agentic-delegation
SolidDelegate exploration sweeps to Haiku subagents and bulk writing to Sonnet subagents while the orchestrator keeps architecture, security-sensitive edits, and commits; use at the start of any multi-step task in this repo to minimize token spend by delegating to cheaper models.
Install
Quality Score: 81/100
Skill Content
Details
- Author
- Raishin
- Repository
- Raishin/vanguard-frontier-agentic
- Created
- 3 months ago
- Last Updated
- today
- Language
- Rust
- License
- Apache-2.0
Integrates with
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
subagent-delegation
Use BEFORE starting any multi-part task (research or comparisons across several sources, reading or summarizing long documents and transcripts, bulk updates across many items, audits, or checking a draft or numbers before they go out). Also use when about to spawn any subagent or worker, or when a task needs 3+ searches or tool calls. Routes gathering, reading, and bulk work to cheaper worker models, and escalates hard reasoning or a final check to a stronger model only when that actually helps.
cost-lean-orchestration
Token-efficient model routing for complex engineering sessions. The main model (Opus / Fable, high reasoning) never bulk-reads or explores — it delegates all exploration, bulk file reading, codebase search, log scanning, dependency tracing, and documentation reading to Sonnet subagents that return compact structured findings, and it spends its own tokens only on synthesis, architecture, judgment, and final code. Use this skill in EVERY session that involves reading more than a couple of files, exploring or mapping a codebase, investigating a bug, auditing call sites, reviewing a large diff, digesting logs or docs, or any multi-step engineering task — even if the user never mentions cost, tokens, subagents, or delegation. This is a standing operating discipline, not an on-request feature.
agent-routing
Decide which model (Haiku/Sonnet/Opus) and effort level each subagent gets, when to cascade cheap-first behind a verifier, and how to run improvement loops safely (evaluator-as-selector, stop on regression). Covers the Managed Agents effort mechanics (per-agent effort levels, cost lever) and how to watch a subagent fan-out stream live so loop and escalation gates have something to observe. Use when spawning subagents via the Agent or Workflow tools, when fanning out more than a handful of agents, or when the user asks which model or effort a task should route to. Routing heuristics grounded in measured calibration data (references/calibration-2026-07-15.md), not vibes; the Managed Agents API specifics are operational, not calibrated.