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Template for creating new Agent Skills for context engineering. Use this template when adding new skills to the collection.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
A comprehensive collection of Agent Skills for context engineering, harness engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, evaluating, or debugging agent systems that require effective context management and reliable operating loops.
This skill should be used when writing, enhancing, or evaluating the launch prompt for a long-running autonomous agent or a parallel multi-agent orchestration attacking a hard problem: pseudo-formal task briefs that define terms and an exact success predicate linguistically, enumerate non-counting outcomes, set persistence rules with explicit stop and return conditions and effort floors, manage a diverse portfolio of parallel approaches with an approach registry and blocked-route bookkeeping, and gate the return on adversarial audit. Route agent topology and coordination protocols to multi-agent-patterns, runtime control surfaces and loop governance to harness-engineering, evaluator and quality-gate construction to evaluation, judge design to advanced-evaluation, and compaction or memory mechanics to context-compression and memory-systems.
This skill should be used when the harness, scaffold, workflow, or optimizer itself is the optimization target: recursive self-improvement (RSI) loops, meta-harnesses, self-improving harnesses that mine their own failures and propose bounded edits, evolutionary or population-based search over agent scaffolds, acceptance gates for self-modifying systems, and agentic context evolution where the mechanism that produces context is versioned and evolved. Route governance of a single autonomous loop (locked surfaces, durable logs, rollback, novelty gates, approval boundaries) to harness-engineering, measurement and quality-gate design to evaluation, judge design to advanced-evaluation, and remote sandbox infrastructure to hosted-agents.
This skill should be used for book-to-SFT pipelines: ePub extraction, literary segmentation, author-voice dataset construction, style-transfer training, LoRA workflows, and model evaluation for voice replication.
This skill should be used for personal operating-system workflows: content creation, voice consistency, relationship lookup, meeting preparation, weekly review, goal tracking, personal brand management, and network management.
Ensure thorough validation, error recovery, and transparent reasoning in research tasks with multiple tool calls
| name | skill-template |
| description | Template for creating new Agent Skills for context engineering. Use this template when adding new skills to the collection. |
Provide a clear, concise description of what this skill covers and when to use it. This description appears in skill discovery and should help agents (and humans) determine when this skill is relevant.
Important: Keep the total SKILL.md body under 500 lines for optimal performance. Move detailed reference material to separate files in the references/ directory.
Every skill body must make its ownership boundary explicit. The description and When to Activate section should say what the skill owns and which adjacent skills own nearby work. This prevents broad skills from stealing activation from narrower skills.
Describe specific situations, tasks, or contexts where this skill should be activated. Include both direct triggers (specific keywords or task types) and indirect signals (broader patterns that indicate skill relevance).
Write in third person. The description is injected into the system prompt, and inconsistent point-of-view can cause discovery problems.
Include a short "Do not activate" block for adjacent skills. Example:
project-development.tool-design.Explain the fundamental concepts covered by this skill. These are the mental models, principles, or frameworks that the skill teaches.
Default assumption: Claude is already very smart. Only add context Claude does not already have. Challenge each piece of information:
Prefer behavior-changing mechanisms over general background. If a concept should be reusable across the corpus, add or update a record in researcher/mechanisms/registry.jsonl.
Provide detailed explanation of the first major topic. Include specific techniques, patterns, or approaches. Use examples to illustrate concepts.
Provide detailed explanation of the second major topic. Continue with additional topics as needed.
For longer topics, consider moving content to references/ and linking:
Provide actionable guidance for applying the skill. Include common patterns, anti-patterns to avoid, and decision frameworks for choosing between approaches.
Match the level of specificity to the task's fragility:
Practical guidance should be executable by an agent: a workflow, checklist, decision table, or concrete operating rule. If a section only explains history or motivation, move it to references/.
Provide concrete examples that illustrate skill application. Examples should show before/after comparisons, demonstrate correct usage, or show how to handle edge cases.
Use input/output pairs for clarity:
Example:
Input: [describe input]
Output: [show expected output]
List specific guidelines to follow when applying this skill. These should be actionable rules that can be checked or verified.
List experience-derived failure modes, common mistakes, and counterintuitive behaviors. These are the highest-signal content in any skill. Each gotcha should be specific, actionable, and non-overlapping with guidance already in the skill body. Use numbered format:
Explain how this skill integrates with other skills in the collection. List related skills as plain text (not links) to avoid cross-directory reference issues:
Internal reference (use relative path to skill's own reference files):
Related skills in this collection:
External resources:
Numeric, benchmark, volatile, or vendor-performance claims need an inline claim-* ID backed by researcher/claims/index.jsonl, or they should be softened and moved to dated reference material.
Created: [Date] Last Updated: [Date] Author: [Author or Attribution] Version: [Version number]