Market Research Reports
v1.0.0Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatt...
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
Name/description (professional market reports + heavy visuals) match the included assets (templates, visual prompts, generator script). However the SKILL.md repeatedly instructs the agent to call other skills/tools (scientific-schematics, generate-image, research-lookup) and expects a LaTeX style package (market_research.sty) that are not included or declared in the skill metadata. That makes the claimed end-to-end capability incomplete/unproven on its own.
Instruction Scope
Runtime instructions tell the agent to run many external python commands (e.g., skills/scientific-schematics/scripts/generate_schematic.py and skills/generate-image/scripts/generate_image.py), produce a large number of visuals, and to 'deep integrat[e] with research-lookup' for data gathering. Those referenced tools/paths are outside the skill bundle and no guidance is provided about required credentials, endpoints, or where data should come from. The skill grants the agent permission to run Bash and file Read/Write/Edit, so if executed it could attempt broad system activity trying to satisfy these instructions.
Install Mechanism
No install spec (instruction-only) — low direct install risk. There is one bundled script (generate_market_visuals.py) which calls external tools via subprocess. Because the skill assumes the presence of other skills/tools, it may fail or try to invoke arbitrary system commands in attempts to run missing programs.
Credentials
The skill requests no environment variables or credentials in metadata (good), yet the instructions mention deep integration with 'research-lookup' (likely requiring API access or credentials) and LaTeX compilation (may invoke xelatex/bibtex). The lack of declared env vars or dependency declarations is an informational gap: the skill could prompt the agent to use credentials or services that are not declared here.
Persistence & Privilege
always:false and no install hooks or persistent privilege requests. The skill does allow Bash and file operations while running, which is normal for an instruction-driven generator, but not combined with any forced always-on privilege.
What to consider before installing
This skill looks like a legitimate market-report generator but it relies on external tools and assets that are not bundled or declared. Before installing or invoking it:
- Confirm that the referenced tools (scientific-schematics, generate-image, research-lookup) exist in your agent environment and are trusted; otherwise the agent may fail or try to execute unexpected system commands.
- Check for the missing LaTeX style package (market_research.sty) and other required files—without them the output will be incomplete.
- Review scripts/generate_market_visuals.py line-by-line (it spawns subprocesses); ensure it does not run shell=True with untrusted input or call unknown network endpoints.
- If the skill will fetch external market data, determine what credentials or API endpoints it uses and avoid supplying high-privilege credentials (AWS keys, org-wide tokens) unless you verify them.
- Run the skill in a sandboxed environment first (isolated container or VM) and monitor network activity and file writes.
If you can validate the external dependencies and the generate script's behavior, the skill is usable; if not, treat it as untrusted and avoid running it with sensitive credentials or on production agents.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.