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BD Proactive Claw

🦞 The most powerful proactive engine for OpenClaw. Your personal assistant that learns from you and helps you be more productive.

ClawHub Agent Skills author: Dawid Piaskowski v1.2.41 40 files · 2 scripts body ≈ 2 750 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
85/100
safety, quality, tests
Safety 60%
99
Quality 40%
64
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security SECURITY.md:107
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | Privilege escalation | No sudo, no root, no system services |

Files scanned: 40. 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")

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 5 mutating operations with no state check
  • 40Consistency. Frontmatter name (Proactive Claw) differs from the folder (proactive-claw)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 85Steps. 51 steps, 1 vague phrases
  • 100Failures and branches. 2 branches, has a failure section
  • 100Execution cost. Instruction body is 2750 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 19 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
  • -328 of 32 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 130: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 51 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
This calendar assistant is not malicious, but it deserves Review because it can read broad calendar data, store local memory, and some paths can write or delete its action-calendar items without the approval language being fully enforced.
LLM: suspicious (high) · VirusTotal: benign · 28 May 2026