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BB sageox-distill

Sync, index, and distill team activity across SageOx-enabled repositories. Keeps your team's knowledge base up to date by syncing repo contexts, indexing GitHub PRs/issues, and running the SageOx distillation pipeline.

ClawHub Agent Skills author: Galex Yen v0.2.1 MIT-0 5 files · 2 scripts body ≈ 2 106 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 72/100 · Nearly there — weak spots: when it triggers, running it twice

ReferenceGitHubInfrastructuretype 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
88/100
safety, quality, tests
Safety 60%
99
Quality 40%
72
Run on models
none yet
Process rating
B
72/100
Nearly there
When it triggers w 12
20
Running it twice w 4
30
Tools and files w 18
60
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.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-pipe-to-shell scripts/install-ox-curl.sh:7
    Downloads and executes remote code from an unrecognised host (pipe to shell) (detector / deny-list definition; code comment)
    # Why this shape: scanners flag `curl | bash` of a remote shell script,
    detectorcomment

Files scanned: 5. 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")

Process rating: all ten parameters 72/100

  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 34 steps
  • 100Failures and branches. 8 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2106 tokens
  • 100Progress reporting. Reports progress
  • 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)
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 218: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 34 items
  • +3Output format is stated explicitly
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This skill appears designed for repository memory, but it needs Review because it can install a CLI and send repository/GitHub context to external services without clear up-front disclosure.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026