SKILLEMALL.ai
GitHub ↗ RU Sign in

BF wiki

LLM-maintained personal knowledge base. Compile raw sources into a structured markdown wiki, auto-lint for consistency, serve as a browsable website. Inspired by Karpathy's 'LLM Knowledge Bases' workflow. Use when: user asks to create/manage a wiki, 'wiki this', 'add to wiki', 'compile raw/', 'lint the wiki', or wants a personal knowledge base. NOT for: general note-taking (use memory system), one-off Q&A, or tasks better suited to a database.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Nguyen Khoi Tran v1.2.0 MIT-0 6 files · 2 scripts body ≈ 1 636 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

LLM-maintained personal knowledge base.

As a process F 31/100 · Will not run — References files that are not bundled: relative-path.md

ReferenceAI and agentsSoftware developmentPersonal 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
79/100
safety, quality, tests
Safety 60%
72
Quality 40%
89
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: relative-path.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. The text references files that are not there: add them or drop the references.
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 · 3

  • high Dangerous commands cmd-persistence scripts/bootstrap.sh:148
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load "${PLIST}"
Medium and low: 2
  • medium Dangerous commands cmd-persistence scripts/bootstrap.sh:116
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    PLIST="${HOME}/Library/LaunchAgents/dev.wiki.server.plist"
    code literal
  • medium Dangerous commands cmd-autorun-instruction SKILL.md:156
    Instructs the agent to auto-run a script on every session
    Always run `scripts/build.sh` after content changes. This:

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: relative-path.md

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: relative-path.md
  • 0Tools and files. 1 referenced file(s) missing: relative-path.md
  • 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
  • 30Running it twice. 17 mutating operations with no state check
  • 40Consistency. Frontmatter name (wiki) differs from the folder (llm-wiki)
  • 50When it triggers. No condition that starts the skill
  • 85Steps. 46 steps, 1 vague phrases
  • 100Execution cost. Instruction body is 1636 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (4 tags): a typed call is more reliable

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
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 447: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 46 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (1 of 2)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

External checks

ClawHub: suspicious
This appears to be a real personal-wiki helper, but it also performs persistent setup, git publication workflows, and optional memory reads that need careful review before use.
LLM: suspicious (high) · 28 May 2026