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BC weekly-content-brief

Scheduled WhatsApp briefing for content founders. Runs every Monday at 8 AM. Reads your content calendar file and sends a weekly brief. Covers what is due, what shipped last week, and one suggested focus area.

ClawHub Agent Skills author: desgnpulse v1.0.0 MIT-0 2 files body ≈ 959 tokens Open the sourceclawhub.ai↗ analyzed 28 h ago

Scheduled WhatsApp briefing for content founders.

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureWhatsAppWriting and documentsMedia and videoPersonal productivitytype 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
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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: 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")

Process rating: all ten parameters 64/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 7 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 959 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

  • +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
  • +1No license
  • +2Single-language instructions
  • +3Description length 209: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This skill is openly meant to send WhatsApp content briefs, but it combines scheduled autonomous messaging with session-log reading and an inaccurate read-only permission claim.
LLM: suspicious (high) · 2 Aug 2026