Borrowing it
Nothing to install: this file belongs to iannuttall/png2svg. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/iannuttall/png2svg/main/AGENTS.mdgit clone --depth 1 https://github.com/iannuttall/png2svgWrote 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/instructions/iannuttall/png2svg/agents-md)<a href="https://agentmods.dev/instructions/iannuttall/png2svg/agents-md"><img src="https://agentmods.dev/badge/instructions/iannuttall/png2svg/agents-md/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/instructions/iannuttall/png2svg/agents-md"><img src="https://agentmods.dev/badge/instructions/iannuttall/png2svg/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00980 | $0.00980 |
| Opus 5 | $0.00490 | $0.00490 |
| Sonnet 5 | $0.00196 | $0.00196 |
| Haiku 4.5 | $0.00098 | $0.00098 |
Grade A, and why
png2svg AGENTS.md 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 9d 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.
This is a copy
91% identical to skills AGENTS.md — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Working on png2svg
This repo's product is the skill in skills/png2svg/. Everything else
exists to build, test and document it.
The design principle
There is no single algorithm that reconstructs every logo. Decomposition — how many shapes, what covers what, which coincidences are real design constraints — needs eyes on the image. So:
- the library makes every measurement deterministic and exact
- the agent decides what to measure, what overlaps what, and when to stop
Do not try to collapse that into a one-shot reconstruct command. Effort is
better spent making each primitive sharper, or moving a decision the agent
keeps re-deriving into a call it can make once.
Layout gotcha
The Python package lives at skills/png2svg/scripts/png2svg/ — inside the
skill, so the skill is self-contained. pyproject.toml points the build
backend there via tool.uv.build-backend.module-root. There is exactly
one copy. Never vendor a second one into src/; a drifting duplicate is
worse than either copy alone.
skills/png2svg/ the deliverable
SKILL.md workflow; keep under 500 lines / 5000 tokens
references/ loaded on demand — conventions, model, examples
scripts/png2svg/ the engine
scripts/*_template.py what an agent copies and edits
examples/ real per-image reconstruction scripts
tests/ ground-truth tests
Commands
uv sync
uv run pytest # must stay green
uv run png2svg --help
uvx --from skills-ref agentskills validate ./skills/png2svg
The bundled entry point must also work with nothing installed, since that is how the skill runs on someone else's machine:
uv run --no-project skills/png2svg/scripts/png2svg_cli.py --help
Testing: validate against ground truth
Synthesise something whose answer is known, then check the code recovers it. Render a gradient with known stops and refit it; fit a known cubic and compare control points; build a shape with known geometry and measure it back.
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.
- 9d ago First seen · 106 lines · 980 tokens per session scan A aae164fbb48b
png2svg AGENTS.md is an instructions file published in the GitHub repository iannuttall/png2svg (3 stars, last pushed 1mo ago), licensed MIT. It adds 980 tokens to every session, about $0.0049 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to skills AGENTS.md, differing in 8 lines, and is treated as a copy.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.