Borrowing it
Nothing to install: this file belongs to dfirtnt/Huntable-CTI-Studio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dfirtnt/Huntable-CTI-Studio/main/.cursor/skills/lg-workflow/SKILL.mdgit clone --depth 1 https://github.com/dfirtnt/Huntable-CTI-StudioWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dfirtnt/huntable-cti-studio/lg-workflow)<a href="https://agentmods.dev/skills/dfirtnt/huntable-cti-studio/lg-workflow"><img src="https://agentmods.dev/badge/skills/dfirtnt/huntable-cti-studio/lg-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dfirtnt/huntable-cti-studio/lg-workflow"><img src="https://agentmods.dev/badge/skills/dfirtnt/huntable-cti-studio/lg-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.00457 |
| Opus 5 | $0.00035 | $0.00229 |
| Sonnet 5 | $0.00014 | $0.00091 |
| Haiku 4.5 | $0.00007 | $0.00046 |
Grade A, and why
lg-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
LG (Looks Good) Workflow
When the user says lg or LG, run the full workflow yourself from hygiene through push to the current branch. Do not stop at commit or ask the user to push manually.
Order
- Full hygiene (so the commit includes these updates):
- Deslop — Check diff against main and remove AI-generated slop (unnecessary comments, defensive checks, any casts, inconsistent patterns). Keep behavior unchanged.
- Changelog — Update CHANGELOG (or
docs/CHANGELOG.md) with this session's changes. - Docs — Ensure docs reflect changes (README, GETTING_STARTED, or touched features).
- Deps — Verify dependency hygiene (e.g.
pip check, lockfiles). - Security — Run
pip-auditandsafety scan(requirespip install -r requirements-test.txt). - Vulture — Run
.venv/bin/vulture src scriptsfor dead-code detection. Fix or whitelist findings before commit.
- Stage —
git add(or equivalent) so all changes are staged. - Commit — Commit with a clear message (no auto-commit before user says LG).
- Push — Push the current branch (e.g.
git push origin HEADorgit push). Complete the push; do not hand off to the user.
Fallback
If the environment's git wrapper breaks (e.g. unsupported --trailer), use the real git binary (e.g. /usr/local/bin/git) so the workflow completes.
Trigger
Only run this workflow when the user has said LG. Do not commit/push on "go" or "implement" unless they also say LG.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 30 lines · 70 tokens per session scan A eaf3b0372628
lg-workflow is a skill published in the GitHub repository dfirtnt/Huntable-CTI-Studio (11 stars, last pushed 3d ago), licensed MIT. It adds 70 tokens to every session and 457 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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