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 hyhmrright/logic-lens --skill logic-explaingit clone --depth 1 https://github.com/hyhmrright/logic-lensWrote 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/hyhmrright/logic-lens/logic-explain)<a href="https://agentmods.dev/skills/hyhmrright/logic-lens/logic-explain"><img src="https://agentmods.dev/badge/skills/hyhmrright/logic-lens/logic-explain/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/hyhmrright/logic-lens/logic-explain"><img src="https://agentmods.dev/badge/skills/hyhmrright/logic-lens/logic-explain.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00171 | $0.00708 |
| Opus 5.5 | $0.00068 | $0.00283 |
| Sonnet 5.5 | $0.00034 | $0.00142 |
| Haiku 4.5 | $0.00017 | $0.00071 |
Grade A, and why
logic-explain 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 1mo 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logic-Lens — Execution Explain
Setup
Use lazy loading per ../_shared/common.md §13:
- Read
../_shared/common.mdonly for language, report header variants, scope routing, and loading budget. - Read only the relevant step in
logic-explain-guide.mdas you reach it. - Load
../_shared/semiformal-guide.md,../_shared/semiformal-checklist.md, and../_shared/report-template.mdon demand when the current step needs them.
Note: logic-risks.md is intentionally skipped — logic-explain does not produce L-code findings, and Remedy is intentionally out of scope for this mode. If the trace reveals a bug, stop and recommend logic-review or logic-locate. When handing off, do not discard work already done — present the premises established and trace steps completed under a "Partial trace context (carry into next skill):" heading so the user can pass them directly to the follow-on skill.
Process
Step 0. Language + scope routing. Detect language per common.md §1. Confirm a single function + a single input scenario. If the user wants bug-finding without a scenario, hand off to logic-review.
Step 1. Entry point and scenario (guide Step 1) — name the function, the input scenario, and what the user is trying to understand.
Step 2. Build premises (guide Step 2) — resolve every non-obvious name, state the types of key variables at entry, note global/module state accessed.
Step 3. Produce step-by-step trace (guide Step 3) — numbered, interprocedural, active voice; cross function boundaries whenever relevant to the user's scenario. Keep the trace scenario-bound; do not branch into alternative paths unless they explain the user's confusion.
Step 4. Highlight non-obvious behavior (guide Step 4) — name resolutions, implicit coercions, hidden side effects; the "gotchas" the casual reader would miss.
Step 5. Summarize actual vs. assumed (guide Step 5) — one sentence each; this is the core value for the user.
Mode line in report: Execution Explain (Chinese: 执行解释).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 46 lines · 171 tokens per session scan A 5caaf33f77e6
logic-explain is a skill published in the GitHub repository hyhmrright/logic-lens (25 stars, last pushed 24d ago), licensed MIT. It adds 171 tokens to every session and 708 once invoked, about $0.0007 per session on Opus 5.5. 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
ai-development-guide
Applies language-agnostic and backend technical decision criteria, anti-pattern detection, debugging, and quality gates. Use when reviewing general/backend implementation choices, code smells, failures, or implementation completeness.
review-all
Multi-agent code review for diffs (project-agnostic). Covers standards, bugs, security, DRY, smells, perf, tests, API contracts, a11y/i18n. Verifies each finding to eliminate false positives. Use for /review-all, pre-PR/pre-commit review, or auditing uncommitted/staged changes.
skeptic
Adversarial code reviewer for Bug Hunter. Rigorously challenges each reported bug to determine if it's real or a false positive. Uses doc-lookup (Context Hub + Context7) to verify framework claims before disproval. The immune system that kills false positives.
debug
Systematic bug investigation with a five-phase framework: reproduce, narrow, diagnose, fix, verify. Supports automated regression bisect via --regression flag. Produces a structured debug report with root cause analysis, regression test, and CQ/Q self-evaluations.
Refactor-Claim Audit リファクタ完了主張の検証
A review check for claims that a migration or refactor is complete, including claims about large reductions or unchanged behavior.
river-review-code
A general code-review skill that checks readability, maintainability, and type safety, with routing for several specialized checks.