Skill Market Fit Ranker
v1.0.0对一批 Skill 选题按高频、低门槛、传播性、ROI 和风险做排序。；use for skills, market-fit, prioritization workflows；do not use for 只按个人偏好排序, 忽略发布风险.
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byvx：17605205782@52yuanchangxing
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the provided assets: a template-driven structured brief and a local Python script (scripts/run.py) that generates reports and audits. Declared requirement (python3) is appropriate and sufficient.
Instruction Scope
SKILL.md limits the skill to producing reviewable drafts and suggests invoking the local script. The script reads files and directories you supply (recursively), parses markdown/json/csv, and performs pattern scans. This file- and directory-reading behavior is expected for an auditing/prioritization tool, but it means the agent will access any files you pass as --input (do not point it at root or directories containing secrets).
Install Mechanism
No install spec is included and no external downloads occur. The skill is instruction- and script-based and only requires python3 (standard library). This is low-risk from an install perspective.
Credentials
The skill declares no environment variables, no credentials, and no config paths. The script does not access environment secrets or external credentials. Requested access (local files) is proportionate to the stated purpose.
Persistence & Privilege
always is false and disable-model-invocation is false (normal). The skill does not attempt to modify other skills or system-wide settings; it only reads local resources and can write output files when invoked with an explicit --output (or when not in dry-run).
Assessment
This skill appears to do what it says: create structured market-fit reports using a local Python script and templates. Before running it: (1) review scripts/run.py if you want to verify behavior; (2) do not point the script at system/root or folders containing secrets or credentials—it will read files recursively under the provided input path; (3) run with --dry-run or direct output to a controlled file to inspect results before publishing or taking actions; (4) the skill does not perform network calls or require API keys, so it is suitable for offline/local use. If you need higher assurance, run the script in an isolated environment (container or VM) and inspect outputs for sensitive content before sharing.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
📊 Clawdis
OSmacOS · Linux · Windows
Binspython3