Paperthin is a collection of low-level design patterns that coding agents can apply as repeatable checks and actions during software work. It is for people using agents such as Claude Code, Codex, Cursor, or other supported tools, and its catalogue entries package the patterns as skills, an instruction, and a plugin.
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 LilMGenius/paperthin --skill sipgit clone --depth 1 https://github.com/LilMGenius/paperthinWrote 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/lilmgenius/paperthin/sip)<a href="https://agentmods.dev/skills/lilmgenius/paperthin/sip"><img src="https://agentmods.dev/badge/skills/lilmgenius/paperthin/sip/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/lilmgenius/paperthin/sip"><img src="https://agentmods.dev/badge/skills/lilmgenius/paperthin/sip.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00055 | $0.00702 |
| Opus 5.5 | $0.00022 | $0.00281 |
| Sonnet 5.5 | $0.00011 | $0.00140 |
| Haiku 4.5 | $0.00006 | $0.00070 |
Grade A, and why
sip 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- sip — 100% identical
How it starts
The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Taste your own cooking: the moment you finish making something, check it with the very skills this repo ships before you serve it.
Goal
A reminder buried in docs ("remember to verify") won't reliably fire in a fresh session. sip makes the recursive self-improvement loop a triggered habit: right after any create or change, run our own skills on the result — the clean checks and the true ones — so quality doesn't ride on the author's biased in-session judgment.
Workflow
- Spot the trigger: you just created or changed an artifact or skill and are about to call it done, commit, or hand it off.
- Cold-read it — run
showeron the artifact (fresh-eyes comprehension / handoff check). - Verify it's true — if the artifact asserts a reality-grounded claim, run
factchk; if it defines an eval, metric, or experiment, runmandela. Skip when it has neither. - Check consistency — run
ssotizein audit mode across the repo for anything the change duplicated or contradicted; execute its consolidation plan only after approval. - Detool portability claims — run
detoolonly when the artifact claims portability, tool-neutrality, stack-agnostic durability, or cross-agent reuse. Skip when it is provenance, operational notes, a tool-targeted runbook, or does not claim portability. - Tidy —
re0the changed docs so the result reads as a clean v0, not a patch over a draft. - Apply the findings here, then serve it.
Rules
- Trigger on your OWN output, right after making it — that's when bias is highest and a check is cheapest.
- Use the skills; don't re-implement them —
showerfor clarity,factchk/mandelafor truth,ssotizefor SSOT,detoolfor portability claims,re0for cleanup.siporchestrates and routes findings back to the author session to fix; the skills do the work. - Skip what plainly doesn't apply, or any check whose skill isn't installed — run only what's present.
factchk/mandelafire only when there is a claim or an eval;detoolfires only when the artifact claims portability, tool-neutrality, stack-agnostic durability, or cross-agent reuse; a one-line prose tweak may need only a consistency check. Say what you skipped and why. - Stop at the artifact —
sipnever touches git or makes commits. - Chain only model-invoked skills; a user-invoked skill (marked
disable-model-invocation) is a human's to fire deliberately, sosipmust not call one.
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 · 37 lines · 55 tokens per session scan A e92f71a75197
sip is a skill published in the GitHub repository LilMGenius/paperthin (1,278 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 702 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
second-opinion
GPT (GPT-6 Astra by default) as advisor, adversarial reviewer or judge through headless codex exec, always read-only; never an implementer. Modes: advise (independent read on a plan, diff or design, beside Claude's own view, with follow-ups), review (Codex's built-in reviewer on uncommitted work, a branch or a…
clean-code
Use when writing, editing, reviewing, testing, planning, or refactoring code in any language or framework; creating files or deciding where code and folders belong; designing or changing module boundaries, layers, and dependencies; starting a new project; auditing or cleaning up an existing one; or compressing agent…
insistir
Run a task through an agent team where every worker's output is cross-reviewed, judged by a second provider and fixed by fresh agents until APPROVED.
solid-interface-segregation
This skill should be used when the user asks about "interface segregation", "ISP", mentions "fat interfaces", discusses clients forced to depend on methods they don't use, or wants to design smaller, focused interfaces.
solid-single-responsibility
This skill should be used when the user asks about "single responsibility", "SRP", mentions "separation of concerns", discusses classes doing too much, or wants to identify when a class has multiple reasons to change.
branch-review
This skill should be used when the user asks to "review a branch", "compare code quality", mentions "branch review", "code quality scorecard", discusses comparing old vs new code, or wants a scored assessment of changes on a feature branch.