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BC claw-bond

Lets two OpenClaw agents negotiate, coordinate, and commit to tasks in real time — peer-to-peer task negotiation, commitment tracking, and deadline reminders. Uses a relay for connection setup; all messages are end-to-end encrypted.

ClawHub Agent Skills author: techtanush v2.1.7 MIT-0 24 files body ≈ 5 761 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubSales and CRMAI 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
81/100
safety, quality, tests
Safety 60%
93
Quality 40%
62
Run on models
none yet
Process rating
C
57/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Result and completion w 14
40
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: claw-bond (ClawHub)

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 · 7

✓ No critical or high findings

Medium and low: 7
  • low Secrets in code secret-high-entropy-token negotiate.py:109
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    NOISE_PATTERN: bytes = b"Nois…256"
    detector
  • low Dangerous commands cmd-cron-mention negotiate.py:2739
    Mentions editing / listing crontab (string literal in code, not executed)
    f.write("#   crontab -e\n\n")
    code literal
  • low Dangerous commands cmd-cron-mention negotiate.py:2774
    Mentions editing / listing crontab (string literal in code, not executed)
    f"To activate Path A alerts: run `crontab -e` and paste that line.\n"
    code literal
  • low Dangerous commands cmd-cron-mention negotiate.py:2857
    Mentions editing / listing crontab (string literal in code, not executed)
    print(f"Crontab entry written to: {cron_file}\nRun `crontab -e` and paste that line to activate Path A alerts.")
    code literal
  • low Dangerous commands cmd-cron-mention permissions.json:76
    Mentions editing / listing crontab (quoted — discussed, not commanded)
    "cron_note": "negotiate.py install writes a ready-to-paste crontab line to skills/claw-bond/crontab-entry.txt. No cron entry is registered automatically. The user pastes it manually via crontab -e. cr
    quoted
  • low Exfiltration read-dotenv relay/docker-compose.yml:4
    Reads a .env file (code comment)
    #   cp .env.example .env   # then fill in RELAY_SECRET
    comment
  • low Exfiltration read-dotenv relay/README.md:16
    Reads a .env file
    cp .env.example .env

Files scanned: 24. 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 ≈ 5761 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 57/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 40Result and completion. Does not say what the result is
  • 40Consistency. Frontmatter name (claw-bond) differs from the folder (claw-connector)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5761 tokens
  • 100Steps. 81 steps
  • 100Failures and branches. 4 branches, has a failure section
  • 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 21 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (6 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 232: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 81 items
  • +4Has examples (39 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: suspicious
This peer-collaboration skill is mostly coherent, but it needs Review because it has broad network, memory, background-listener, and cross-agent context behavior with some unclear or inconsistent controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026