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 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/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/qingxuantang/tar-engine/echo"><img src="https://agentmods.dev/badge/skills/qingxuantang/tar-engine/echo.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00050 | $0.00324 |
| Opus 5.5 | $0.00020 | $0.00130 |
| Sonnet 5.5 | $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 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.
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.
- 1mo 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 2mo ago), licensed Apache-2.0. It adds 50 tokens to every session and 324 once invoked, about $0.0002 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 2026-08-31.
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