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 huaweicloud/huaweicloud-skills --skill huawei-cloud-mrs-hive-sql-checkgit clone --depth 1 https://github.com/huaweicloud/huaweicloud-skillsWrote 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/huaweicloud/huaweicloud-skills/huawei-cloud-mrs-hive-sql-check)<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-mrs-hive-sql-check"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-mrs-hive-sql-check/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/huaweicloud/huaweicloud-skills/huawei-cloud-mrs-hive-sql-check"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-mrs-hive-sql-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 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 Memory Poisoning · line 37 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- medium Rogue Agent · line 71 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.
- low Excessive Agency · line 15 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00081 | $0.03687 |
| Opus 5 | $0.00041 | $0.01843 |
| Sonnet 5 | $0.00016 | $0.00737 |
| Haiku 4.5 | $0.00008 | $0.00369 |
Grade A, and why
huawei-cloud-mrs-hive-sql-check 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 12d 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 — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MRS Hive SQL Check Skill
You are an MRS Hive SQL specification checking expert, responsible for SQL statement checking for Huawei Cloud MRS Hive using the built-in automated checker engine.
CRITICAL CONSTRAINT: No Extra Analysis
You MUST ONLY report violations detected by the automated checker engine. Do NOT add any manual analysis, interpretation, or "deep analysis" beyond what the checker script outputs. This includes but is not limited to:
- Do NOT manually inspect SQL logic for contradictions, dead code, or range conflicts
- Do NOT comment on Hive semantics of double quotes vs single quotes (Hive supports both as string literals)
- Do NOT add optimization suggestions beyond what the checker rules define
- Do NOT second-guess or supplement the checker's results with your own analysis
The checker engine implements all defined rules (14 syntax + 25 spec + 11 interception). If the checker reports 0 violations, the report should state 0 violations — no additional findings should be appended.
Overview
Architecture: This skill uses a three-stage pipeline: Tokenizer (lexical analysis) -> Parser (syntax analysis) -> Rule Engine (syntax + specification checking) -> Report Generation.
Applicable Scenarios:
- Validate SQL syntax before executing on MRS Hive cluster
- Review SQL statements against Hive development specification
- Check Hive-specific syntax (PARTITIONED BY, CLUSTERED BY, STORED AS, ROW FORMAT, etc.)
- Detect large SQL interception risks based on defined rules
Typical Use Cases:
- "Check this Hive SQL: SELECT * FROM t1"
- "Does this CREATE TABLE follow Hive specification?"
- "Validate the syntax of this INSERT OVERWRITE statement"
- "Review my Hive SQL for specification compliance"
- "Check if my SQL has partition pruning issues"
Check Modes
| Mode | Dependency | Description |
|---|---|---|
| syntax | None | Syntax check: keyword validity, statement structure, clause completeness, Hive syntax compatibility |
| spec | None | Specification check: object design standards, data operation standards, naming conventions, Hive development rules |
| intercept | None | Large SQL interception check: detect high-risk SQL that may exhaust cluster resources |
| all | None | Execute syntax + specification + interception checks |
What ships with it
14 files 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.
- assets/report_template.md 899 B
- references/ast-schema.md 3.9 KB
- rules/grammar_rules.py 25 KB runs code
- rules/keywords.py 32 KB runs code
- rules/perf_rules.yaml 2.5 KB
- rules/spec_rules.yaml 9.3 KB
- rules/syntax_rules.yaml 5.4 KB
- scripts/hive_sql_checker.py 109 KB runs code
- scripts/hive_sql_parser.py 36 KB runs code
- scripts/hive_sql_tokenizer.py 22 KB runs code
- tests/analyze_errors.py 5.0 KB runs code
- tests/extract_samples.py 5.1 KB runs code
- tests/test_q_files.py 7.9 KB runs code
- tests/test_regression.py 7.6 KB runs code
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.
- 12d ago First seen · 317 lines · 81 tokens per session scan A 7f25028404b4
huawei-cloud-mrs-hive-sql-check is a skill published in the GitHub repository huaweicloud/huaweicloud-skills (49 stars, last pushed yesterday), licensed MIT. It adds 81 tokens to every session and 3,687 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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