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Agent Dispatch — measured AI agent skill | DecimalAI

a5c-ai/agent-dispatch

SkillScore50Maintained

Build dependency-aware, batched dispatch queues for parallel agent execution.

by a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

AI Engineer pack

decimalai skills pull a5c-ai-agent-dispatch

Get this skill — curl · raw file

curl -fsSL https://app.decimal.ai/s/a5c-ai-agent-dispatch/SKILL.md

Raw file: /s/a5c-ai-agent-dispatch/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-agent-dispatch.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 9d ago

Yes — +45% lift-38% tokens0% turns50% of whole cases pass with skill (11/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-05	✗→✓	▲ Improved	-56%	0%
case-07	✗→✓	▲ Improved	-77%	0%
case-08	✗→✓	▲ Improved	-70%	0%
case-09	✗→✓	▲ Improved	-73%	0%
case-12	✗→✓	▲ Improved	-54%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/31/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/methodologies/automaker/skills/agent-dispatch/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

Agent Dispatch

Build dependency-aware, batched dispatch queues for parallel agent execution.

Agent

Feature Planner - automaker-feature-planner

Workflow

Analyze inter-feature dependencies
Build directed acyclic graph (DAG)
Generate topologically sorted execution order
Group features into batches respecting concurrency limits
Ensure no batch contains interdependent features
Assign agent types to each feature

Inputs

projectName - Project name
orderedPlans - Feature plans in dependency order
maxParallel - Maximum concurrent agents
dependencyGraph - Feature dependency graph

Outputs

Batched dispatch queue with agent assignments

Process Files

automaker-feature-pipeline.js - Stage 5
automaker-orchestrator.js - Phase 3 (batching)

Want to see if a5c-ai/agent-dispatch would activate on your phrasing? Try it before you install — no LLM call, no signup.

Other measured skills in the registry, with their headline benchmark lift.