python-deploy

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Author repo skills-registry

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Deploy a Python project to the target environment. Runs pytest, builds the wheel, and pushes a deployment tag. Only invoke manua…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Pre-flight checks”, “Step 1: Abort if there are uncommitted changes”, “Step 2: Run the test suite”, “Step 3: Build the distribution package”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name python-deploy directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Pre-flight checks / Step 1: Abort if there are uncommitted changes / Step 2: Run the test suite” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Pre-flight checks

!git status --short

!git log --oneline -5

Deploy to: $ARGUMENTS

If $ARGUMENTS is empty, stop immediately. Report: "No environment specified. Invoke as: /python-deploy <environment> (e.g., /python-deploy staging or /python-deploy production)."

Step 1: Abort if there are uncommitted changes

Check the git status output above. If it shows any lines (modified, untracked, staged, or deleted files), stop here.

Report: "Deploy aborted: there are uncommitted changes. Commit or stash them before deploying to $ARGUMENTS."

A clean working tree shows no output from git status --short. Do not proceed unless the output is empty.

Step 2: Run the test suite

Run:

python -m pytest

If any tests fail, report the failing test names and count, then stop. Do not proceed.

If pytest is not installed, try:

python -m unittest discover

If neither is available, report that no test runner was found and stop. Do not deploy without running tests.

Step 3: Build the distribution package

Run:

python -m build

This requires the build package. If it is not installed, run:

pip install build

Then retry python -m build.

If the build fails, report the error output and stop.

On success, confirm the output: the dist/ directory should contain a .whl and a .tar.gz file.

Step 4: Create a deployment tag

Construct the tag name:

deploy-$ARGUMENTS-<YYYYMMDD>-<HHMMSS>

Use current UTC date and time. Example: deploy-staging-20260513-143207.

Run:

git tag deploy-$ARGUMENTS-<YYYYMMDD>-<HHMMSS>

Step 5: Push the tag

Run:

git push origin deploy-$ARGUMENTS-<YYYYMMDD>-<HHMMSS>

If the push fails, report the error and stop.

Step 6: Report success

Print a final summary:

Deploy initiated.
Environment: $ARGUMENTS
Tag: deploy-$ARGUMENTS-<YYYYMMDD>-<HHMMSS>
Time: <YYYY-MM-DD HH:MM:SS UTC>
Build artifacts: dist/

Source: davila7/claude-with-skills — distributed by TomeVault.

Fluxly profile Author and license come from source; runtime, permissions, and network are Fluxly detections or estimates

Fluxly category: DevOps
Author-declared agents: No explicit declaration found; this is not inferred or tested compatibility
Static check: 88 / 100 · heuristic scan, not runtime safety proof
Author / version / license: @tomevault-io · no license declared
Fluxly token estimate: Lean
Fluxly setup estimate: Plug-and-play
External API key: No requirement detected
Detected OS requirements: Unspecified
Runtime requirements: Python
Detected file/system behavior: Read-only
Write / modify
Detected network behavior: Local-only
Install commands: None (reference only)

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。

Output preview python-deploy.preview

The current SKILL.md does not define a fixed output example.

SKILL.md SKILL.md

## Pre-flight checks

!`git status --short`

!`git log --oneline -5`

---

Deploy to: $ARGUMENTS

If `$ARGUMENTS` is empty, stop immediately. Report: "No environment specified. Invoke as: /python-deploy <environment> (e.g., /python-deploy staging or /python-deploy production)."

### Step 1: Abort if there are uncommitted changes

Check the git status output above. If it shows any lines (modified, untracked, staged, or deleted files), stop here.

Report: "Deploy aborted: there are uncommitted changes. Commit or stash them before deploying to $ARGUMENTS."

A clean working tree shows no output from `git status --short`. Do not proceed unless the output is empty.

### Step 2: Run the test suite

Run:
```
python -m pytest
```

If any tests fail, report the failing test names and count, then stop. Do not proceed.

If pytest is not installed, try:
```
python -m unittest discover
```

If neither is available, report that no test runner was found and stop. Do not deploy without running tests.

### Step 3: Build the distribution package

Run:
```
python -m build
```

This requires the `build` package. If it is not installed, run:
```
pip install build
```

Then retry `python -m build`.

If the build fails, report the error output and stop.

On success, confirm the output: the `dist/` directory should contain a `.whl` and a `.tar.gz` file.

### Step 4: Create a deployment tag

Construct the tag name:
```
deploy-$ARGUMENTS-<YYYYMMDD>-<HHMMSS>
```

Use current UTC date and time. Example: `deploy-staging-20260513-143207`.

Run:
```
git tag deploy-$ARGUMENTS-<YYYYMMDD>-<HHMMSS>
```

### Step 5: Push the tag

Run:
```
git push origin deploy-$ARGUMENTS-<YYYYMMDD>-<HHMMSS>
```

If the push fails, report the error and stop.

### Step 6: Report success

Print a final summary:

```

…

Evidence boundary and execution chain

Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.

sections -> Pre-flight checks → Step 1: Abort if there are uncommitted changes → Step 2: Run the test suite → Step 3: Build the distribution package → Step 4: Create a deployment tag → Step 5: Push the tag
terms    -> If $ARGUMENTS is empty, stop immediately. · Check the git status output above. · Report: "Deploy aborted: there are uncommitted changes. · A clean working tree shows no output from git status --short. · If any tests fail, report the failing test names and count, then stop. · If neither is available, report that no test runner was found and stop. · This requires the build package. · Then retry python -m build.
files/cmd -> git status --short · git log --oneline -5 · $ARGUMENTS · build · python -m build · dist/ · .whl · .tar.gz
body sha256 -> da4a602d62e7

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

Pre-flight checks

Step 1: Abort if there are uncommitted changes

Step 2: Run the test suite

Step 3: Build the distribution package

Step 4: Create a deployment tag

Step 5: Push the tag

Step 6: Report success

Discussion