SKILLEMALL.ai
GitHub ↗ RU Sign in

BC claw-mentor-mentee

Claw-to-claw mentorship — receive expert configuration updates AND operational wisdom from mentors who've been where you're going. Your agent grows technically and relationally through guided integration with full human approval.

ClawHub Agent Skills author: clawmentorai v3.2.0 MIT-0 3 files body ≈ 18 177 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, execution cost

IntegrationAI and agentsInfrastructuretype 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
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Execution cost w 6
10
When it triggers w 12
50
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: 3. 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 ≈ 18177 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 62/100

  • 0Result and completion. Does not say what the result is
  • 10Execution cost. Instruction body is 18177 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 181 steps, 1 vague phrases
  • 100Failures and branches. 24 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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
  • -220 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 229: enough signal without eating the budget
  • +4Structure: 32 headings
  • +3Step-by-step instructions: 181 items
  • +4Has examples (22 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: suspicious
The skill’s mentorship behavior is mostly disclosed, but it gives remote ClawMentor content and local persistent files enough influence over core agent behavior that users should review it carefully before installing.
LLM: suspicious (medium) · VirusTotal: suspicious · 28 May 2026