str match. No net, no spawn.
If err: unreliable check (false pos = missed work, false neg = waste LLM) → simplify digest. Single bool field (has_pending: true/false) most reliable.
Step 6: Validate Cost Model
Calculate → confirm savings.
- Fast runs/day:
fast_runs = 24 / fast_interval_hours - Slow runs/day: typ 1
- Observe cost:
fast_runs * cost_per_analysis_run(~$0 no LLM) - Act cost:
active_days_fraction * cost_per_action_run - Idle cost:
(1 - active_days_fraction) * cost_per_idle_check(~$0) - Compare w/ original
| Architecture | Daily (active) | Daily (idle) | Monthly (80% idle) |
|---|---|---|---|
| Single loop (LLM every 30min) | $13.74/37h | $13.74/37h | ~$400 |
| Du-dum (6 analyses + 1 action) | $0.30 | $0.00 | ~$6 |
→ Model shows ≥10x cheaper on idle days.
If err: no savings → (a) fast too freq, (b) fast has hidden LLM, (c) rarely idle. Du-dum wants high idle ratio. Always active → simpler polling.
Check
- Fast/slow split clean → no LLM in fast path
- Digest has clear empty indicator
- Idle detect <1s, 0 ext calls
- Fast fail → no digest corrupt (stale preserved)
- Slow fail → no clear pending (retry next)
- Cost model ≥10x savings idle days
- Both clocks log runs
- Digest bounded (archive/clear after process)
Traps
- Digest unbounded: Append no clear → growing log. Always clear/archive after act.
- Fast too fast: Analysis every 5min, events daily → wastes API/IO. Match freq to event rate.
- Slow too slow: Once/day but need same-hour → too slow. Increase freq or urgent shortcut.
- LLM in fast: Breaks cost model. Audit fast scripts → 0 LLM. Defer summary to slow.
- Coupled fast scripts: 1 depends on another → cascade fail. Keep indep → own source, own section.
- Silent idle log: No log → can't distinguish "running idle" vs "crashed". Always log idle.
- Clear digest on analysis fail: Source down → no empty write. Slow would skip actual pending. Preserve last good.
→
manage-token-budget— cost framework du-dum makes practical; du-dum = pattern, budget = accountingcircuit-breaker-pattern— failure case (tools breaking); du-dum = normal case (nothing to do). Together: du-dum idle, circuit-breaker failobserve— methodology for fast clock; du-dum structures when observes become actionable via digestforage-resources— strategic explore layer; du-dum = execution rhythmcoordinate-reasoning— stigmergic signaling; digest = stigmergy (indirect coord via env artifact)
Repositorio GitHub
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