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-doris-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-doris-sql-check)<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-doris-sql-check"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-doris-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-doris-sql-check"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-doris-sql-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
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 →
- medium Prompt Injection · line 46 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 138 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 151 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00251 | $0.05911 |
| Opus 5 | $0.00125 | $0.02955 |
| Sonnet 5 | $0.00050 | $0.01182 |
| Haiku 4.5 | $0.00025 | $0.00591 |
Grade A, and why
huawei-cloud-doris-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 — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Doris SQL Check Skill
You are an Apache Doris SQL specification checking expert, responsible for comprehensive SQL statement checking for Apache Doris (based on Doris 3.1.4 source code). You have a custom-built Doris SQL tokenizer and recursive descent parser that can precisely identify Doris-specific syntax from the Nereids ANTLR4 grammar (DorisLexer.g4 / DorisParser.g4).
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 a Doris cluster (FE/BE)
- Review SQL statements against Apache Doris development best practices
- Check Doris-specific syntax (DISTRIBUTED BY HASH/RANDOM, PARTITION BY RANGE/LIST/AUTO, BUCKETS, PROPERTIES, ENGINE, DUPLICATE/AGGREGATE/UNIQUE KEY, INSERT OVERWRITE TABLE, LOAD LABEL, ROUTINE LOAD, EXPORT, MTMV, BACKUP/RESTORE SNAPSHOT, ADMIN SET/SHOW, CANCEL, KILL, TABLESAMPLE, OUTFILE, Hint /*+ /, full-text MATCH_, COLOCATE GROUP)
- Identify potential performance anti-patterns in Doris SQL statements
Typical Use Cases:
- "Check this Doris SQL: SELECT * FROM t1"
- "Does this CREATE TABLE follow Doris specification (DISTRIBUTED BY, KEY model, PARTITION)?"
- "Validate the syntax of this INSERT OVERWRITE TABLE statement"
- "Review my Doris SQL for specification compliance"
- "Check if my SQL uses Doris-specific syntax correctly (MTMV, LOAD, EXPORT)"
- "Validate BACKUP/RESTORE SNAPSHOT syntax"
- "Check my ROUTINE LOAD job definition"
Check Modes
| Mode | Dependency | Description |
|---|---|---|
| syntax | None | Syntax check: keyword validity, statement structure, clause completeness, Doris syntax compatibility |
| spec | None | Specification check: object design standards, data operation standards, naming conventions |
| all | None | Execute both syntax and specification checks |
What ships with it
10 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.
- references/ast_schema.md 12 KB
- rules/grammar_rules.py 54 KB runs code
- rules/keywords.py 36 KB runs code
- rules/perf_rules.yaml 5.0 KB
- rules/spec_rules.yaml 20 KB
- rules/syntax_rules.yaml 16 KB
- scripts/doris_sql_checker.py 47 KB runs code
- scripts/doris_sql_parser.py 45 KB runs code
- scripts/doris_sql_tokenizer.py 18 KB runs code
- templates/report_template.md 927 B
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 · 343 lines · 251 tokens per session scan A 9c76c6105383
huawei-cloud-doris-sql-check is a skill published in the GitHub repository huaweicloud/huaweicloud-skills (49 stars, last pushed yesterday), licensed MIT. It adds 251 tokens to every session and 5,911 once invoked, about $0.0013 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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