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 rainmanjam/poka-yoke --skill designgit clone --depth 1 https://github.com/rainmanjam/poka-yokeWrote 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/rainmanjam/poka-yoke/design)<a href="https://agentmods.dev/skills/rainmanjam/poka-yoke/design"><img src="https://agentmods.dev/badge/skills/rainmanjam/poka-yoke/design/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/rainmanjam/poka-yoke/design"><img src="https://agentmods.dev/badge/skills/rainmanjam/poka-yoke/design.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 | $0.00034 | $0.01361 |
| Opus 5 | $0.00017 | $0.00681 |
| Sonnet 5 | $0.00007 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
design 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 9d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design: Getting the Shape Right First
An interface is a promise about how something will be used. Once it has callers, changing it costs a migration, so the cheapest time to get the shape right is now, before anything depends on it.
The disciplines are the same as everywhere else. What changes is that you are choosing rather than repairing, so there is no existing consistency to respect and no cost to doing it well.
Start from the call site
Write the code that will use the thing before writing the thing. A signature that looks reasonable in isolation often reads terribly at the point of use:
report = build(data, True, False, None, 30)
Nothing at that call site says what any argument means. The design problem is visible from the caller and invisible from the definition, which is why the caller is where to start.
The same call with the shape fixed:
report = build(rows, include_inactive=True, timeout=Seconds(30))
Keyword arguments at the boundary, defaults for what is usually right, and a name on every value whose meaning is not obvious from its type.
Parameters
Order by how often they vary. What the caller always supplies goes first; what rarely changes gets a default and goes last.
Make booleans keyword-only. A positional True at a call site is unreadable, and two
adjacent booleans are worse: nothing stops a caller transposing them, and nothing detects it
afterwards. If a function takes more than one flag, consider whether it is really two
functions.
Watch adjacent parameters of the same type. def transfer(src: str, dst: str) accepts its
arguments in the wrong order without complaint. Either make them keyword-only or give the two
concepts distinct types.
Prefer few parameters to many. More than about four suggests the function is doing several things, or that some of the parameters travel together and want to be one object.
Return shapes
Return the thing, not a status. A function that computes rows should return rows. A count,
a boolean or None forces the caller to ask a second question.
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.
- 9d ago First seen · 132 lines · 34 tokens per session scan A 1e16fbd624da
design is a skill published in the GitHub repository rainmanjam/poka-yoke (22 stars, last pushed 7d ago), licensed MIT. It adds 34 tokens to every session and 1,361 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
Nullability Contract Review
Detect null/undefined/empty handling gaps where callers or consumers may receive unexpected nullish values.
skill-audit
Audit codebases for quality, consistency, and broken patterns — use for pre-release or tech debt review.
brooks-sweep
Full-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution. Drawing on twelve classic engineering books. Triggers when: user…
critical-code-reviewer
Rigorously review code or pull requests for correctness, security, accessibility, maintainability, tests, and edge cases. Use when users request a critical code review, want a guided walkthrough of findings, need implementer-facing feedback, or want to prepare, create, or submit a GitHub pull request review.
second-pass-review
Independent audit of sanitized specs in workspace/output/. Three parallel LLM-based reviewer roles check structural leakage, content contamination, and behavioral completeness. Run AFTER Layer 5 sanitization, BEFORE implementation handoff.
check-pr
Read-only inspection of a single GitHub PR lifecycle — checks CI, review threads, description sync, and mergeability, and returns PASS or FAIL with per-gate findings. Never invokes the merge button. Use when verifying a PR is ready to merge, polling lifecycle progress, checking mergeability, or babysitting a GitHub PR…