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 painhardcore/pstack --skill principle-boundary-disciplinegit clone --depth 1 https://github.com/painhardcore/pstackWrote 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/painhardcore/pstack/principle-boundary-discipline)<a href="https://agentmods.dev/skills/painhardcore/pstack/principle-boundary-discipline"><img src="https://agentmods.dev/badge/skills/painhardcore/pstack/principle-boundary-discipline.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00046 | $0.00378 |
| Opus 5 | $0.00023 | $0.00189 |
| Sonnet 5 | $0.00009 | $0.00076 |
| Haiku 4.5 | $0.00005 | $0.00038 |
Grade A, and why
principle-boundary-discipline 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 6d 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-boundary-discipline — 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
Boundary Discipline
Place validation, type narrowing, and error handling at system boundaries. Trust internal code unconditionally. Business logic lives in pure functions; the shell is thin and mechanical.
Why: Scattered validation is noisy, redundant, and gives a false sense of safety. Validate data once at the boundary. Keep logic out of framework wiring so it can be tested without the framework.
The pattern:
- At boundaries (CLI args, config files, external APIs, network protocols): validate, return errors, handle defensively.
- Inside the system: typed data, error propagation, no re-validation. Trust the types.
- Across the boundary. Expose domain concepts, not the boundary's private representation. Keep general-purpose mechanism inside and special-purpose policy at the edge.
Applications:
Validation and error handling:
- Validate config at parse time (the boundary), not inside business logic
- Parse raw data into domain types at the boundary
- Do not re-export transport, storage, framework, or wire types through the public surface
- No redundant nil checks deep in call chains if the boundary already validated
Code organization:
- Business logic in pure functions with no framework dependencies
- Parse functions: pure transforms from raw bytes to typed state
- Prompt construction: structured state in, string out
- Scoring and assessment: pure transforms from state to results
The tests:
- "Is this data crossing a system boundary right now?" If not, validation is redundant.
- "Can this be a pure function that the shell just calls?" If yes, extract it.
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.
- 6d ago First seen · 34 lines · 46 tokens per session scan A 3fee7ce89a74
principle-boundary-discipline is a skill published in the GitHub repository painhardcore/pstack (1 stars, last pushed 10d ago), licensed MIT. It adds 46 tokens to every session and 378 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-boundary-discipline, differing in 1 line, and is treated as a copy.
Other skills, from other repositories
codex-setup
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smart-rebase
Smart partial rebase for squash-merge repositories. Auto-detect which commits to keep/drop when base branch was squash-merged into target. Use when: user says 'rebase', 'partial rebase', 'base already merged', 'smart rebase', or /smart-rebase. Not for: simple git rebase (the developer runs it — Claude never executes…
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Post-development recap document generator. Use when: AI/Codex has implemented a feature and the user needs a guided walkthrough of what changed and why, with blind-spot detection and anticipated questions. Not for: Q&A follow-up (use /recap-ask), technical share-out for teammates (use /tech-brief), or generic code…
runbook
Generate and update feature release runbooks from existing docs and codebase. Use when: creating operational runbook, release handbook, deployment checklist, pre-release preparation. Not for: incident response (v2), code review (use codex-code-review), architecture design (use architecture).
test-review
Test coverage review via Codex exec. Use when: reviewing test sufficiency, identifying coverage gaps, test quality audit. Not for: generating tests (use codex-test-gen), code review (use codex-code-review). Output: coverage analysis + gap report.
debug
Interactive debugging workflow with hypothesis-driven probe loop. Use when: unknown bugs, script errors, silent failures, troubleshooting. Not for: known bugs (use bug-fix), GitHub issue analysis (use issue-analyze), code understanding (use code-explore). Output: debug report with probe journal + root cause + fix.