CF xint
X Intelligence CLI — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", "find tweets about", "monitor x for", "track followers", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to find what devs/experts/community thinks about a topic, (4) user needs real-time monitoring ("watch"), (5) user wants AI-powered analysis ("analyze", "sentiment", "report"), (6) user wants to sync bookmarks to Obsidian ("sync bookmarks", "capture bookmarks", "bookmark research", "save my bookmarks to obsidian"). Also supports: bookmarks, likes, following (read/write), trending topics, Grok AI analysis, and cost tracking. Export as JSON, JSONL (pipeable), CSV, or Markdown. Non-goals: Not for posting tweets, not for DMs, not for enterprise features. Requires OAuth for user-context operations (bookmarks, likes, following, diff).
As a process F 51/100 · Will not run — References files that are not bundled: url, references/x-api.md
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 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.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Shorten the description to 1024 characters.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- 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 · 5
✓ No critical or high findings
Medium and low: 5
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medium Exfiltration
net-redirectable-api-keylib/mcp-package-contract.test.ts:14Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
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medium Dangerous commands
cmd-pipe-to-shell-known-hostREADME.md:34Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://raw.githubusercontent.com/0xNyk/xint/main/install.sh | bash
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medium Dangerous commands
cmd-pipe-to-shell-known-hostREADME.md:41Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://raw.githubusercontent.com/0xNyk/xint/main/install.sh | bash
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medium Dangerous commands
cmd-pipe-to-shellSKILL.md:77Downloads and executes remote code from an unrecognised host (pipe to shell) (quoted — discussed, not commanded)- For Bun: prefer OS package managers over `curl | bash` when possible
quoted -
low Secrets in code
secret-high-entropy-tokenREADME.md:527High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)`BYLu…vPg`
quoted
Files scanned: 80. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1136 chars, limit 1024 - warning
body-longSKILL.md body ≈ 6462 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: url - warning
missing-refreference to a missing file: references/x-api.md - note
frontmatter-keyunknown frontmatter key "credentials" - note
frontmatter-keyunknown frontmatter key "required_env_vars" - note
frontmatter-keyunknown frontmatter key "primary_credential" - note
frontmatter-keyunknown frontmatter key "security"
Process rating: all ten parameters 51/100
- 0Tools and files. 2 referenced file(s) missing: url, references/x-api.md
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 12 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 6462 tokens
- 85Steps. 145 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (10 tags): a typed call is more reliable
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
- +3Description length 1135: 120–800 characters recommended
- +1No license
- +2Single-language instructions
- +5Description quotes 18 example trigger phrases
- +4Description says when NOT to use the skill
- +4Structure: 52 headings
- +3Step-by-step instructions: 145 items
- +3Output format is stated explicitly
- +4Has examples (39 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 46.