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 instructions/iannuttall/skills/agents-mdgit clone --depth 1 https://github.com/iannuttall/skillsWrote 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/skills/agents-md)<a href="https://agentmods.dev/instructions/iannuttall/skills/agents-md"><img src="https://agentmods.dev/badge/instructions/iannuttall/skills/agents-md.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 | $0.01019 | $0.01019 |
| Opus 5 | $0.00509 | $0.00509 |
| Sonnet 5 | $0.00204 | $0.00204 |
| Haiku 4.5 | $0.00102 | $0.00102 |
Grade A, and why
skills 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 5d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- png2svg AGENTS.md — 91% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Working on Ian's agent skills
Every public skill lives at skills/<name>/. Keep each installed folder
self-contained. Supporting tests, examples and private work belong outside
the skill folder.
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
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.
- 5d ago First seen · 112 lines · 1,019 tokens per session scan A a8a9206a1399
skills AGENTS.md is an instructions file published in the GitHub repository iannuttall/skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 1,019 tokens to every session, about $0.0051 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 2026-08-31.
Other instructions, from other repositories
png2svg AGENTS.md
Instructions for iannuttall/png2svg, covering working on png2svg, the design principle, layout gotcha, commands and testing: validate against ground truth.
png2svg CLAUDE.md
Instructions for iannuttall/png2svg, a project described as: Agent-guided PNG to SVG reconstruction for logos and icons. Clean geometry and gradients, not traced pixels.
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).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.