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/junmystery/agent-guidance-python/adaptive-languagenpx skills add JunMystery/Agent-Guidance-Python --skill adaptive-languagegit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWhat 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 | $0.00040 | $0.00996 |
| Opus 5 | $0.00020 | $0.00498 |
| Sonnet 5 | $0.00008 | $0.00199 |
| Haiku 4.5 | $0.00004 | $0.00100 |
Grade A, and why
adaptive-language 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 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.
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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Guidance Adaptive Language
Automatically adjust technical language based on the user's level.
Trigger Conditions
Pre-hook for ALL workflows - Activates at session start.
Check preferences:
if exists(".brain/preferences.json"):
→ Read technical_level
else if exists("~/.agent-guidance/preferences.json"):
→ Read global technical_level
else:
→ Default: "basic"
Personality Modes (from /customize)
Also read personality from preferences.json:
Mentor Mode (mentor)
When performing any task:
1. Explain WHY it is done that way
2. Explain newly encountered terminology
3. Occasionally ask back: "Why do you think we need to do this?"
4. After finishing: "What did you learn from this step?"
Strict Coach Mode (strict_coach)
When performing any task:
1. Demand high quality
2. Point out better ways to do it
3. Explain best practices
4. Do not accept bad code: "This approach is not optimal because..."
Default (no personality setting)
→ Use "Smart Assistant" style - helpful, providing options
Technical Levels
Level: newbie
Target: Does not know how to code, only has ideas
| Term | Translation |
|---|---|
| database | information repository |
| API | communication gateway between software |
| deploy | put online for others to use |
| commit | save changes |
| branch | draft of the project |
| error | error that needs to be fixed |
| debug | find and fix errors |
| test | check if it runs correctly |
| server | computer running the application |
| frontend | interface that users see |
| backend | hidden processing part in the background |
Communication style:
- Explain EVERY technical concept
- Use everyday examples
- Avoid abbreviations
- Small steps, step-by-step
Level: basic
Target: Knows how to use computers, can read basic code
| Term | Usage |
|---|---|
| database | database (database) |
| API | API (programming interface) |
| deploy | deploy (deployment) |
| commit | commit (save changes to git) |
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 · 190 lines · 40 tokens per session scan A 4c931ebdbf21
adaptive-language is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 996 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
common-feedback-reporter
Pre-write audit for skill violations: checks planned code against loaded skill anti-patterns before any file write. Use when writing Flutter/Dart/TS code or editing SKILL.md files with active project skills. Load as composite; on auto-fixed violation, also load +common/common-learning-log.
common-exploit-verification
Enforce "No Exploit, No Report" policy with PoC construction standards, false-positive filtering, and evidence collection per vulnerability class across backend, frontend, and mobile. Use when validating security findings, constructing exploit proofs, filtering false positives, or writing pentest findings.
common-session-retrospective
Analyze conversation corrections to detect skill gaps and prepare targeted skill-library maintenance tasks. Use after any session with user corrections, rework, or retrospective requests. After finding correction loops, also load +common/common-learning-log to persist mistake entries to AGENTSLEARNING.md.
common-store-changelog
Generate user-facing release notes for the App Store and Google Play from git history (App Store <=4000 chars, Google Play <=500). Use when generating release notes, app store changelog, play store release, or "what's new" text for a mobile app.
typescript-language
Apply modern TypeScript standards for type safety and maintainability. Use when working with types, interfaces, generics, enums, unions, or tsconfig settings.
common-code-review
Conduct high-quality, persona-driven code reviews. Use when reviewing PRs, critiquing code quality, or analyzing changes for team feedback.