{"skill":{"slug":"probabl-ai-python-code-style","name":"python-code-style","description":"Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Three responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, (2) run ruff against any Python files Claude has just generated or edited, and (3) contextualize each touched file's comments to the data-science problem — rewriting any leftover template / workflow prose (skill names, gates, runner, digest, guard-rails) into concise, problem-specific docs so the user's committed files read like a colleague wrote them, not like a generated scaffold. Stops at \"the touched files pass `ruff check` and document the problem, not the process.\" TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run AND the file's comments are contextualized to the problem; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and th","repository":"https://github.com/probabl-ai/skills/tree/main/skills/python-code-style"},"recommended_command":"npx skills add probabl-ai/skills --skill python-code-style","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add probabl-ai-python-code-style","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"python-code-style\" agent skill from https://github.com/probabl-ai/skills/tree/main/skills/python-code-style. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Three responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, (2) run ruff against any Python files Claude has just generated or edited, and (3) contextualize each touched file's comments to the data-science problem — rewriting any leftover template / workflow prose (skill names, gates, runner, digest, guard-rails) into concise, problem-specific docs so the user's committed files read like a colleague wrote them, not like a generated scaffold. Stops at \"the touched files pass `ruff check` and document the problem, not the process.\" TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run AND the file's comments are contextualized to the problem; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and th After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"probabl-ai-python-code-style\",\"task\":\"Install python-code-style\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"python-code-style\" as a Claude Code skill from https://github.com/probabl-ai/skills/tree/main/skills/python-code-style. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Three responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, (2) run ruff against any Python files Claude has just generated or edited, and (3) contextualize each touched file's comments to the data-science problem — rewriting any leftover template / workflow prose (skill names, gates, runner, digest, guard-rails) into concise, problem-specific docs so the user's committed files read like a colleague wrote them, not like a generated scaffold. Stops at \"the touched files pass `ruff check` and document the problem, not the process.\" TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run AND the file's comments are contextualized to the problem; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and th After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"probabl-ai-python-code-style\",\"task\":\"Install python-code-style\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"python-code-style\" from https://github.com/probabl-ai/skills/tree/main/skills/python-code-style into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Three responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, (2) run ruff against any Python files Claude has just generated or edited, and (3) contextualize each touched file's comments to the data-science problem — rewriting any leftover template / workflow prose (skill names, gates, runner, digest, guard-rails) into concise, problem-specific docs so the user's committed files read like a colleague wrote them, not like a generated scaffold. Stops at \"the touched files pass `ruff check` and document the problem, not the process.\" TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run AND the file's comments are contextualized to the problem; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and th After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"probabl-ai-python-code-style\",\"task\":\"Install python-code-style\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"install_receipt":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","idempotency":"event_id is unique; retries update the same receipt","count_rule":"verified installs require install_used=true and outcome=success","example":{"event_id":"install_<unique-id>","skill_slug":"probabl-ai-python-code-style","task":"Install python-code-style","agent":"codex","outcome":"success","install_used":true}},"safety_gate":{"tier":"blocked","label":"Blocked for auto-install","badge":"BLOCKED","auto_install_policy":"block","auto_install_allowed":false,"human_review_required":true,"blocked":true,"recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","reasons":["Metadata combines secrets access with shell or command execution","High-risk permission hints: Shell or command execution, Secrets or environment access"]},"agent_prompt":"Install the \"python-code-style\" agent skill only after reviewing the OpenAgentSkill profile and source repository. Safety gate: Blocked for auto-install (block). Start with https://www.openagentskill.com/skills/probabl-ai-python-code-style, inspect the trust and audit notes, then use the recommended install handoff: npx skills add probabl-ai/skills --skill python-code-style. After installation, summarize changed files, required setup, and a minimal verification result before using the skill for real work. Report the verified result to https://www.openagentskill.com/api/agent/outcome using a unique event_id, skill_slug=probabl-ai-python-code-style, install_used=true, and outcome=success or failed.","safety_checklist":["Safety gate: Blocked for auto-install. Policy: block.","Do not auto-install. Inspect the source, dependencies, and permission surface first.","Review the repository and license before running third-party code.","Prefer a sandbox or isolated project when testing a new skill.","Start with the recommended command, then inspect generated files before committing changes.","Do not execute external side effects, payments, account changes, or credentialed actions without explicit user approval."],"verification_steps":["Open the skill documentation or SKILL.md and identify required setup.","Run the smallest safe example for the target task.","Confirm outputs match the task before allowing broader agent use.","Record any missing credentials, policy risks, or manual approvals needed."],"do_not_auto_install_when":["The repository or license cannot be reviewed.","The skill requires broad credentials or production account access.","The task involves regulated, private, or high-impact data without user approval."],"urls":{"web":"https://www.openagentskill.com/skills/probabl-ai-python-code-style","api":"https://www.openagentskill.com/api/agent/skills/probabl-ai-python-code-style","install_api":"https://www.openagentskill.com/api/skills/probabl-ai-python-code-style/install","repository":"https://github.com/probabl-ai/skills/tree/main/skills/python-code-style"},"meta":{"agent_friendly":true,"api_version":"1.0","generated_at":"2026-09-08T11:41:36.863Z"}}