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BC hosted-agents

This skill should be used when designing hosted or background agent infrastructure: sandboxed execution, remote coding environments, warm pools, session persistence, multiplayer collaboration, self-spawning agents, or Modal-style sandboxes.

muratcankoylan/Agent-Skills-for-Context-Engineering Agent Skills author: muratcankoylan MIT 3 files · 1 script body ≈ 4 359 tokens Open the sourcegithub.com↗ analyzed 7 d ago

This skill should be used when designing hosted or background agent infrastructure: sandboxed execution, remote coding environments, warm pools, session…

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

IntegrationSlackGitHubAI and agentstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
97
Quality 40%
85
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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

    ✓ No critical or high findings

    Medium and low: 3
    • low Dangerous commands cmd-eval-dynamic references/infrastructure-patterns.md:43
      Dynamic code execution from decoded/untrusted input (documentation of a security skill)
      os.system(f"git clone https://x-access-token:{token}@github.com/{self.repo_url}")
      security skill
    • low Dangerous commands cmd-eval-dynamic references/infrastructure-patterns.md:51
      Dynamic code execution from decoded/untrusted input (documentation of a security skill)
      os.system(f'git config user.name "{user_identity["name"]}"')
      security skill
    • low Dangerous commands cmd-eval-dynamic references/infrastructure-patterns.md:52
      Dynamic code execution from decoded/untrusted input (documentation of a security skill)
      os.system(f'git config user.email "{user_identity["email"]}"')
      security skill

    Files scanned: 3. 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 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 18 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 70Execution cost. Instruction body is 4359 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 119 steps
    • 100Consistency. Name and required fields are in place
    • low 10 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
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 240: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 119 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.