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
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/volcengine/searchcli/vs-search-tuning-partial-casenpx skills add volcengine/SearchCLI --skill vs-search-tuning-partial-casegit clone --depth 1 https://github.com/volcengine/SearchCLIWrote 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-search-tuning-partial-case)<a href="https://agentmods.dev/skills/volcengine/searchcli/vs-search-tuning-partial-case"><img src="https://agentmods.dev/badge/skills/volcengine/searchcli/vs-search-tuning-partial-case.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 | $0.00085 | $0.03993 |
| Opus 5 | $0.00043 | $0.01997 |
| Sonnet 5 | $0.00017 | $0.00799 |
| Haiku 4.5 | $0.00009 | $0.00399 |
Grade A, and why
vs-search-tuning-partial-case 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 5d 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 — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Viking Search Partial Case Tuning
When to Use
Use this skill when the user provides a small number of concrete bad-case queries, usually 1-50, and asks to "optimize the search results for these queries."
This skill only performs local, highly deterministic, fine-grained operational fixes:
- It does not replace global relevance or recall-parameter tuning.
- It does not change online configuration; it only validates candidates through request-level payloads.
- The final deliverables are a fine-grained operations configuration sheet that can be copied into the console, validated payloads, and a replay script.
Preconditions
- A Viking Search application id is available.
- A dataset id and baseline search scene id are either provided by the user or can be resolved from read-only CLI checks.
- The user has provided 1-50 concrete bad-case queries for the same application.
vs auth status --jsonsucceeds before any runtime search probe.- The work can be completed with request-level candidate payloads and offline deliverables only.
Constraints
- Do not change core recall parameters:
user_defined_recall_mode,dense_weight,text_weight,query_keyword_match_percent, ormax_retrieved_num. - The baseline scene is read-only; do not create, modify, derive, publish, or switch scenes.
- Do not write app config, dataset config, dictionaries, recommend scenes; do not bind anything, and do not perform any persistent writes.
- Validation may only take effect through a single-request payload passed to
vs search run --data; no side effects may remain after the request finishes. - Do not rewrite the user's real query. Query-rewrite ideas may only be used as candidate evidence; they must not be written back to the original query or used as online trigger terms that replace the user's query.
- Do not use conclusions from local cases to judge the overall quality of the recall strategy.
- Do not force a search-mode change. Evaluate the currently locked baseline scene as-is; if the scene itself is not UserDefined, do not change it for this skill.
- In the apply phase, only deliver the configuration sheet and evidence; actual launch must be performed manually in the Viking console based on the configuration sheet.
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.
- 5d ago First seen · 357 lines · 85 tokens per session scan A db0d443fb7b7
vs-search-tuning-partial-case is a skill published in the GitHub repository volcengine/SearchCLI (1,176 stars, last pushed 8d ago), licensed Apache-2.0. It adds 85 tokens to every session and 3,993 once invoked, about $0.0004 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 2026-08-30.
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