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/resciencelab/tryskills/clarifynpx skills add ReScienceLab/TrySkills --skill clarifygit clone --depth 1 https://github.com/ReScienceLab/TrySkillsWhat 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 | $0.00051 | $0.01564 |
| Opus 5 | $0.00026 | $0.00782 |
| Sonnet 5 | $0.00010 | $0.00313 |
| Haiku 4.5 | $0.00005 | $0.00156 |
Grade A, and why
clarify 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.
This is a copy
81% identical to clarify — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Identify and improve unclear, confusing, or poorly written interface text to make the product easier to understand and use.
MANDATORY PREPARATION
Invoke /impeccable — it contains design principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no design context exists yet, you MUST run /impeccable teach first. Additionally gather: audience technical level and users' mental state in context.
Assess Current Copy
Identify what makes the text unclear or ineffective:
-
Find clarity problems:
- Jargon: Technical terms users won't understand
- Ambiguity: Multiple interpretations possible
- Passive voice: "Your file has been uploaded" vs "We uploaded your file"
- Length: Too wordy or too terse
- Assumptions: Assuming user knowledge they don't have
- Missing context: Users don't know what to do or why
- Tone mismatch: Too formal, too casual, or inappropriate for situation
-
Understand the context:
- Who's the audience? (Technical? General? First-time users?)
- What's the user's mental state? (Stressed during error? Confident during success?)
- What's the action? (What do we want users to do?)
- What's the constraint? (Character limits? Space limitations?)
CRITICAL: Clear copy helps users succeed. Unclear copy creates frustration, errors, and support tickets.
Plan Copy Improvements
Create a strategy for clearer communication:
- Primary message: What's the ONE thing users need to know?
- Action needed: What should users do next (if anything)?
- Tone: How should this feel? (Helpful? Apologetic? Encouraging?)
- Constraints: Length limits, brand voice, localization considerations
IMPORTANT: Good UX writing is invisible. Users should understand immediately without noticing the words.
Improve Copy Systematically
Refine text across these common areas:
Error Messages
Bad: "Error 403: Forbidden" Good: "You don't have permission to view this page. Contact your admin for access."
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 · 183 lines · 51 tokens per session scan A fadbe45be1fd
clarify is a skill published in the GitHub repository ReScienceLab/TrySkills (2 stars, last pushed 3mo ago), licensed MIT. It adds 51 tokens to every session and 1,564 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to clarify, differing in 16 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.