Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
Turn your expensive model into an affordable daily driver. Offload the boring stuff to Gemini Flash workers — parallel, batch, research — at a fraction of the cost.
If tasks fail within a chain stage, only the failed tasks get retried (not the whole stage). Default: 1 retry. Configurable per-phase via phase.retries or globally via options.stageRetries.
Cost Tracking (v1.3.1)
All endpoints return cost data in their complete event:
session — current daemon session totals
daily — persisted across restarts, accumulates all day
Workers search the live web via Google Search grounding (Gemini only, no extra cost).
# Research uses web search by default
swarm research "Subject" --topic "angle"# Parallel with web search
curl -X POST http://localhost:9999/parallel \
-d '{"prompts":["Current price of X?"],"options":{"webSearch":true}}'
JavaScript API
const { parallel, research } = require('~/clawd/skills/node-scaling/lib');
const { SwarmClient } = require('~/clawd/skills/node-scaling/lib/client');
// Simple parallelconst result = awaitparallel(['prompt1', 'prompt2', 'prompt3']);
// Client with streamingconst client = newSwarmClient();
forawait (const event of client.parallel(prompts)) { ... }
forawait (const event of client.research(subjects, topic)) { ... }
// Chainconst result = await client.chainSync({ task, data, depth });
Daemon Management
swarm start # Start daemon (background)
swarm stop # Stop daemon
swarm status # Status, cost, cache stats
swarm restart # Restart daemon
swarm savings # Monthly savings report
swarm logs [N] # Last N lines of daemon log
Force JSON output with schema validation — zero parse failures on structured tasks.
# With built-in schema
curl -X POST http://localhost:9999/structured \
-d '{"prompt":"Extract entities from: Tim Cook announced iPhone 17","schema":"entities"}'# With custom schema
curl -X POST http://localhost:9999/structured \
-d '{"prompt":"Classify this text","data":"...","schema":{"type":"object","properties":{"category":{"type":"string"}}}}'# JSON mode (no schema, just force JSON)
curl -X POST http://localhost:9999/structured \
-d '{"prompt":"Return a JSON object with name, age, city for a fictional person"}'# List available schemas
curl http://localhost:9999/structured/schemas
Uses Gemini's native response_mime_type: application/json + responseSchema for guaranteed JSON output. Includes schema validation on the response.
Majority Voting (v1.3.7)
Same prompt → N parallel executions → pick the best answer. Higher accuracy on factual/analytical tasks.
# Judge strategy (LLM picks best — most reliable)
curl -X POST http://localhost:9999/vote \
-d '{"prompt":"What are the key factors in SaaS pricing?","n":3,"strategy":"judge"}'# Similarity strategy (consensus — zero extra cost)
curl -X POST http://localhost:9999/vote \
-d '{"prompt":"What year was Python released?","n":3,"strategy":"similarity"}'# Longest strategy (heuristic — zero extra cost)
curl -X POST http://localhost:9999/vote \
-d '{"prompt":"Explain recursion","n":3,"strategy":"longest"}'
Strategies:
judge — LLM scores all candidates on accuracy/completeness/clarity/actionability, picks winner (N+1 calls)
similarity — Jaccard word-set similarity, picks consensus answer (N calls, zero extra cost)
longest — Picks longest response as heuristic for thoroughness (N calls, zero extra cost)
When to use: Factual questions, critical decisions, or any task where accuracy > speed.
Strategy
Calls
Extra Cost
Quality
similarity
N
$0
Good (consensus)
longest
N
$0
Decent (heuristic)
judge
N+1
~$0.0001
Best (LLM-scored)
Self-Reflection (v1.3.5)
Optional critic pass after chain/skeleton output. Scores 5 dimensions, auto-refines if below threshold.
# Add reflect:true to any chain or skeleton request
curl -X POST http://localhost:9999/chain/auto \
-d '{"task":"Analyze the AI chip market","data":"...","reflect":true}'
curl -X POST http://localhost:9999/skeleton \
-d '{"task":"Write a market analysis","reflect":true}'
