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Gtm System

v1.0.0

Manage Go-To-Market activities including contacts, opportunities, pipeline stages, reminders, and signal crawling via command-line interface.

0· 674·0 current·0 all-time
byExpanso@aronchick
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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low confidence
Purpose & Capability
Name/description (GTM system) match the included docs: pipeline, contacts, reminders, crawlers. The bundle doesn't request unrelated credentials or system-level access. Note: the README/SKILL.md recommend integrations (Apollo, Syften, Telegram, GitHub, Twitter/X) — these are optional add-ons but the skill does not declare any required env vars for them.
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Instruction Scope
SKILL.md instructs the agent to run a local Python CLI against a hardcoded workspace path (/home/daaronch/.openclaw/workspace/gtm-system/) and to use crawlers for HN/Reddit/GitHub and to send digests via Telegram. Hardcoded absolute paths imply the instructions are tied to a developer's environment and may be incorrect for other users. The docs reference network crawling and webhook endpoints; without reviewing scripts/gtm.py we cannot confirm whether the CLI reads additional files, environment variables, or posts signals to third-party endpoints beyond what the docs describe.
Install Mechanism
No install spec — instruction-only with included code. No remote downloads or installers declared. This is lower-risk in terms of installation mechanism, but the included Python script will be written to disk as part of the skill bundle and executed when invoked.
Credentials
The skill declares no required env vars or external credentials, which is consistent with a basic SQLite-backed, self-hosted CLI. However, the documentation refers to optional integrations (Telegram bot, GitHub/Twitter/Syften/APIs) that typically require API keys; it is unclear whether gtm.py expects those keys be provided via environment variables or embeds calls that attempt unauthenticated scraping. Confirm whether credentials are needed and whether any are embedded in the code.
Persistence & Privilege
always:false and normal model-invocation settings. The skill stores data locally in data/gtm.db (SQLite) per docs — expected for this purpose. No declarations that it alters other skills or system-wide agent settings. Ensure that cron jobs referenced in docs are not automatically created without your consent (the docs mention cron but do not include an install step that sets them).
What to consider before installing
This package looks like a plausible local GTM tracker, but you should not run it blind. Before installing or running the CLI: 1) Open and read scripts/gtm.py to confirm where it makes network requests and what endpoints it posts to (look for URLs, webhook handlers, Telegram/GitHub/Twitter/Syften endpoints). 2) Search the code for any hardcoded tokens, API keys, or external servers (strings like 'http', 'https', 'api.', 'token', 'key', or personal domains). 3) Update the absolute paths in SKILL.md to match your own environment (or run from the repository root) — hardcoded /home/... paths indicate the docs were exported from someone else's machine. 4) If you enable crawlers or webhooks, prefer to run them from an isolated machine or test environment first and ensure rate limits/terms of service for target APIs. 5) If the script integrates with Telegram or other services, confirm it uses your bot/token (not an embedded token) and that you understand what data will be sent externally. 6) If you're not comfortable auditing the Python file yourself, ask for the full gtm.py source to be reviewed (or run it under a network monitor / sandbox) — because the CLI will have network access and will write to a local database, those are the primary places sensitive data could be exfiltrated. After you inspect the code and confirm no unexpected endpoints/credentials are present, it is reasonable to proceed.

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.

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