SKILLEMALL.ai

BC socialconductor

Manage your SocialConductor AI comment automation bots from any chat app. Control Facebook, Instagram, YouTube, and TikTok — check status, pause or resume AI replies, view comment logs, manage leads, block users, post manual replies, regenerate AI replies, view analytics, manage prompts, control drafts and approvals, teach the AI, manage vacation mode, and access the viral vault. After a one-time 30-second browser setup per platform, all bot control and reply posting runs fully server-side — no ongoing browser access needed.

ClawHub Agent Skills author: dcecchino v1.7.4 MIT-0 2 files body ≈ 5 053 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

GeneratorYouTubeMarketingData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
55
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5053 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "summary"

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 15 mutating operations with no state check
  • 40Consistency. Frontmatter name (socialconductor) differs from the folder (socialconductor-skill)
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 5053 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 14 steps
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 21 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
  • +4No input/output examples
  • -218 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 530: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 14 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.

External checks

ClawHub: clean
This skill clearly describes a SocialConductor integration that can control live social media comment bots, with the high-impact posting and blocking abilities disclosed up front.
LLM: benign (high) · VirusTotal: · 4 Jun 2026