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 skills add darellchua2/opencode-config-template --skill changelog-python-cliff-skillgit clone --depth 1 https://github.com/darellchua2/opencode-config-templateWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/darellchua2/opencode-config-template/changelog-python-cliff-skill)<a href="https://agentmods.dev/skills/darellchua2/opencode-config-template/changelog-python-cliff-skill"><img src="https://agentmods.dev/badge/skills/darellchua2/opencode-config-template/changelog-python-cliff-skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/darellchua2/opencode-config-template/changelog-python-cliff-skill"><img src="https://agentmods.dev/badge/skills/darellchua2/opencode-config-template/changelog-python-cliff-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 246 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
What 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 5.1 | $0.00028 | $0.02560 |
| Opus 5.5 | $0.00011 | $0.01024 |
| Sonnet 5.5 | $0.00006 | $0.00512 |
| Haiku 4.5 | $0.00003 | $0.00256 |
Grade A, and why
changelog-python-cliff-skill 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 1mo 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 — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What I do
I implement automated changelog generation for Python projects using git-cliff:
- Detect Python Project: Identify version source (
pyproject.toml,__init__.py,setup.py,setup.cfg) - Verify git-cliff: Check if git-cliff is installed and configured
- Configure cliff.toml: Generate Python-specific configuration with PEP 440 version support
- Generate Changelog: Run
git cliffto produce changelogs from conventional commits - Integrate with Release Workflow: Support
bump-my-version,semantic-release, or manual versioning
When to use me
Use this workflow when:
- You need to generate or update a
CHANGELOG.mdfor a Python project - You are preparing a release and want an automated changelog
- You want to configure git-cliff for a Python project with PEP 440 versioning
- You need CI/CD integration for changelog generation in Python projects
- You are using conventional commits and want structured release notes
Prerequisites
- Python project with git repository
- git-cliff installed (
cargo install git-cliffor download from releases) - Conventional commits in git history (see
git-semantic-commitsskill) - Version defined in
pyproject.toml,__init__.py,setup.py, orsetup.cfg
Steps
Step 1: Detect Python Project
Verify this is a Python project and identify the version source:
[ -f pyproject.toml ] && echo "pyproject.toml found"
[ -f setup.py ] && echo "setup.py found"
[ -f setup.cfg ] && echo "setup.cfg found"
find . -name "__init__.py" -path "*/src/*" -o -name "__init__.py" -path "*/pkg/*" | head -5
Extract the current version:
grep -oP 'version\s*=\s*"\K[^"]+' pyproject.toml 2>/dev/null
grep -oP '__version__\s*=\s*"\K[^"]+' src/**/__init__.py 2>/dev/null
Step 2: Verify git-cliff Installation
Check if git-cliff is available:
git cliff --version
If not installed, guide installation:
cargo install git-cliff
# or download binary from https://github.com/orhun/git-cliff/releases
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.
- 1mo ago First seen · 299 lines · 28 tokens per session scan A 4df0cc9a105b
changelog-python-cliff-skill is a skill published in the GitHub repository darellchua2/opencode-config-template (6 stars, last pushed 28d ago), licensed Apache-2.0. It adds 28 tokens to every session and 2,560 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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