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/ntaffzii/skill-agents/personalnpx skills add ntaffzii/Skill-Agents --skill personalgit clone --depth 1 https://github.com/ntaffzii/Skill-AgentsWrote 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/ntaffzii/skill-agents/personal)<a href="https://agentmods.dev/skills/ntaffzii/skill-agents/personal"><img src="https://agentmods.dev/badge/skills/ntaffzii/skill-agents/personal.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 | $0.00499 |
| Opus 5 | $0.00023 | $0.00249 |
| Sonnet 5 | $0.00009 | $0.00100 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
personal 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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Personal Skill Rules
Use this skill for instructions tied to one user, one machine, one vault, or one private workflow.
Purpose
skills/personal/ keeps personal context out of general-purpose skills. This prevents public skills from becoming noisy, brittle, or too specific to one setup.
What Belongs Here
- Personal writing preferences
- Local machine paths
- Private project conventions
- Personal Obsidian vault rules
- Private API or service usage notes without secrets
- Repeated workflows that only one user needs
What Does Not Belong Here
- Secrets, tokens, passwords, or private keys
- Generic engineering practices that belong in
engineering/ - Team-wide rules that deserve a stable shared skill
- Large reference dumps that should live in a separate private document
Rules
- Never store secrets in a personal skill.
- Keep local paths and user preferences clearly scoped.
- Do not let personal rules override explicit user instructions in a task.
- Promote only a cleaned, non-private version into public buckets.
Workflow
-
Classify the instruction
- If it helps only this user, keep it personal.
- If it helps a team or repo, consider a stable skill bucket.
- If it is executable behavior, consider
mcp-tools/.
-
Keep it scoped
- Write the smallest instruction that changes agent behavior.
- Avoid turning preferences into universal rules.
- Include examples only when they prevent ambiguity.
-
Protect private context
- Do not store secrets.
- Do not paste sensitive personal data unless explicitly needed.
- Prefer references to local files over copied private content.
-
Review promotion
- If a personal skill becomes broadly useful, promote a cleaned version to a public bucket.
- Remove user-specific paths, names, secrets, and assumptions before promotion.
Verification
- Confirm the skill does not contain secrets.
- Confirm the instruction is personal rather than broadly reusable.
- Confirm any local paths are intentional.
What ships with it
3 files 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.
- 6d ago First seen · 72 lines · 46 tokens per session scan A 1e9221048872
personal is a skill published in the GitHub repository ntaffzii/Skill-Agents (4 stars, last pushed 3d ago), licensed MIT. It adds 46 tokens to every session and 499 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 2026-08-31.
Other skills, from other repositories
honcho
Configure and troubleshoot Honcho memory for Hermes.
mem0-dream
Consolidates stored memories by merging duplicates, resolving contradictions, and pruning stale entries. Use when memory count is high, search results feel noisy or repetitive, or periodic cleanup is needed to maintain memory quality.
mem0-tour
Browses all stored memories grouped by category with full content display. Use when reviewing all project memories, exploring stored knowledge, onboarding to a project, or getting an overview of captured decisions, conventions, and learnings.
mem0-vercel-ai-sdk
Mem0 provider for Vercel AI SDK (@mem0/vercel-ai-provider). TRIGGER when: user mentions "vercel ai sdk", "@mem0/vercel-ai-provider", "createMem0", "retrieveMemories", "addMemories", "getMemories", "searchMemories", "mem0 vercel", "AI SDK provider", "AI SDK memory", or is using generateText/streamText with mem0. Also…
mem0-cli
Mem0 CLI -- the command-line interface for mem0 memory operations. TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli", "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get, mem0 init, mem0…
mem0-remember
Stores a memory verbatim from user input with appropriate type classification and metadata. Use when the user says remember this, save this, store this, note that, or explicitly asks to record a decision, preference, convention, or learning.