Borrowing it
Nothing to install: this file belongs to Othmane-Khadri/YALC-the-GTM-operating-system. 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/Othmane-Khadri/YALC-the-GTM-operating-system/main/.claude/skills/qualify-leads/SKILL.mdgit clone --depth 1 https://github.com/Othmane-Khadri/YALC-the-GTM-operating-systemWrote 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/othmane-khadri/yalc-the-gtm-operating-system/qualify-leads)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/qualify-leads"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/qualify-leads/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/othmane-khadri/yalc-the-gtm-operating-system/qualify-leads"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/qualify-leads.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 83 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 90 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium MCP Rug Pull · line 32 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 84 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 91 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00125 | $0.01512 |
| Opus 5 | $0.00063 | $0.00756 |
| Sonnet 5 | $0.00025 | $0.00302 |
| Haiku 4.5 | $0.00013 | $0.00151 |
Grade A, and why
qualify-leads 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 12d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- coding-standards — 86% identical, 134 lines differ
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Qualify Leads
I'll wrap leads:qualify. I'll ask for the input source and path, validate locally, run the CLI, parse the per-gate counts, and surface the result-set id so you can hand it to launch-linkedin-campaign or personalize-message.
When This Skill Applies
Use this skill when the user says:
- "qualify these leads"
- "score this lead list"
- "run the qualification pipeline"
- "check if these leads are a fit"
- "qualify the engagers"
NOT this skill (use personalize-message instead):
- "personalize a message for this lead" — that wraps the
personalizeCLI and writes a single LinkedIn DM, it doesn't run the gate pipeline. - "draft a DM for [lead]" — same.
NOT this skill (use scrape-post-engagers instead):
- "scrape engagers off this LinkedIn post" — that wraps
leads:scrape-post. Run that first to produce an engagers JSON, then come back here to qualify it.
What This Skill Does
- Asks where the leads live (CSV path, JSON path, Notion DB id, visitors export, engagers export, or an existing result-set id).
- Validates the input locally — file exists, Notion id has the right shape, result-set id format looks plausible.
- Shells out to
npx tsx src/cli/index.ts leads:qualify <args>from~/Desktop/gtm-os/. - Parses the CLI's stdout — the pipeline emits per-gate counters and the resultSetId.
- Renders a clean per-gate summary, the result-set id, and the top hot leads.
- Offers two follow-up moves: launch a campaign or personalize messages.
What This Skill Does NOT
- Send any outbound messages. That's
launch-linkedin-campaign(LinkedIn) orsend-cold-email(email). - Author personalized message bodies. That's
personalize-message. - Re-import data that's already a result set. If the user already has a resultSetId, pass
--result-set <id>and skip--source/--input. - Modify any
.envfile. If a key is missing, the CLI raises and we surface its stderr verbatim.
Pre-flight (do this before step 1)
- Onboarding interruption guard. Run:
Iftest -f ~/.gtm-os/.in-flight-setup && echo "BLOCKED" || echo "OK"BLOCKED, stop. Tell the user: "Setup is mid-flight. Finishyalc-gtm startfirst, then re-invoke me." Exit cleanly.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 121 lines · 125 tokens per session scan A b95a342f8d06
qualify-leads is a skill published in the GitHub repository Othmane-Khadri/YALC-the-GTM-operating-system (301 stars, last pushed 22d ago), licensed MIT. It adds 125 tokens to every session and 1,512 once invoked, about $0.0006 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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kn-handoff
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kn-spec
Use when creating a specification document for a feature (SDD workflow).
kn-flow
Use when orchestrating a full Knowns spec or task wave through planning, implementation, review, integration, and verification, optionally using sub-agents when scopes are parallel-safe.
kn-debug
Use when debugging errors, test failures, build issues, or blocked tasks — structured triage to fix to learn.
kn-research
Use when you need to understand existing code, find patterns, search project knowledge, investigate current external facts, or explore a large codebase before implementation.