SKILLEMALL.ai

BC BytesAgain X Manager

Manage X (Twitter) account: auto-post AI-generated tweets, monitor brand mentions, auto-like relevant posts, and send Telegram approval requests for replies.

ClawHub Agent Skills author: loutai0307-prog v1.6.0 MIT-0 8 files · 1 script body ≈ 1 347 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

GeneratorTelegramInfrastructureMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
98
Quality 40%
65
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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

✓ No critical or high findings

Medium and low: 2
  • low Exfiltration exfil-webhook-url scripts/x-engage.py:39
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    f"https://api.telegram.org/bot{TG_TOKEN}/sendMessage",
    placeholder
  • low Exfiltration exfil-webhook-url scripts/x-monitor.py:86
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    f"https://api.telegram.org/bot{TG_TOKEN}/sendMessage",
    placeholder

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "credentials"

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 9 mutating operations with no state check
  • 40Consistency. Frontmatter name (BytesAgain X Manager) differs from the folder (bytesagain-x-manager)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 22 steps
  • 100Execution cost. Instruction body is 1347 tokens
  • low 12 top-level sections: this looks like several domains in one skill

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
  • -214 emoji in the instructions: noise for the model
  • -32 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 157: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
This X/Twitter automation skill is mostly honest about its purpose, but it can post, like, and reply from a live account with weak approval safeguards and some misleading disclosure.
LLM: suspicious (high) · VirusTotal: · 29 May 2026