skillpack-creator
- Repo stars 438
- Author updated Live
- Author repo skillpack
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @CreminiAI · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- macOS · Linux · Windows
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- 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: skillpack-creator
description: Create a reusable SkillPack from a successful completed task. Use when the user wants to convert…
category: ai
runtime: no special runtime
---
# skillpack-creator output preview
## PART A: Task fit
- Use case: Create a reusable SkillPack from a successful completed task. Use when the user wants to convert a one-off research, coding, analysis, or content workflow into a distributable local SkillPack with `skillpack.json`, local skills under `skills/`, starter prompts, start scripts, and an optional zip package..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Overview / Workflow / 1. Normalize the source task” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Create a reusable SkillPack from a successful completed task. Use when the user wants to convert a one-off research, coding, analysis, or content workflow into a distributable local SkillPack with `skillpack.json`, local skills under `skills/`, starter prompts, start scripts, and an optional zip package.”.
- **02** When the source has headings, the agent prioritizes “Overview / Workflow / 1. Normalize the source task” 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, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; 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 `/tmp`, `/absolute`; 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, write/modify files, run shell commands.
Start with a small task and check whether the result follows “Overview / Workflow / 1. Normalize the source task”. 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: skillpack-creator
description: Create a reusable SkillPack from a successful completed task. Use when the user wants to convert…
category: ai
source: CreminiAI/skillpack
---
# skillpack-creator
## When to use
- Create a reusable SkillPack from a successful completed task. Use when the user wants to convert a one-off research, c…
- 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 / Workflow / 1. Normalize the source task” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; 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 "skillpack-creator" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Overview / Workflow / 1. Normalize the source task
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Skillpack Creator
Overview
Turn a successful task into a reusable SkillPack. Extract the stable workflow, decide what belongs in a local skill versus pack-level prompts, generate the pack structure, and package it only after the workflow is explicit and repeatable.
Workflow
1. Normalize the source task
Reduce the finished task into a clean execution spec:
- Capture the user goal, concrete deliverable, and the final successful workflow (not the full exploratory transcript).
- List required skills, tools, files, secrets, and environment assumptions.
- Separate deterministic steps from heuristic steps; remove dead ends and debugging noise.
- If the task is still too broad, narrow the scope instead of writing a vague mega-skill. If key success conditions depend on hidden human judgment, mark the pack as a best-effort assistant workflow.
Ask for missing stable facts or infer only the low-risk pieces.
2. Decide what the pack should contain
- Local skill (
skills/): reusable procedural knowledge. Keep scripts minimal unless reproducibility depends on exact file generation or repetitive shell steps. - Scripts (
scripts/): repeated shell or file-generation logic where reliability matters. - References (
references/): detailed schemas, API notes, or conventions that should not bloatSKILL.md. - Prompts (
skillpack.json): 1–3 pack-level starter inputs for the UI — not a DAG or state machine. Seereferences/skillpack-format.mdfor exact pack semantics.
3. Create the pack specification
Before writing files, define the pack spec. Prefer one local orchestrator skill plus a small number of external skills. Example minimal manifest:
{
"name": "company-research",
"description": "Research a company and produce a summary report",
"version": "1.0.0",
"prompts": ["Research {company} and create a report with financials and competitors"],
"skills": [
{ "name": "research-orchestrator", "source": "./skills/research-orchestrator", "description": "Orchestrate company research across multiple sources" }
]
}
4. Create the local orchestrator skill
Create skills/<skill-name>/SKILL.md with frontmatter and imperative workflow instructions:
---
name: research-orchestrator
description: "Orchestrate multi-source company research. Use when the user wants a structured company report covering financials, competitors, and market position."
---
- Write the stable workflow as imperative steps in the body.
- Add
scripts/only for fragile or repeated operations; addreferences/only for detailed information.
5. Materialize the pack
Use scripts/scaffold_skillpack.py when you have the pack spec:
# Basic
python3 skills/skillpack-creator/scripts/scaffold_skillpack.py \
--manifest /tmp/skillpack.json \
--output /absolute/path/to/output-pack
# With zip
python3 skills/skillpack-creator/scripts/scaffold_skillpack.py \
--manifest /tmp/skillpack.json \
--output /absolute/path/to/output-pack \
--zip
The script validates the manifest, writes skillpack.json, creates skills/, copies start.sh/start.bat from templates/, and optionally runs npx -y @cremini/skillpack zip.
6. Validate the result
Before handing the pack back, confirm:
- The manifest matches the intended pack scope
- Every declared skill has a valid
name,source, anddescription - Local skills are present under the target pack's
skills/ - Starter prompts are concrete enough to reproduce the workflow
- Zip only after the pack runs as a directory
Output Standard
Produce:
- A short summary of the stabilized workflow.
- The target pack structure and skill inventory.
- The created or updated local skill files.
- The generated
skillpack.json. - Whether the pack was zipped and where the zip lives.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review