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/ykdojo/claude-code-tips/half-clonenpx skills add ykdojo/claude-code-tips --skill half-clonegit clone --depth 1 https://github.com/ykdojo/claude-code-tipsWhat 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 | $0.00026 | $0.00359 |
| Opus 5 | $0.00013 | $0.00179 |
| Sonnet 5 | $0.00005 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade B, and why
half-clone scanned grade B with 1 finding 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
1. Get the current session ID and project path: `tail -1 ~/.claude/history.jsonl | jq -r '[.sessionId, .project] | @tsv'` The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 22 lines · 26 tokens per session scan B dfed2360f59a
half-clone is a skill published in the GitHub repository ykdojo/claude-code-tips (10,005 stars, last pushed 2d ago), with no licence file. It adds 26 tokens to every session and 359 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
architecture-elevation
Validate the architectural ALTITUDE of a stated root cause or proposed fix before peer review or implementation. Interrogates the frame itself — whether the concern exists because of an abstraction that could be removed — before mapping enforcement sites within the concern. Tests whether a different boundary could…
architecture-docs
Generate or refresh /docs/architecture/ — the current-state source of architectural truth for this codebase, grounded in code and git history (NOT in .designs/). Produces an anchor-dense corpus (invariants.md, idioms.md, trust-boundaries.md, seams.md, subsystems/.md, history.md, gaps.md) plus a high-level overview…
github-issue
Creates well-documented GitHub issues (or comments on existing ones) from problems discussed in conversation. Investigates the codebase to map affected layers, files, and data flow, then writes up findings with acceptance criteria — without prescribing fixes. Use when a conversation has identified a problem that needs…
rootcause-review
Perform scientific peer review of a rootcauseanalysis.md document, validating all claims with independent verification. Appends review findings without modifying original content.
agentic-skill-eval
Evaluates a skill library to identify which SKILL.md files would produce valuable autonomous agents when converted via /formula-create. Use when assessing a repository of skills for agent creation candidates, prioritizing which skills to convert to formulas, or auditing an existing agent roster for gaps.
improve-agent
Improve an agent's formula TOML based on post-execution learnings. Use after a formula run required manual intervention, produced incorrect artifacts, or left cleanup work for the operator. Classifies the failure type, scans for sibling vulnerabilities, selects the appropriate fix pattern, and surgically inserts…