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/aravindev/inkscape_mcp/releasenpx skills add aravindev/inkscape_mcp --skill releasegit clone --depth 1 https://github.com/aravindev/inkscape_mcpWrote 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/aravindev/inkscape_mcp/release)<a href="https://agentmods.dev/skills/aravindev/inkscape_mcp/release"><img src="https://agentmods.dev/badge/skills/aravindev/inkscape_mcp/release.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00040 | $0.01216 |
| Opus 5 | $0.00020 | $0.00608 |
| Sonnet 5 | $0.00008 | $0.00243 |
| Haiku 4.5 | $0.00004 | $0.00122 |
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 4d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cutting an inkscape-mcp release
A release is: bump version → commit → tag vX.Y.Z → push main + tag → the Release
workflow auto-creates the GitHub release → manually dispatch the Publish workflow to
push to PyPI. Confirm the target version with the user before starting if it isn't given.
1. Prerequisites
git checkout main && git pull --ff-only
git status --short # working tree should be clean (stash unrelated changes)
grep -n 'version = ' pyproject.toml # current version, two lines
2. Pre-release checks — lint, tests, security
The tag triggers the CI + Security workflows; a release must not ship red. Run these locally first and fix everything before bumping the version.
uv run ruff format --check . # formatting — run `uv run ruff format .` to fix
uv run ruff check . # lint
uv run pytest -q # tests
Security — audit third-party deps (mirrors what the Security workflow runs):
uv export --no-emit-project --format requirements-txt -o /tmp/req.txt
uv run --with pip-audit pip-audit -r /tmp/req.txt --disable-pip --strict
If pip-audit flags anything, bump the affected package(s) to a fixed (ideally the latest) version and re-audit until it reports "No known vulnerabilities found":
uv lock --upgrade-package <pkg> # one --upgrade-package per package
# then re-export + re-audit (above) to confirm clean
Transitive deps (e.g. joserfc, pydantic-settings) often have no Dependabot PR — bump
them here manually. Commit any format/lint and uv.lock fixes (as their own commit) so
main is green before you tag.
3. Bump the version
The version string lives in exactly three release-relevant locations. Set all three to the
new X.Y.Z:
pyproject.toml—[project]version(~line 7)pyproject.toml—[tool.fastmcp]version(~line 118)src/inkscape_mcp/__init__.py—__version__
Do not touch src/inkscape_mcp/transport.py — its version="1.0.0" is a docstring
example, not the real version.
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.
- 4d ago First seen · 125 lines · 40 tokens per session scan A 6f551737f2b3
release is a skill published in the GitHub repository aravindev/inkscape_mcp (55 stars, last pushed 3d ago), licensed MIT. It adds 40 tokens to every session and 1,216 once invoked, about $0.0002 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…