structured-intelligence-skill-creator
Create or update repository skills that conform to local templates, provider metadata requirements, registry rules, and validation workflows.
- License 许可
- MIT
- 最近更新
- 2026-11-03
- Stars
- ★ 4
- Forks
- 1
01 前言 Front Matter
- name
- structured-intelligence-skill-creator
- description
- Create or update repository skills that conform to local templates, provider metadata requirements, registry rules, and validation workflows.
02 资源文件 8
- 参考文档agents/claude.yaml378 B
- 参考文档agents/openai.yaml379 B
- 参考文档agents/README.md322 B
- 资产文件assets/.gitkeep—
- 参考文档config.yaml325 B
- 参考文档references/project-skill-checklist.md1.5 KB
- 参考文档references/README.md68 B
- 脚本scripts/run.sh1.3 KB
03 SKILL.md 正文
Skill: structured-intelligence-skill-creator
Use When
- A user wants to create a new skill in this repository under
skills/<skill-id>/. - A user wants to update an existing repository skill without breaking local conventions.
- The task must produce a Codex- and Claude-compatible skill bundle with matching registry metadata.
Inputs
- Required:
skill-idinkebab-case- human-friendly skill name
- one-line description
- Optional:
- owner override
- version override
- whether the skill needs
scripts/,references/, orassets/ - example prompts, input schema, or output contract
Workflow
- Confirm the task is a skill, not an agent. Skill folders live under
skills/<id>/. - Read only the local files needed to stay aligned with the repository:
docs/conventions.mdskills/README.mdskills/registry.yamlskills/_templates/skill/*references/project-skill-checklist.mdfrom this skill when exact requirements are needed
- For a new skill, prefer deterministic scaffolding:
- If bundled scripts are available, run
scripts/run.sh <skill-id> [repo-root] - Otherwise run the repository helper:
./scripts/bootstrap_new_skill.sh <skill-id>
- If bundled scripts are available, run
- Replace all template placeholders before finishing:
config.yaml:id,name,version,owner,descriptionSKILL.md: use conditions, inputs, workflow, output contract, limitsagents/openai.yamlandagents/claude.yaml: matching display text and provider-specific default prompt
- Keep the bundle minimal:
- Add scripts only when deterministic execution or repeated logic is useful
- Add references only when they reduce
SKILL.mdsize or hold project-specific detail - Do not add generic changelogs, installation guides, or duplicate documentation
- Register the skill in
skills/registry.yamland keepid,name, andversionidentical toconfig.yaml. - Validate with
./scripts/validate_structure.shbefore returning the task as complete. - Report the created or updated files, validation result, and install commands for both tools.
Output Contract
skills/<skill-id>/config.yamlwith valid metadataskills/<skill-id>/SKILL.mdwith explicit inputs, outputs, and limitsskills/<skill-id>/agents/openai.yamlskills/<skill-id>/agents/claude.yaml- optional
scripts/,references/, andassets/only when justified - matching entry in
skills/registry.yaml - validation status from
./scripts/validate_structure.sh - install commands:
./scripts/install_skill.sh <skill-id>./scripts/install_skill.sh <skill-id> --tool claude
Limits
- Do not overwrite an existing skill blindly; read the current bundle first.
- Do not leave placeholder strings from the template.
- Do not introduce a registry entry without a real folder and matching config.
- Common failure cases:
- invalid
kebab-caseid - semver mismatch between registry and
config.yaml - missing
agents/openai.yamloragents/claude.yaml - using the wrong default prompt format (
$skill-idfor OpenAI, bareskill-idfor Claude) - skipping
./scripts/validate_structure.sh
- invalid
04 同仓库更多 Skills
stat-survival-analysis
Estimate and compare survival functions using Kaplan-Meier curves and log-rank test, with optional Cox proportional hazards regression.
stat-pca
Perform PCA on a numeric data matrix to reduce dimensionality, visualize sample structure, and identify top contributing features.
stat-pairwise-correlation
Compute pairwise correlations and significance tests across all numeric variables, and produce a correlation heatmap.
stat-nonlinear-embedding
Embed high-dimensional data into 2D using t-SNE or UMAP for exploratory visualization of sample or cell relationships.
stat-logistic-regression
Fit a logistic regression model for binary outcomes, report odds ratios and model performance (AUC-ROC, confusion matrix).
stat-learn-bayesian-network
Learn the structure and conditional probabilities of a Bayesian network from observational data for causal discovery or dependency modeling.