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DC wikisage

A Karpathy-style persistent LLM wiki. Use when: (1) user says '加进wiki/ingest/摄入', (2) user says '查wiki/wiki里有没有', (3) user says '整理wiki/lint', (4) answering questions that should check long-lived local knowledge first. Also use after answering valuable technical questions to ask if user wants to save to wiki.

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: HarryZhu v1.0.0 MIT-0 9 files body ≈ 1 067 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI 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
D
59/100
safety, quality, tests
Safety 60%
45
Quality 40%
81
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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.

Exfiltration
If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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.
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 · 4

  • high Exfiltration exfil-webhook-url README.md:242
    Webhook / callback URL commonly used for exfiltration (verify the destination)
    --data '{"text":"{}"}' https://hooks.slack.com/services/XXX/YYY/ZZZ
  • high Exfiltration exfil-webhook-url README.md:251
    Webhook / callback URL commonly used for exfiltration (verify the destination)
    --data '{"content":"{}"}' https://discord.com/api/webhooks/XXX/YYY
  • high Dangerous commands cmd-persistence README.md:267
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    Register-ScheduledTask -TaskName "wikisage-weekly-lint" `
Medium and low: 1
  • low Exfiltration exfil-webhook-url scripts/lint.py:25
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    python3 lint.py --summary | curl -X POST -d @- https://hooks.slack.com/services/...
    placeholder

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 53/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 14 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1067 tokens
  • 100Running it twice. No mutating operations
  • 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
  • -31 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 310: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
Wikisage is a disclosed agent-maintained local wiki skill with expected file writes and persistence, though users should treat the wiki and optional cloud embedding features as sensitive.
LLM: benign (high) · VirusTotal: · 29 May 2026