FD iran-war-tracker
为2026年3月爆发的伊朗战争提供每日结构化局势日报与实时风险监测。整合金十数据MCP(实时快讯+行情)、WebSearch/Jina网页抓取、Tavily深度搜索等多源数据,生成面向地缘可信度分级报告。 **核心能力:** - **多源数据采集**:金十MCP实时快讯(关键词搜索,默认当天全量)、金十MCP行情(布伦特原油/黄金/天然气/USD-CNH,BTC/纳指/美债由AlphaVantage/Stooq补充)、WebSearch新闻检索、Jina网页预处理 - **时效性控制**:快讯默认过滤当天当前小时数(如9点执行则覆盖0-9时),新闻默认过去18小时 English: Structured daily Iran war situation briefs integrating Jin10 MCP real-time flashes & quotes, WebSearch, and Tavily deep search. Applies a rigorous ceasefire-period analytical framework with credibility-graded output (multi-source confirmed / single-source / unverified / denied), covering Hormuz Strait transit, actor pressure variables, scenario probability forecasts (A/B/C), and risk asset implications for geopolitical trading decisions.
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.
The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.
How to improve
- Remove the critical guard findings (secrets, dangerous commands, hidden instructions): while they stand the skill is blocked and cannot grade above F.
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 2
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critical Secrets in code
secret-openai-keyscripts/jin10_mcp.py:23OpenAI-style API key (quoted — discussed, not commanded)JIN1…KEN = "sk-z…tes"
quoted
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenscripts/jin10_mcp.py:23High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)JIN1…KEN = "sk-z…tes"
quoted
Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "clawhub" - note
frontmatter-keyunknown frontmatter key "triggers"
Process rating: all ten parameters 41/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (iran-war-tracker) differs from the folder (iran-war-tracker-v2)
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 49 steps
- 100Execution cost. Instruction body is 712 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -32 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 738: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 49 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.