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/rish-modi/career-agent/coding-prepnpx skills add Rish-Modi/career-agent --skill coding-prepgit clone --depth 1 https://github.com/Rish-Modi/career-agentWhat 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 | $0.00000 | $0.03221 |
| Opus 5 | $0.00000 | $0.01611 |
| Sonnet 5 | $0.00000 | $0.00644 |
| Haiku 4.5 | $0.00000 | $0.00322 |
Grade A, and why
coding-prep 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 yesterday.
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.
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.
- yesterday First seen · 223 lines · 0 tokens per session scan A 3b5ee9cd556a
coding-prep is a skill published in the GitHub repository Rish-Modi/career-agent (2 stars, last pushed 2mo ago), with no licence file. It costs nothing until one of its globs matches a file; then it loads 3,221 tokens. 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 2026-08-31.
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以"程序员鱼皮"的身份、口吻、思维方式回答问题。鱼皮是前腾讯全栈工程师、全网200万+粉丝的AI+编程知识博主、科技公司鱼鸢网络CEO、编程导航创始人。 当用户想要以鱼皮的视角获得编程学习建议、求职指导、项目选型、技术方向判断、创业经验、自媒体运营建议、AI编程实战指导时使用此技能。 也适用于用户明确要求"用鱼皮的风格"或"像鱼皮一样"回答的场景。 覆盖的典型问题包括：编程学习路线、简历怎么写、要不要接某个offer、该学什么技术、怎么做开源、怎么做自媒体、AI时代程序员怎么办、创业踩过哪些坑。.
propose
Draft a Kauri decision for human review before recording it. This skill should be used proactively — when the user makes, confirms, or rejects a non-trivial choice (picking a library, rejecting an approach, choosing an architecture, resolving a trade-off, establishing a convention), invoke this skill to draft a…
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A staff-engineer promotion packet — scope, the proof moments, the artifacts, and the impact that clears the bar. Built as a decision-grade career deck for manager, calibration committee.
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A year-end self-review for a product manager — the role, the outcomes, the learning, and the ask, all evidence-backed. Built as a decision-grade career deck for manager, review committee.
consult
Consult existing Kauri decisions before planning or implementing changes. Use BEFORE making architectural choices, changing conventions, picking libraries, or modifying files that might be covered by a recorded decision.
review
Review recent code changes against Kauri decisions. Use after implementing changes, before committing, during PR review, or when asked "does this look right?" to verify consistency with recorded decisions.