BD x-scraper-comprehensive
X.com (Twitter) 全量推文采集技能。支持三种采集方案：自动搜索模式、GraphQL API 模式、DOM 滚动模式。Complete X.com tweet scraping skill with three strategies: auto-search, GraphQL API, and DOM scrolling.
X.com (Twitter) 全量推文采集技能。支持三种采集方案：自动搜索模式、GraphQL API 模式、DOM 滚动模式。Complete X.com tweet scraping skill with three strategies: auto-search, GraphQL API, and DOM…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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 If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail.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
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Secrets in code
secret-labelled-tokenscripts/scrape_x_v9.py:23Labelled token / key literal (vendor format unknown — verify it is not a live credential)BEARER = "AAAA…uTs=1Zv7…TnA"
Files scanned: 8. 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 "agent_created"
Process rating: all ten parameters 46/100
- 0Result and completion. Does not say what the result is
- 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
- 30Running it twice. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (x-scraper-comprehensive) differs from the folder (x-tweet-scraper)
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 6 steps
- 100Execution cost. Instruction body is 1453 tokens
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
- +1No license
- +2Single-language instructions
- +3Description length 168: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 6 items
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.