Structflow

Evidence-first structural research for industries, companies, commodities, tradable assets, and policy systems. Use when the user requests StructFlow or needs a rigorous, source-grounded analysis of system boundaries, variables, causal drivers, feedback loops, nonlinear dynamics, regimes, market distortion, structural signals, or asset mapping. Run canonical input resolution, staged L0-L7 modeling, adversarial challenge, contradiction search, deterministic research gates, and auditable report generation. Use the host agent's model for reasoning; no separate LLM API key is required. Optional Ta

Install

skills CLI (Claude Code, Cursor, Codex and more)
npx skills add kings0527/structflow --skill structflow
Manual install
git clone --depth 1 https://github.com/kings0527/structflow.git /tmp/structflow
mkdir -p ~/.claude/skills
cp -r /tmp/structflow/. ~/.claude/skills/structflow

Personal skills live in ~/.claude/skills. Use .claude/skills in a project folder to share a skill with your team.

From the SKILL.md

# StructFlow

Build a falsifiable structural model from evidence, validate every stage, and
publish only when hard gates pass.

## Use the bundled runtime

Run commands from this skill directory:

```bash
python scripts/structflow.py ...
```

If dependencies are unavailable, install this package once with
`python -m pip install -e .`.

Use the host agent's current model for every reasoning and generation step.
Never request or configure an LLM API key and never call a second LLM from
Python.

Check optional provider configuration with `setup --check`. If Tavily or
AnySearch is unavailable, use the host agent's search tools and import
normalized results with `import-evidence`. Never ask the user to paste a key
into chat.

## Load references as needed

- Read [runtime-flow.md](references/runtime-flow.md) before executing a new
  analysis or repairing a blocked run.
- Read [methodology.md](references/methodology.md) before generating profile or
  L0-L7 artifacts.
- Read [evidence-policy.md](references/evidence-policy.md) when acquiring,
  importing, selecting, or citing evidence.
- Read [tool-contract.md](references/tool-contract.md) when using commands,
  schemas, workspaces, modes, or provider-key setup.

## Execute the request

Default to `full` mode. Use `core` when the user excludes L7 asset mapping. Use
`validate-only` when the user supplies an existing draft for validation.

Initialize the run and preserve its returned `run_dir`. If the result flags
Read the full skill on GitHub

Details

Skill name
structflow
Repo updated
31 July 2026

FAQ

What does the Structflow skill do?

Evidence-first structural research for industries, companies, commodities, tradable assets, and policy systems. Use when the user requests StructFlow or needs a rigorous, source-grounded analysis of system boundaries, variables, causal drivers, feedback loops, nonlinear dynamics, regimes, market distortion, structural signals, or asset mapping. Run canonical input resolution, staged L0-L7 modeling, adversarial challenge, contradiction search, deterministic research gates, and auditable report generation. Use the host agent's model for reasoning; no separate LLM API key is required. Optional Ta

How do I install the Structflow skill?

skills CLI (Claude Code, Cursor, Codex and more): npx skills add kings0527/structflow --skill structflow. Skills go in ~/.claude/skills (personal) or .claude/skills (project), and Claude loads them automatically when a task matches the description.

Is Structflow popular?

It lives in kings0527/structflow, which has 6 GitHub stars and 0 forks.

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