hydra
Hydra is a Lead-driven orchestration toolkit that lets you coordinate multiple agents through structured workflows. The Lead makes strategic decisions while workers report semantic outcomes (done, needs_rework, replan) via a typed result contract, enabling parallel task execution with explicit decision points and intervention capabilities.
Hydra orchestrates multi-agent workflows where a Lead agent makes strategic decisions while workers handle operational tasks through a structured result contract.
AI-generated summary based on this skill's SKILL.md
Install
blueberrycongee/termcanvas/hydra · repository language: TypeScript
git clone https://github.com/blueberrycongee/termcanvas
cp -r termcanvas/skills/skills/hydra ~/.claude/skills/hydranpx skillfed install blueberrycongee/termcanvas/hydraFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
What is hydra multi-agent orchestration?
Hydra is a Lead-driven orchestration toolkit that coordinates multiple agents through structured workflows. The Lead makes strategic decisions while workers report semantic outcomes (done, needs_rework, replan) via a typed result contract, enabling parallel task execution with explicit decision points and intervention capabilities.
How does hydra dispatch and retry agents?
Hydra routes agent outcomes—completed, stuck, or error—and manages retries through decision points. When agents report needs_rework or error states, the Lead can intervene with feedback and redispatch tasks. Parallel worktrees remain isolated during execution, then merge results once agents complete or reach terminal states.
Can hydra run parallel agent tasks with isolated worktrees?
Yes. Hydra dispatches parallel agent tasks, each with isolated worktrees to prevent interference. Once agents finish or reach terminal outcomes, hydra merges their results according to the Lead's coordination logic, enabling safe concurrent execution and result aggregation.
How do I monitor agent progress and intervene at decision points?
Hydra lets you watch decision points and inspect workflow state, telemetry, and event logs for debugging. You can monitor agent progress in real time and intervene with feedback at decision points, allowing the Lead to redirect stuck or underperforming agents before they consume more resources.
What does the agent result contract schema define?
Hydra's typed result contract defines semantic intent result parsing: agents report outcomes as done, needs_rework, or replan. This contract ensures consistent communication between workers and the Lead, enabling predictable routing and decision-making across your multi-agent workflow.
How does hydra handle workflow state and event logs?
Hydra maintains a workflow ledger that tracks all events, state transitions, and agent telemetry. You can inspect this ledger to debug failures, audit decisions, and understand how the Lead coordinated agents. State management captures each decision point and outcome for full workflow visibility.
SKILL.md
rendered from the published skill — quoted content, verbatim
Hydra Orchestration Toolkit
Hydra is a Lead-driven orchestration toolkit. You (the Lead agent) make strategic decisions; Hydra handles operational management (dispatch, retry, health checks, result collection).
Sub-agents output semantic intent (done/needs_rework/replan), not routing
information. Hydra manages the lifecycle; you decide what happens next.
Why this design (vs. other coding-agent products)
- SWF decider pattern, specialized for LLM deciders. Hydra is the AWS SWF / Cadence / Temporal decider pattern.
hydra watchisPollForDecisionTask; the Lead is the decider;lead_terminal_idenforces single-decider semantics. - Parallel-first, not bolted on.
dispatch+depends_on+ worktree +mergeare first-class. Other products (Factory.ai's Droid, Amp, Claude Code subagents) treat parallelism as open research; Hydra makes it the default. - Typed result contract. Workers publish a schema-validated
result.json(outcome: completed | stuck | error,
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skills/skills/hydra/SKILL.md