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 pproenca/dot-skills --skill library-reference-distillationgit clone --depth 1 https://github.com/pproenca/dot-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/skills/pproenca/dot-skills/library-reference-distillation)<a href="https://agentmods.dev/skills/pproenca/dot-skills/library-reference-distillation"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/library-reference-distillation/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/pproenca/dot-skills/library-reference-distillation"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/library-reference-distillation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00217 | $0.01790 |
| Opus 5 | $0.00109 | $0.00895 |
| Sonnet 5 | $0.00043 | $0.00358 |
| Haiku 4.5 | $0.00022 | $0.00179 |
Grade A, and why
library-reference-distillation 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 6d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Library-Reference Distillation — Archetype Playbook
Methodology distillation of the conventions that hold across shipped library-reference distillations in this repo — the archetype that turns one external library into an idiomatic-usage rule pack. Not a generator; a constraint set on the editorial decisions /dev-skill:new cannot make for you.
This is the archetype layer that sits above /dev-skill:new and /dev-skill:ingest. The generator handles the structural shell. This skill handles the four decisions you re-make for every library-ref skill: where to source from, how to pin against version drift, how to shape categories and rules, and how to keep the metadata an honest checksum.
When to Apply
Use this skill when:
- Starting a new library-ref distillation (the library has docs and a stable surface area you want to capture as idiomatic rules)
- Evolving an existing library-ref skill against a new upstream release or major version bump
- Reviewing a draft library-ref skill that "feels like the docs rewritten"
- Picking categories and a prefix scheme for a new skill and the choices feel arbitrary
- Deciding whether to pin the upstream version in
SKILL.mdheading or only inmetadata.json - Refreshing a skill where you suspect rule drift from upstream (the
openai-codex-rust-patternslesson: codex-rs drifts hard between snapshots)
This skill is not for:
- Code-atlas distillations (e.g.,
openai-codex-rust-patterns,opencode-ts,nextjs-ppr-patterns) — sources are a real repo at a pinned HEAD, not upstream docs. Sibling archetype playbook still to be extracted. - Methodology distillations (e.g.,
radical-simplification,deterministic-metric-design) — sources are named humans and their canon, not a library. - Scaffolders (e.g.,
expo-design-system-scaffolder) — composition workflow, not a rulebook.
How to Use
The four categories are orthogonal decisions you make once per skill. Match the symptom to the move:
| Symptom | Reach for | First rule to read |
|---|---|---|
| Don't know where to mine rules from | Source | source-priority-ladder |
| Rules feel like API restatement, not load-bearing | Source (failure-gap) | source-failure-gap |
| Library changes fast — skill will rot | Pin | pin-by-velocity |
| Existing skill is drifting from upstream | Pin (refresh) | pin-refresh-vs-head |
| Categories feel arbitrary | Shape | shape-category-ladder |
| When-to-Apply does not trigger reliably | Shape (When-to-Apply) | shape-when-to-apply-template |
| Cite list and rule sources have drifted | Meta | meta-references-checksum |
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- AGENTS.md 2.9 KB
- metadata.json 1.3 KB
- references/_sections.md 3.4 KB
- references/meta-references-checksum.md 2.4 KB
- references/pin-by-velocity.md 2.4 KB
- references/pin-refresh-vs-head.md 2.4 KB
- references/shape-category-ladder.md 2.6 KB
- references/shape-when-to-apply-template.md 2.9 KB
- references/source-failure-gap.md 2.2 KB
- references/source-priority-ladder.md 2.3 KB
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.
- 6d ago First seen · 83 lines · 217 tokens per session scan A b008b50bd59f
library-reference-distillation is a skill published in the GitHub repository pproenca/dot-skills (205 stars, last pushed 24d ago), licensed MIT. It adds 217 tokens to every session and 1,790 once invoked, about $0.0011 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 2026-09-03.
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