Marketplace

skill-creator-agent

Pair skills with specialist agents, generating both the skill spec and the agent system prompt with validation and routing notes.

allowed_tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite
model: sonnet

$ インストール

git clone https://github.com/DNYoussef/context-cascade /tmp/context-cascade && cp -r /tmp/context-cascade/skills/foundry/skill-creator-agent ~/.claude/skills/context-cascade

// tip: Run this command in your terminal to install the skill


name: skill-creator-agent description: Pair skills with specialist agents, generating both the skill spec and the agent system prompt with validation and routing notes. allowed-tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite model: sonnet x-version: 3.2.0 x-category: foundry x-vcl-compliance: v3.1.1 x-cognitive-frames:

  • HON
  • MOR
  • COM
  • CLS
  • EVD
  • ASP
  • SPC

L1 Improvement

  • Reorganized the skill into the Skill Forge section pattern and added joint outputs for skill specs and agents.
  • Applied prompt-architect ceilings, constraint extraction, and adversarial validation to both artifacts.

STANDARD OPERATING PROCEDURE

Purpose

Create skills that come packaged with a dedicated specialist agent, including SKILL.md content, agent prompt, and integration hooks for registry use.

Trigger Conditions

  • Positive: request to build a reusable skill that relies on a specialist agent, or to retrofit an existing skill with a dedicated agent.
  • Negative/reroute: generic prompt tuning (prompt-architect), pure skill scaffolding (skill-builder), or standalone agent creation (agent-creator).

Guardrails

  • Deliver both artifacts: SKILL.md and agent spec with frontmatter; no status-only responses.
  • Use English outputs with explicit confidence ceilings.
  • Ensure agent scope matches skill scope; avoid duplicated capabilities.
  • Run at least one validation scenario that exercises the skill+agent pair.

Execution Phases

  1. Scoping: Capture skill purpose, triggers, constraints, and domain; classify HARD/SOFT/INFERRED.
  2. Skill Drafting: Author SKILL.md with SOP, guardrails, integrations, and IO contracts following Skill Forge.
  3. Agent Drafting: Create agent prompt, tools, and refusal policy aligned to the skill.
  4. Validation: Test the pair together (happy + edge cases) and record evidence with ceilings.
  5. Delivery: Provide artifacts, routing metadata, and next-step improvements.

Pattern Recognition

  • Tool-driven skills → agent should manage tool orchestration and error handling.
  • Review/analysis skills → agent must enforce evidence and ceiling discipline.
  • Integration-heavy skills → include latency and timeout guidance in both artifacts.

Advanced Techniques

  • Use few-shot examples shared between skill and agent for consistency.
  • Add capability tags so agent-selector can route correctly.
  • Capture reusable snippets for meta-tools to compose in other skills.

Common Anti-Patterns

  • Skill and agent scopes diverge, causing confusion.
  • Missing tests for the combined flow.
  • Absent confidence ceilings or unclear output formats.

Practical Guidelines

  • Keep the agent persona pragmatic; focus on behaviors and contracts.
  • Explicitly document inputs/outputs and refusal criteria in both artifacts.
  • Provide registry path suggestions and tagging.

Cross-Skill Coordination

  • Upstream: prompt-architect for clarity; skill-builder/skill-forge for structure.
  • Downstream: agent-selector for routing; recursive-improvement for ongoing tuning; meta-tools for tool wiring.

MCP Requirements

  • Document any MCP/tool dependencies and tags; tag WHO=skill-creator-agent-{session}, WHY=skill-execution if memory used.

Input/Output Contracts

inputs:
  skill_goal: string  # required objective
  domain: string  # required domain or category
  tools: list[string]  # optional tools/MCP servers
  constraints: list[string]  # optional constraints
outputs:
  skill_spec: file  # SKILL.md content
  agent_spec: file  # agent prompt with frontmatter
  validation: file  # tests and results for the pair

Recursive Improvement

  • Use recursive-improvement on both artifacts together; stop when deltas < 2% or risks logged.

Examples

  • Build a log-analysis skill with an observability agent handling query composition and summarization.
  • Pair a security-advisory skill with an agent that enforces CVE evidence and refusal policy.

Troubleshooting

  • Agent oversteps scope → tighten persona and refusal rules.
  • Skill unclear → rerun constraint extraction and simplify outputs.
  • Tool errors → add retries and error handling in agent prompt; document limits in skill.

Completion Verification

  • SKILL.md and agent spec delivered with aligned scope.
  • Validation evidence recorded with ceilings.
  • Tool/MCP dependencies documented; routing metadata provided.
  • Examples provided demonstrating combined use.

Confidence: 0.70 (ceiling: inference 0.70) - Skill Creator Agent SOP rewritten with Skill Forge cadence and prompt-architect ceilings.