agent-patterns
- Repo stars 2,235
- Author updated Live
- Author repo claude-code-plugins-plus-skills
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @jeremylongshore · no license declared
- Token usage
- Moderate
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- Python
- Permissions
-
- Read-only
- Shell exec
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: agent-patterns
description: 'Execute this skill should be used when the user asks about "SPAWN REQUEST Agent Patterns define…
category: ai
runtime: Python
---
# agent-patterns output preview
## PART A: Task fit
- Use case: 'Execute this skill should be used when the user asks about "SPAWN REQUEST Agent Patterns defines the coordination protocol for multi-agent sprint execution within the Sprint plugin. It governs how the project architect spawns implementation and testing agents, how agents communicate results via structured reports, and how parallel agents avoid conflicts.….
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Overview / Prerequisites / Instructions” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “'Execute this skill should be used when the user asks about "SPAWN REQUEST Agent Patterns defines the coordination protocol for multi-agent sprint execution within the Sprint plugin. It governs how the project architect spawns implementation and testing agents, how agents communicate results via structured reports, and how parallel agents avoid conflicts.…”.
- **02** When the source has headings, the agent prioritizes “Overview / Prerequisites / Instructions” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source mentions slash commands such as `/plugin`; use them first when your agent supports command triggers.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, run shell commands, write/modify files.
Start with a small task and check whether the result follows “Overview / Prerequisites / Instructions”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: agent-patterns
description: 'Execute this skill should be used when the user asks about "SPAWN REQUEST Agent Patterns define…
category: ai
source: jeremylongshore/claude-code-plugins-plus-skills
---
# agent-patterns
## When to use
- 'Execute this skill should be used when the user asks about "SPAWN REQUEST Agent Patterns defines the coordination pro…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Overview / Prerequisites / Instructions” and keep inference separate from source facts.
- read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "agent-patterns" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Overview / Prerequisites / Instructions
rules -> SKILL.md triggers / order / output contract
runtime -> Python | read files, run shell commands, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Agent Patterns
Overview
Agent Patterns defines the coordination protocol for multi-agent sprint execution within the Sprint plugin. It governs how the project architect spawns implementation and testing agents, how agents communicate results via structured reports, and how parallel agents avoid conflicts.
Prerequisites
- Sprint plugin installed and configured (
/plugin install sprint) - Sprint directory initialized at
.claude/sprint/[N]/ specs.mdwritten with clear scope and testing configuration- Familiarity with the sprint phase lifecycle (see the
sprint-workflowskill)
Instructions
Structure every agent spawn using the SPAWN REQUEST format. Include the agent name, the specification file it should read, and any scope constraints:
SPAWN REQUEST Agent: python-dev Specs: .claude/sprint/1/backend-specs.md Contract: .claude/sprint/1/api-contract.md Scope: Authentication endpoints onlyEnsure each spawned agent receives only the files relevant to its scope. Pass the
api-contract.mdas a shared interface so backend and frontend agents stay synchronized.Collect structured reports from every agent upon completion. Each report must include: work completed, files modified, tests added, and conformity status against the specification.
When running agents in parallel, partition work by domain boundary (e.g., backend vs. frontend vs. CI/CD). Never assign overlapping file paths to concurrent agents.
Feed agent reports back to the project architect for review. The architect decides whether to iterate (re-spawn with narrowed specs) or advance to the next phase.
For testing agents, pass the UI test report format shown in
${CLAUDE_SKILL_DIR}/references/ui-test-report.mdso results follow a consistent schema including test counts, coverage, failures, and console errors.
Output
- SPAWN REQUEST blocks consumed by the sprint orchestrator to launch agents
- Structured agent reports containing: summary, files changed, test results, and conformity status
- UI test reports with pass/fail counts, coverage details, failure descriptions, and console error logs
- Updated
status.mdreflecting completed and remaining work after each iteration
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Agent receives wrong specification file | Incorrect path in SPAWN REQUEST | Verify the sprint directory number and file name before spawning |
| Overlapping file modifications from parallel agents | Scope boundaries not clearly defined | Partition work by domain; assign distinct directories to each agent |
| Agent report missing required fields | Agent instructions lack report format | Include the structured report template in the agent prompt |
| Infinite iteration loop | Specs never fully satisfied | Check status.md for blocking issues; the orchestrator pauses after 5 iterations |
| Agent not found | Misspelled agent name in SPAWN REQUEST | Verify agent markdown files exist in agents/ directory |
Examples
Spawning parallel implementation agents:
SPAWN REQUEST
Agent: python-dev
Specs: .claude/sprint/1/backend-specs.md
Contract: .claude/sprint/1/api-contract.md
SPAWN REQUEST
Agent: nextjs-dev
Specs: .claude/sprint/1/frontend-specs.md
Contract: .claude/sprint/1/api-contract.md
Both agents share the same api-contract.md to ensure API compatibility.
Structured agent report format:
AGENT REPORT
Agent: python-dev
Status: COMPLETE
Files Modified: src/auth/routes.py, src/auth/models.py, tests/test_auth.py
Tests: 12 passed, 0 failed
Conformity: All backend-specs requirements implemented
Notes: JWT token expiry set to 24h per spec
Testing agent coordination:
SPAWN REQUEST
Agent: qa-test-agent
Specs: .claude/sprint/1/specs.md
Run After: python-dev, nextjs-dev
SPAWN REQUEST
Agent: ui-test-agent
Specs: .claude/sprint/1/specs.md
Run After: qa-test-agent
Resources
${CLAUDE_SKILL_DIR}/references/ui-test-report.md-- Structured UI test report format with coverage and failure tracking- Sprint workflow skill for phase lifecycle context
- API contract skill for shared interface design
- Sprint plugin README for agent architecture overview
Decide Fit First
Design Intent
How To Use It
Boundaries And Review