SKILLEMALL.ai

AC sageox

Complete toolkit for SageOx team knowledge. Query team context, manage AI coworkers, distill and summarize activity, see what coworkers are working on, catch up after time away, import/export knowledge, and manage configured repos. Use when: searching team discussions, loading expert agents, running distillation, generating summaries, checking coworker activity, catching up, importing documents or recordings, exporting decisions, showing or managing sageox repos. Keywords: SageOx, team context, query, coworker, distill, summary, glance, catchup, import, export, repos, manifest

ClawHub Agent Skills author: avi-ox-agola v0.1.0 MIT-0 17 files · 4 scripts body ≈ 965 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

GeneratorWriting and documentsInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
99
Quality 40%
81
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 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: 17. 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 61/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 5 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 12 steps
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 965 tokens

    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
    • -32 of 4 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 583: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (9 of 9)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: suspicious
    This SageOx skill is mostly coherent, but it deserves review because it can move repo, team, recording, and OpenClaw memory data into SageOx or Claude without strong per-action consent controls.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026