SKILLEMALL.ai

AC gingiris-social-content

🇺🇸 Social Media Content — Multi-platform distribution for startups. Create and distribute content across Twitter/X, LinkedIn, Reddit, HackerNews, Product Hunt, and more. Platform-specific format optimization, thread writing, community engagement tactics, posting schedules, Reddit karma building, and HN submission best practices. 🇨🇳 社交媒体内容 — 创业公司多平台分发。Twitter/X、LinkedIn、Reddit、HackerNews、Product Hunt 等平台内容创作与分发。平台格式优化、Twitter Thread 写作、社区互动策略、发布时间表。 🇯🇵 ソーシャルメディアコンテンツ — スタートアップのマルチプラットフォーム配信。Twitter/X、LinkedIn、Reddit、HackerNews全般のコンテンツ作成と配信。プラットフォーム別最適化、スレッド作成、コミュニティ戦略。 🇰🇷 소셜 미디어 콘텐츠 — 스타트업 멀티플랫폼 배포. Twitter/X, LinkedIn, Reddit, HackerNews 전반의 콘텐츠 제작 및 배포. 플랫폼별 최적화, 스레드 작성, 커뮤니티 전략. Triggers: "social media content" | "Twitter thread" | "LinkedIn post" | "Reddit marketing" | "HackerNews" | "content distribution" | "social media strategy" | "startup content" | "community marketing" | "社交媒体" | "内容分发" | "社群运营"

ClawHub Agent Skills author: Iris Wei v1.0.1 MIT-0 1 file body ≈ 1 136 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

ProcedureMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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 · 0

✓ No critical or high findings

Files scanned: 1. 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")

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
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 31 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1136 tokens

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)
  • +3Description length 929: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 9 example trigger phrases
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This is a static social-media playbook with broad activation terms and promotional links, but no executable or hidden privileged behavior.
LLM: benign (high) · 3 Jun 2026