BB twitter-cli
Use twitter-cli for ALL Twitter/X operations — reading tweets, posting, replying, quoting, liking, retweeting, following, searching, user lookups. Invoke whenever user requests any Twitter interaction.
As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, consistency
The same skill appears in 1 more place: ClawHub
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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- 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 · 3
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high Exfiltration
intent-browser-credential-storeREADME.md:155Accesses a browser credential / cookie store2. **Browser cookies** (recommended): auto-extract from Arc/Chrome/Edge/Firefox/Brave
Medium and low: 2
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medium Exfiltration
intent-browser-credential-storeREADME.md:494Accesses a browser credential / cookie store (quoted — discussed, not commanded)- 报错 `No Twitter cookies found`：请先登录 `x.com`，并确认浏览器为 Arc/Chrome/Edge/Firefox/Brave 之一，或手动设置环境变量。
quoted -
low Secrets in code
secret-high-entropy-tokentwitter_cli/constants.py:9High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)"%3D1Z…TnA"
quoted
Files scanned: 25. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 68/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Consistency. Frontmatter name (twitter-cli) differs from the folder (twitter-command)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Steps. 11 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 2632 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +1No license
- +2Single-language instructions
- +3Description length 201: enough signal without eating the budget
- +4Structure: 29 headings
- +3Step-by-step instructions: 11 items
- +3Output format is stated explicitly
- +4Has examples (22 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.