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 skills add umputun/cc-thingz --skill clarifygit clone --depth 1 https://github.com/umputun/cc-thingzWrote 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/umputun/cc-thingz/clarify)<a href="https://agentmods.dev/skills/umputun/cc-thingz/clarify"><img src="https://agentmods.dev/badge/skills/umputun/cc-thingz/clarify/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/umputun/cc-thingz/clarify"><img src="https://agentmods.dev/badge/skills/umputun/cc-thingz/clarify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 86 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00091 | $0.01811 |
| Opus 5.5 | $0.00036 | $0.00724 |
| Sonnet 5.5 | $0.00018 | $0.00362 |
| Haiku 4.5 | $0.00009 | $0.00181 |
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 1mo 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 — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clarify
Handle user confusion by verifying intent, explaining actual behavior, and determining if there's a real issue.
Primary goal: Clarify and explain, not fix. Most confusion stems from misunderstanding or forgetting, not from bugs.
Activation Triggers
- "confused", "I'm confused", "this is confusing"
- "I don't understand", "doesn't make sense", "makes no sense"
- "wait, shouldn't it...", "but I thought..."
- "why is this happening", "why does this..."
- "I expected X but got Y"
- "this is wrong", "something's off"
- frustration signals, contradictory statements
- questions that reveal misconceptions about system behavior
Important Context
Users often:
- Work on multiple projects in parallel and may confuse behaviors between them
- Forget how things were implemented especially after time away
- Have outdated mental models based on old versions or different projects
- Mix up similar concepts from different codebases or frameworks
But also:
- Users are experienced developers - their instincts are often correct
- Real bugs exist - about half of confusion cases point to actual issues
- User expectations are reasonable - if something feels wrong, investigate thoroughly
Do not assume either way. Investigate before concluding. Both outcomes are equally valid:
- User misremembered/mixed things up -> clarify with evidence
- System has a genuine issue -> proceed to plan mode for fix
Workflow
Phase 1: Identify the Confusion
- Extract the core question - What specifically is the user asking about?
- Identify the expectation - What did the user expect to happen?
- Identify the reality - What is actually happening?
- Locate the gap - Where is the misalignment?
- Consider context mixing - Could user be thinking of a different project/feature?
Categories of confusion:
- Memory gap - user forgot how it works, needs a reminder
- Project mixing - user confused this with another project they're working on
- Outdated mental model - user's understanding is based on old behavior
- Architectural - misunderstanding system design, component relationships, data flow
- Behavioral - expecting different runtime behavior than what occurs
- Configuration - settings not producing expected results
- Documentation - docs don't match implementation or are unclear
- Conceptual - misunderstanding underlying concepts or patterns
- Implementation - code doesn't work as assumed
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.
- 1mo ago First seen · 215 lines · 91 tokens per session scan A 3c98ff57c98b
clarify is a skill published in the GitHub repository umputun/cc-thingz (489 stars, last pushed 6d ago), licensed MIT. It adds 91 tokens to every session and 1,811 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-30.
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