Bias Assessor
v1.0.0Add bias/risk-of-bias assessment fields to an extraction table and populate them consistently. **Trigger**: bias, risk-of-bias, RoB, evidence quality, 偏倚评估,...
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The skill's name/description (add RoB fields to papers/extraction_table.csv) matches the runtime instructions and the declared requirement of python. The bundle also includes a large set of pipeline manifests and helper modules (tooling/*.py and many pipelines), which increases the attack surface compared with a minimal single-file helper but is coherent in the context of a research-pipeline collection.
Instruction Scope
SKILL.md explicitly limits inputs to papers/extraction_table.csv and outputs to an updated extraction_table.csv, prescribes a simple 3-level scale and short notes, and states 'Network: none'. The instructions do not ask the agent to read unrelated files, environment variables, or to transmit data externally.
Install Mechanism
No install spec is provided (instruction+bundled python modules). That is low-risk: nothing is downloaded at install time. The declared runtime requirement (python/python3) is appropriate for the included Python code.
Credentials
The skill requests no environment variables, credentials, or config paths. This is proportionate to a local CSV-editing utility.
Persistence & Privilege
The skill is not marked always:true and does not request elevated persistence or to modify other skills. The default ability for the agent to invoke the skill autonomously is unchanged and not by itself suspicious here.
Assessment
This skill appears to do what it claims: it reads papers/extraction_table.csv and populates conservative RoB fields (low|unclear|high) with short notes. Things to consider before installing: 1) Back up your papers/extraction_table.csv before running the skill (the tooling contains atomic write/backup helpers but always keep a copy). 2) The package includes many pipeline manifests and helper modules (larger code bundle than a tiny single-script helper); if you want minimal surface area, review or run only the specific script that edits extraction_table.csv. 3) Confirm you will run this in a workspace that does not contain sensitive files you don't want touched (the skill writes local files but declares no network access or credentials). 4) If you need stronger assurance, inspect tooling/quality_gate.py and the scripts that will be executed (scripts/run.py is referenced by the executor) to verify they only perform local CSV/file updates. 5) Human oversight is appropriate: review the produced rob_* fields and notes for errors or systematic drift.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
Runtime requirements
Any binpython3, python