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/lilmgenius/paperthin/hatenpx skills add LilMGenius/paperthin --skill hategit clone --depth 1 https://github.com/LilMGenius/paperthinWhat 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 | $0.00079 | $0.00540 |
| Opus 5 | $0.00039 | $0.00270 |
| Sonnet 5 | $0.00016 | $0.00108 |
| Haiku 4.5 | $0.00008 | $0.00054 |
Grade A, and why
hate 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 3d 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.
What it actually says
Refuse to be nice to the plan — return the one objection that could kill it and the cheapest shot that proves it matters.
Goal
hate asks "what would someone who wants this to fail attack first?" (validity). It attacks the whole plan — not one fact or one line, but the load-bearing structure — and collapses the attack to a single root. The highest-value output is never a checklist — it's one objection plus the cheaper experiment hiding inside the elaborate plan.
Workflow
- Pin the load-bearing assumption(s) — what must hold for the whole thing to stand.
- Attack on whatever axes apply — the general ones first: a load-bearing fact that may be false, confabulation (a post-hoc story treated as ground truth), analogy-mistaken-for-isomorphism (structure assumed to transfer across domains where it doesn't), future-tense suture (the argument leans on a result that doesn't exist yet), and the sharpest — cites a principle but implements its opposite; and for empirical / research plans, leakage (no external ground-truth enters the validation independently) and statistical power / family-wise α (a true hypothesis auto-failing from uncorrected tests; a near-zero-power condition that rubber-stamps regardless of truth).
- Collapse the findings to the single root objection — the one whose failure makes the others moot.
- Find the first nail — the cheapest falsification of the load-bearing assumption: the check (in time / cost / sample) that could kill it before the expensive program runs.
- Return
{ root, first_nail }— not a list.
Rules
- Attack, don't improve — improving is a different reflex.
- Own the synthesis — many axes may fire, but collapse them to the single load-bearing root; return that, never a list.
Verification
Before finishing:
- The root is genuinely load-bearing — the plan falls without it.
- The first nail is genuinely cheaper than the plan it would pre-empt.
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.
- 3d ago First seen · 32 lines · 79 tokens per session scan A 57252bb878e7
hate is a skill published in the GitHub repository LilMGenius/paperthin (999 stars, last pushed 15d ago), licensed MIT. It adds 79 tokens to every session and 540 once invoked, about $0.0004 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.
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