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/qingxuantang/tar-engine/echonpx skills add qingxuantang/tar-engine --skill echogit clone --depth 1 https://github.com/qingxuantang/tar-engineWrote 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/qingxuantang/tar-engine/echo)<a href="https://agentmods.dev/skills/qingxuantang/tar-engine/echo"><img src="https://agentmods.dev/badge/skills/qingxuantang/tar-engine/echo.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 | $0.00050 | $0.00324 |
| Opus 5 | $0.00025 | $0.00162 |
| Sonnet 5 | $0.00010 | $0.00065 |
| Haiku 4.5 | $0.00005 | $0.00032 |
Grade A, and why
echo 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 3d 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.
What it actually says
Echo Skill
The simplest possible skill — it echoes the user's wish back as the result.
When to use
Use this skill when the user wish is:
- A greeting: "hi", "hello", "hey there"
- A literal echo request: "echo hello world", "say something"
- A smoke test: "is this working?"
- Anything purely conversational that doesn't need data, fetching, or analysis
How to respond
No tools needed. No scripts to call. Just respond with a single message that includes the user's wish text wrapped in a brief acknowledgment.
Format:
You said: <verbatim user input>
That's the entire skill. Done.
What this skill demonstrates
This SKILL.md format is the standard Claude Code skill format. The TAR Engine
reads this file and puts it in the LLM's system prompt. The LLM then produces a
response — for trivial skills like this one, no run_bash / read_file /
write_file tool calls are needed.
For skills that need data or scripts, the SKILL.md instructs the LLM to call
run_bash to invoke scripts in the same skill directory. See url-summarize/SKILL.md
in this pack for that pattern.
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.
- 3d ago First seen · 41 lines · 50 tokens per session scan A 255c017db701
echo is a skill published in the GitHub repository qingxuantang/tar-engine (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 50 tokens to every session and 324 once invoked, about $0.0003 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
edgeone skill scanner
Scan any agent skill for security risks before you install or use it. Powered by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). 100% local static analysis — no file contents or credentials leave your device. Compatible with CodeBuddy, Cursor, Windsurf, Claude Code, OpenClaw and more. Triggers on: 这个 skill 安全吗, skill 安全扫描…
skill-review
Critically review a workspace skill and suggest improvements. Use when asked to review, audit, critique, evaluate, or improve a SKILL.md file or skill directory. Covers frontmatter validation, instruction clarity, completeness, and adherence to the Agent Skills Specification.
air-blackbox-sales-agent
AIR Blackbox's autonomous sales prospecting agent. Finds Python AI projects on GitHub that need EU AI Act compliance, identifies the right person to contact (CEO, CTO, lead maintainer), runs a free compliance scan, and drafts personalized outreach emails that convert to engagement. The sales flow: free scan as the…
compliance-scan
Scans a Python AI project for EU AI Act compliance gaps using AIR Blackbox. Use when the user asks to check compliance, scan their code, audit their AI project, or mentions EU AI Act, Articles 9-15, or compliance checking.
interpret-results
Interprets AIR Blackbox scan results and maps findings to specific EU AI Act articles, recitals, and remediation steps. Use when the user has scan output and wants to understand what to fix, why it matters, or how to prioritize.
skill-scorer
Evaluates Agent Skills (Cursor / Claude / OpenClaw compatible) and produces a quantitative, rubric-based score with actionable improvement suggestions. Use when the user asks to review, rate, audit, grade, lint, or improve a SKILL.md file, a skill folder, or a skill archive, or says things like "给这个 skill 打分", "评估一下…