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Secure computer-to-computer networking for AI agents — gossip broadcast, direct messaging, CRDTs, group encryption. Post-quantum encrypted, NAT-traversing. Everything you need to build any decentralized application.

ClawHub Agent Skills author: Jim Collinson v0.44.0 MIT-0 2 files body ≈ 18 446 tokens Open the sourceclawhub.ai↗ analyzed 7 h ago

Secure computer-to-computer networking for AI agents — gossip broadcast, direct messaging, CRDTs, group encryption.

As a process F 42/100 · Will not run — References files that are not bundled: scripts/install.py

GeneratorGitHubAI and agentstype 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%
95
Quality 40%
54
Run on models
none yet
Process rating
F
42/100
Will not run
References files that are not bundled: scripts/install.py
Tools and files w 18
0
Result and completion w 14
0
Execution cost w 6
10
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.
  3. 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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Exfiltration net-credential-use SKILL.md:164
    Credential used in a network call (verify the destination is the intended service) (destination host is a configured variable; documentation of a security skill)
    curl -s -H "Authorization: Bearer $TOKEN" "http://$API/status"
    variable hostsecurity skill
  • low Exfiltration net-credential-use SKILL.md:174
    Credential used in a network call (verify the destination is the intended service) (destination host is a configured variable; documentation of a security skill)
    curl -X POST "http://$API/subscribe" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" -d '{"topic":"hello-world"}'
    variable hostsecurity skill
  • low Exfiltration net-credential-use SKILL.md:175
    Credential used in a network call (verify the destination is the intended service) (destination host is a configured variable; documentation of a security skill)
    curl -X POST "http://$API/publish"   -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
    variable hostsecurity skill
  • low Exfiltration net-credential-use SKILL.md:177
    Credential used in a network call (verify the destination is the intended service) (destination host is a configured variable; documentation of a security skill)
    curl -N -H "Authorization: Bearer $TOKEN" "http://$API/events"     # SSE; fields nested under "data"
    variable hostsecurity skill
  • low Exfiltration net-credential-use SKILL.md:201
    Credential used in a network call (verify the destination is the intended service) (destination host is a configured variable; documentation of a security skill)
    curl -X PUT "http://$API/profile" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
    variable hostsecurity skill

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")
  • warning body-long SKILL.md body ≈ 18446 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/install.py
  • note frontmatter-key unknown frontmatter key "repository"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "keywords"
  • note edit-residue the text marks something as outdated (lines 324, 401, 588, 674, 707, 728): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: scripts/install.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/install.py
  • 0Result and completion. Does not say what the result is
  • 10Execution cost. Instruction body is 18446 tokens: crowds the task out of the window
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 38 steps, 1 vague phrases
  • 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 14 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (25 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 215: enough signal without eating the budget
  • +4Structure: 43 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (40 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.

External checks

ClawHub: suspicious
The skill is mostly transparent about being a powerful networking daemon, but its install and update paths create meaningful review risk because they fetch mutable executable code and include high-impact daemon, remote execution, and self-update capabilities.
LLM: suspicious (high) · 13 Sept 2026