Agent Skills: Skill Creator

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UncategorizedID: krafton-ai/kira/skill-creator

Repository

krafton-aiLicense: Apache-2.0
820103

Install this agent skill to your local

pnpm dlx add-skill https://github.com/krafton-ai/KIRA/tree/HEAD/KiraClaw/defaults/skills/skill-creator

Skill Files

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KiraClaw/defaults/skills/skill-creator/SKILL.md

Skill Metadata

Name
skill-creator
Description
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Skill Creator

Use this skill when the task is to create or refine a reusable skill package.

Goals

  • keep the skill short enough to load cheaply
  • encode workflow, not generic model intelligence
  • use references or scripts only when they clearly reduce risk or repetition
  • fit KiraClaw's seeded-skill layout under Filesystem Base Dir/skills

Workflow

  1. Define the trigger clearly:
    • what user requests should activate this skill?
    • what should not activate it?
  2. Decide the scope:
    • one focused workflow per skill
    • avoid combining unrelated jobs into one package
  3. Write the frontmatter carefully:
    • name
    • description
    • include trigger examples in the description
  4. Write the body as operational guidance:
    • workflow steps
    • failure modes
    • decision rules
    • exit criteria
  5. Add references or scripts only if they reduce repeated work or improve reliability.

Rules

  • Prefer one strong skill over one huge omnibus skill.
  • Do not explain concepts the base model already knows unless the local workflow is special.
  • Do not turn the skill into a README or changelog.
  • If the skill depends on local tools, directories, or conventions, say so directly.
  • Keep examples short and realistic.

Good Skill Shape

Most good skills have:

  • a narrow trigger
  • a short workflow
  • a few rules that prevent common mistakes
  • one or two high-value examples

When to Split

Split the skill if:

  • it has multiple unrelated trigger families
  • it needs different rules for different domains
  • the body is becoming reference material instead of workflow guidance

Seed Skill Guidance

For seeded default skills:

  • optimize for broad usefulness
  • avoid org-private assumptions
  • keep the body compact so new workspaces do not inherit unnecessary prompt weight

Validation

Before finishing a new skill, check:

  • is the trigger description specific enough?
  • does the body contain real workflow guidance?
  • can at least one realistic task use it without extra explanation?