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BB reddit-assistant

Reddit content creation assistant for indie developers and product builders. Creates authentic posts, researches communities, tracks real performance data via Reddit API. Triggers on: "write reddit post", "draft reddit", "post to reddit", "reddit content", "find subreddits for", "which subreddits", "check reddit performance", "reddit analytics", "reddit results", "log reddit post", "reddit post ideas", "reddit strategy"

ClawHub Agent Skills author: EdisonChenAI v1.0.0 2 files body ≈ 2 106 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process B 70/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
75
Run on models
none yet
Process rating
B
70/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
30
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Write

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")
  • note frontmatter-key unknown frontmatter key "inputs"
  • note frontmatter-key unknown frontmatter key "outputs"

Process rating: all ten parameters 70/100

  • 0Result and completion. Does not say what the result is
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 2 mutating operations with no state check
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 29 steps, 1 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2106 tokens
  • 100Progress reporting. Reports progress

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

  • +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
  • +5Description quotes 12 example trigger phrases
  • +3Description length 423: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (14 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: suspicious
The skill has a coherent Reddit drafting and analytics purpose, but it tells the agent to automatically run local helper scripts that are not included in the reviewed package.
LLM: suspicious (high) · VirusTotal: · 29 May 2026