agentic-delegation

Solid

Delegate 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.

AI & Automation 18 stars 3 forks Updated today Apache-2.0

Install

View on GitHub

Quality Score: 81/100

Stars 20%
43
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Agentic Delegation ## Doctrine Most tasks in this repo decompose into cheap, parallelizable work plus a small amount of work that genuinely needs the orchestrator's judgment. Default to delegating the former. Before doing multi-step work yourself, ask: can a cheaper model do this step just as well? ## a) Exploration and reconnaissance → Haiku - Use the `Explore` agent type with `model: haiku` for read-only reconnaissance: locating files, grepping for symbols, mapping call sites, summarizing existing structure. - Scope each Explore task tightly — one question, one area of the tree. Do not send an Explore agent an open-ended "understand the whole system" ask; split it into targeted sweeps instead. - Require file:line citations in every finding. A report without exact paths and line numbers is not actionable — re-run it with a tighter prompt rather than accepting it. ## b) Bulk writing → Sonnet - Route bulk writing — docs, guides, boilerplate, test scaffolding, repetitive multi-file edits — to Sonnet subagents. - Give each writing task a precise spec: exact file paths to create or edit, the content shape expected, and which repo conventions to mirror (frontmatter shape, heading structure, existing tone). - Hard-constrain every writing delegate: - **Files it may touch** — list them explicitly; nothing outside that list. - **Linters/gates it must pass** — e.g. `npx markdownlint-cli2`, `codespell`, or the schema/validation gate relevant to the files it...

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

AI & Automation Listed

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.

0 Updated 5 days ago
alectivism
AI & Automation Listed

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.

0 Updated 1 weeks ago
itzTiru
AI & Automation Solid

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.

134 Updated today
oaustegard