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/painhardcore/pstack/principle-minimize-reader-loadnpx skills add painhardcore/pstack --skill principle-minimize-reader-loadgit clone --depth 1 https://github.com/painhardcore/pstackWhat 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 | $0.00044 | $0.00437 |
| Opus 5 | $0.00022 | $0.00218 |
| Sonnet 5 | $0.00009 | $0.00087 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade A, and why
principle-minimize-reader-load 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 2d 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
98% identical to principle-minimize-reader-load — 1 line 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.
What it actually says
Minimize Reader Load
Maintainability is the work a reader must do to understand code. Track two axes:
- Layers to trace. How many indirections sit between the question and the answer.
- State to hold. How much hidden or mutable context the reader must keep in their head.
Why: Code is read far more than it is written. LOC, cyclomatic complexity, and "clean architecture" are proxies. Reader load is the thing that matters. The two axes are independent. A flat file with 50 globals can be as hard to reason about as a 6-layer adapter stack. Guard both. This is the human analog of Guard the Context Window: working memory is finite for readers too.
The pattern:
- Collapse layers that do not earn their keep: wrappers with one caller, adapters with no second implementation, indirection introduced for a future that never came. Inline them.
- Make adjacent layers change the abstraction. A layer that repeats the same methods and arguments adds reader load without compression. Collapse pass-through layers.
- Demand interface compression. A broad interface that hides little complexity makes readers learn both the surface and the implementation. Prefer boundaries that hide meaningful decisions.
- Shrink state scope: prefer pure functions (returns over mutations), locals over fields, fields over module state, and module state over globals. Derive instead of sync.
- Name the invariant at the boundary, not in every consumer, so the reader learns it once.
- Before adding a layer or a piece of state, ask: does this reduce reader load somewhere else by at least as much?
The test: Can a new reader answer "where does X come from?" and "what can change X?" in under 30 seconds? If not, cut layers or cut state.
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.
- 2d ago First seen · 23 lines · 44 tokens per session scan A 02f1bf8431cb
principle-minimize-reader-load is a skill published in the GitHub repository painhardcore/pstack (1 stars, last pushed 6d ago), licensed MIT. It adds 44 tokens to every session and 437 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to principle-minimize-reader-load, differing in 1 line, and is treated as a copy.
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