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BC disinto-factory

Set up and operate a disinto autonomous code factory. Use when bootstrapping a new factory instance, checking on agents and CI, managing the backlog, or troubleshooting the stack.

ClawHub Agent Skills author: johba37 v0.2.1 MIT-0 4 files · 1 script body ≈ 1 747 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, running it twice, progress reporting

ProcedureSoftware developmentInfrastructureAI 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
82/100
safety, quality, tests
Safety 60%
84
Quality 40%
80
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

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.

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 · 8

    ✓ No critical or high findings

    Medium and low: 8
    • medium Exfiltration net-credential-use SKILL.md:178
      Credential used in a network call (verify the destination is the intended service)
      WP_CSRF=$(curl -sf -b "user_sess=$WOODPECKER_TOKEN" http://loca…000/web-config.js \
    • medium Exfiltration net-credential-use SKILL.md:180
      Credential used in a network call (verify the destination is the intended service)
      curl -sf -b "user_sess=$WOODPECKER_TOKEN" -H "X-CSRF-Token: $WP_CSRF" \
    • low Dangerous commands cmd-cron-mention SKILL.md:64
      Mentions editing / listing crontab
      docker exec -u agent disi…s-1 crontab -l -u agent
    • low Exfiltration read-dotenv SKILL.md:67
      Reads a .env file (detector / deny-list definition)
      docker exec disi…s-1 bash -c "source /home/agent/disinto/.env && curl -sf http://forg…000/api/v1/version | jq .version"
      detector
    • low Exfiltration read-dotenv SKILL.md:76
      Reads a .env file (detector / deny-list definition)
      docker exec -u agent disi…s-1 bash -c "source /home/agent/disinto/.env && git clone http://dev-bot:\${FORGE_TOKEN}@forg…000/<org>/<repo>.git /home/agent/repos/<name>"
      detector
    • low Exfiltration read-dotenv SKILL.md:106
      Reads a .env file
      source .env && source lib/env.sh && export PROJECT_TOML=projects/<name>.toml && source lib/load-project.sh && source lib/mirrors.sh && mirror_push
    • low Exfiltration read-dotenv SKILL.md:119
      Reads a .env file
      source .env
    • low Exfiltration read-dotenv SKILL.md:158
      Reads a .env file
      source .env

    Files scanned: 4. 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 58/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 26 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1747 tokens
    • high The skill tells the model to perform an irreversible action with no human approval
    • low The response is described with custom markup (3 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
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • -2localhost URLs: will not work for another user
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 179: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (15 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: suspicious
    The skill appears coherent for running an autonomous code factory, but it includes broad repo, CI, credential, and container-control steps with some under-scoped destructive and privileged operations.
    LLM: suspicious (high) · VirusTotal: · 28 May 2026