CtrlK
BlogDocsLog inGet started
Tessl Logo

kimi-datasource

Universal data-source assistant for stocks (Wind, S&P, SEC EDGAR), macro (World Bank, IMF, FRED, NBS), Chinese government data and standards (GB/HB/DB/TT), corporate, academic, legal, WHO/FAO/OECD and other IGO data, financial news (Xinhua, Caixin). This plugin exposes tools via MCP server `plugin-kimi-datasource_data`; call them in the flow `mcp__plugin-kimi-datasource_data__get_data_source_desc` → `mcp__plugin-kimi-datasource_data__call_data_source_tool`.

57

Quality

72%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./plugins/official/kimi-datasource/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

78%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is an unusually strong operational document: every rule is concrete, sourced from real failure modes (silent wrong-data on bad tickers, API_NOT_FOUND, file_path omissions), and organized into a clear workflow with worked examples and stop conditions. Its main structural weakness is that it is a monolith — the 25-source capability table, boundary notes, and watchlist spec would be better split into reference files for progressive disclosure. Minor duplication of the ticker-verification caution could be trimmed.

Suggestions

Move the 25-row datasource capability table and the '能力边界参考' notes to references/datasources.md, keeping SKILL.md to the workflow, hard rules, and a compact selection summary — this also trims ~60 lines from the always-loaded context.

Consider moving the watchlist.json format spec to references/watchlist.md or shortening it, since it is a niche feature relative to the core workflow.

Deduplicate the ticker-verification caution (stated fully in §3.1 and again in §6) to reclaim a few lines.

DimensionReasoningScore

Conciseness

The body is dense with genuinely non-obvious operational knowledge — capability boundaries ("yahoo_finance 的外汇历史最多 2 年"), batch limits ("实时接口最多 3 个 ticker,历史接口最多 10 个"), error strings, and the split-CSV A/HK quirk — with almost no padding or explanation of things Claude already knows. It falls short of anchor 5 only through minor repetition (ticker-verification caution appears in both §3.1 and §6) and the example-question column of the table, which could be trimmed.

4 / 5

Actionability

Guidance is fully executable: exact MCP tool names, concrete parameter JSON in worked examples ("{\"name\":\"stock_finance_data\"}" and a complete params object with ticker 600519.SH, dates, and file_path), literal error messages ("Missing required parameters: file_path"), specific batch sizes, and file-naming conventions. The one abstraction ("<文档里写的 api>") is explicitly justified flexibility — the skill deliberately defers API tables to the runtime desc call, which the rubric permits when justified.

5 / 5

Workflow Clarity

The 6-step numbered workflow plus three worked examples gives a clear sequence, and there are real checkpoints: pre-flight ticker verification via web_search, stop conditions ("结果成功且已经覆盖问题时停止调用"), batching rules, and explicit error-handling guidance ("汇报错误给用户,不要硬试"). It falls short of anchor 5 because there is no validate-then-fix retry loop — though for read-only data retrieval, error recovery is 'report and stop', which is reasonable but not the full feedback-loop pattern of the top anchor.

4 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are all absent), so all ~170 lines live in SKILL.md: the 25-row datasource capability table, the capability-boundary notes, three worked examples, and watchlist documentation are inlined in one file with clear section headers but no references at all. This matches anchor 3 (some structure, content that could be separate is inline) — the table plus boundary notes would sit naturally in a references/ file while SKILL.md keeps the workflow and hard rules.

3 / 5

Total

16

/

20

Passed

Description

52%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description excels at enumerating the covered domains and named data sources, giving strong trigger vocabulary, but it never states concrete actions the skill performs and entirely lacks a 'Use when...' trigger clause. The second line wastes space on MCP plumbing details that belong in the body. Adding explicit capability verbs and a when-to-use clause would lift it substantially.

Suggestions

Add an explicit trigger clause, e.g., "Use when the user asks for financial, macroeconomic, legal, standards, or IGO data from specific named sources (Wind, SEC EDGAR, World Bank, GB standards) rather than general web search."

Replace the generic "Universal data-source assistant for..." opener with concrete actions, e.g., "Fetches stock quotes and financials, queries macroeconomic time series, retrieves SEC filings, and searches Chinese laws and standards."

Trim the MCP server/tool-name plumbing line (better placed in the body) and use the freed space for natural synonyms like GDP, financial statements, 10-K filings, and case law.

DimensionReasoningScore

Specificity

The description names the domain exhaustively — "stocks (Wind, S&P, SEC EDGAR), macro (World Bank, IMF, FRED, NBS)" — but the only actions stated are generic: "Universal data-source assistant for..." and "exposes tools via MCP server... call them in the flow". No concrete capability verbs (fetch quotes, download 10-K filings, query GDP series) appear, matching anchor 2 (domain named, actions minimal/generic); it does not reach anchor 3, which requires 1-2 concrete actions.

2 / 5

Completeness

The "what" is clear (data-source assistant covering 25 external finance/macro/legal/IGO sources via two MCP tools), but there is no "Use when..." clause or equivalent explicit trigger guidance anywhere in the description, which caps completeness at 3 per the rubric. It is not anchor 2 because the "what" is specific rather than vague.

3 / 5

Trigger Term Quality

Good coverage of natural source names users would actually say — "Wind", "S&P", "SEC EDGAR", "World Bank", "IMF", "FRED", "WHO/FAO/OECD", "Xinhua", "Caixin" — plus domain words like "stocks", "macro", "financial news". Not anchor 5 because common natural synonyms are missing (e.g., "GDP", "financial statements", "10-K", "case law", plain-language phrasing like "stock quotes" or "papers").

4 / 5

Distinctiveness Conflict Risk

The named sources (Wind, SEC EDGAR, GB/HB/DB/TT standards, Xinhua) form a fairly distinctive niche, but the framing "Universal data-source assistant... corporate, academic, legal" is very broad and overlaps any general research/search/finance skill. It sits between anchor 3 (somewhat specific, overlap risk) and anchor 4; the "universal" breadth plus missing when-clause keeps it at 3 rather than 4.

3 / 5

Total

12

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
MoonshotAI/kimi-code
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.