SearchCLI is a command-line interface for connecting agent or business systems to Volcengine’s search, recommendation, and conversational-retrieval services. It is for developers who need to onboard data, build and test retrieval workflows, adjust search strategies, inspect poor results, and verify changes. Its catalogue entries provide installable skills for operating these workflows.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/volcengine/SearchCLInpx agentmods add skills/volcengine/searchcli/vs-item-onboardingWrote 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/volcengine/searchcli/vs-item-onboarding)<a href="https://agentmods.dev/skills/volcengine/searchcli/vs-item-onboarding"><img src="https://agentmods.dev/badge/skills/volcengine/searchcli/vs-item-onboarding/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/volcengine/searchcli/vs-item-onboarding"><img src="https://agentmods.dev/badge/skills/volcengine/searchcli/vs-item-onboarding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, 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 Prompt Injection · line 25 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Privilege Escalation · line 147 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 67 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 140 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Rogue Agent · line 142 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Rogue Agent · line 429 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00086 | $0.13196 |
| Opus 5.5 | $0.00034 | $0.05278 |
| Sonnet 5.5 | $0.00017 | $0.02639 |
| Haiku 4.5 | $0.00009 | $0.01320 |
Grade B, and why
vs-item-onboarding scanned grade B with 2 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
| PUT upload | `curl -X PUT --data-binary @<path> "<FileUrl>"` | Upload the local file to TOS (no auth header needed) | Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| PUT upload | `curl -X PUT --data-binary @<path> "<FileUrl>"` | Upload the local file to TOS (no auth header needed) | How it starts
The opening of the file, as written. The whole thing — 474 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Viking Item Onboarding
Language Matching (apply throughout)
Match the language of the user's most recent message in every line of prose you write — confirmation prompts, status notes, hand-off summaries, questions, error explanations, and any internal thinking / reasoning / planning output that the host may surface (e.g. <thinking> blocks, "thinking" panels, scratchpad notes, todo descriptions). If the user is writing in Chinese, every prose line and every reasoning line must also be in Chinese; if English, English; same for Japanese, etc. The fact that this skill file is written in English is for documentation only — at runtime translate all prose and reasoning into the user's language. Do not switch back to English mid-flow just because the surrounding skill text is English.
Chinese-user priority (the most common case) — when current_query or the most recent user message is in Chinese:
- All prose you write for the user (confirmation prompts, status notes, error explanations, final hand-off summaries) must be in Chinese.
- All internal thinking / reasoning / planning output (thinking blocks, scratchpad, todo descriptions) must also be in Chinese.
- For workspace artifacts you create, the description / comment portions (excluding CLI-contract English identifiers) should also prefer Chinese.
Do not translate the following — keep them verbatim so the contract stays machine-checkable:
- The verbatim CLI block between
<!-- vs-schema-confirm: BEGIN -->and<!-- vs-schema-confirm: END -->(English section labels**Metadata**/**Fields (N)**/**Field Roles**/**Warnings (N)**and English warning text come straight from the CLI). - CLI command names, flag names, JSON keys, enum values, field names, primary-key BizAttr identifiers (
multi_modal_id), dataset IDs / app IDs / TaskIDs, and console URLs. - The single literal token the user must reply to confirm — write it as
`yes`in any language so the contract for advancing to step 8 is unambiguous (you may add a parenthetical native-language hint, e.g.回复 \yes`（即"确认"）继续`).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed · +2 lines 3700e52176de
- 1mo ago Changed · +4 lines c8d8f62740fe
- 1mo ago First seen · 468 lines · 86 tokens per session scan B be3dd5cdde88
vs-item-onboarding is a skill published in the GitHub repository volcengine/SearchCLI (1,189 stars, last pushed 4d ago), licensed Apache-2.0. It adds 86 tokens to every session and 13,196 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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