Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/sequenzia/agent-alchemy/release-python-packagenpx skills add sequenzia/agent-alchemy --skill release-python-packagegit clone --depth 1 https://github.com/sequenzia/agent-alchemyWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00024 | $0.01858 |
| Opus 5 | $0.00012 | $0.00929 |
| Sonnet 5 | $0.00005 | $0.00372 |
| Haiku 4.5 | $0.00002 | $0.00186 |
Grade A, and why
release scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Release Manager
Execute a complete pre-release workflow for Python packages using uv and ruff. This command automates version calculation, changelog updates, and tag creation.
Arguments
$ARGUMENTS- Optional version override (e.g.,1.0.0). If not provided, version is calculated from changelog entries.
Workflow
Execute these 9 steps in order. Fail fast: Stop immediately if any verification step fails.
Step 1: Pre-flight Checks
Run these checks and stop if any fail:
# Check current branch
git branch --show-current
- Must be on
mainbranch. If not, stop and report: "Release must be run from the main branch. Currently on: {branch}"
# Check for uncommitted changes
git status --porcelain
- Must have clean working directory. If output is not empty, stop and report: "Working directory has uncommitted changes. Please commit or stash them first."
# Pull latest changes
git pull origin main
- Report any merge conflicts and stop if they occur.
Step 2: Run Tests
Execute the test suite:
uv run pytest
- If tests fail, stop and report the failure output
- If tests pass, report: "All tests passed"
Step 3: Run Linting
Execute linting checks:
uv run ruff check
uv run ruff format --check
- If either command fails, stop and report the issues
- If both pass, report: "Linting and formatting checks passed"
Step 4: Verify Build
Build the package:
uv build
- If build fails, stop and report the error
- If build succeeds, report: "Package builds successfully"
Step 5: Changelog Update Check
All verification checks have passed. Before calculating the version, offer to run the changelog-agent to ensure the [Unreleased] section is up-to-date.
Use AskUserQuestion:
Would you like to run the changelog-agent to update CHANGELOG.md before proceeding?
This will analyze git commits since the last release and suggest new changelog entries.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 288 lines · 24 tokens per session scan A c89bd96d5133
release is a skill published in the GitHub repository sequenzia/agent-alchemy (43 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 1,858 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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