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/backnotprop/pstack/principle-minimize-reader-loadnpx skills add backnotprop/pstack --skill principle-minimize-reader-loadgit clone --depth 1 https://github.com/backnotprop/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 | $0.00445 |
| Opus 5 | $0.00022 | $0.00222 |
| Sonnet 5 | $0.00009 | $0.00089 |
| 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- principle-minimize-reader-load — 98% identical, 1 lines differ
- principle-minimize-reader-load — 94% identical, 2 lines differ
- principle-minimize-reader-load — 94% identical, 2 lines differ
- principle-minimize-reader-load — 92% identical, 4 lines differ
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 · 24 lines · 44 tokens per session scan A 480f4ddec29e
principle-minimize-reader-load is a skill published in the GitHub repository backnotprop/pstack (181 stars, last pushed 13d ago), licensed MIT. It adds 44 tokens to every session and 445 once invoked, about $0.0002 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…