Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Varnan-Tech/opendirectory --skill linkedin-job-post-to-buyer-pain-mapgit clone --depth 1 https://github.com/Varnan-Tech/opendirectoryWrote 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/varnan-tech/opendirectory/linkedin-job-post-to-buyer-pain-map)<a href="https://agentmods.dev/skills/varnan-tech/opendirectory/linkedin-job-post-to-buyer-pain-map"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/linkedin-job-post-to-buyer-pain-map/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/varnan-tech/opendirectory/linkedin-job-post-to-buyer-pain-map"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/linkedin-job-post-to-buyer-pain-map.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 29 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 Supply Chain · line 113 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 151 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 113 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 151 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00134 | $0.03335 |
| Opus 5 | $0.00067 | $0.01667 |
| Sonnet 5 | $0.00027 | $0.00667 |
| Haiku 4.5 | $0.00013 | $0.00333 |
Grade A, and why
linkedin-job-post-to-buyer-pain-map scanned grade A with 1 finding 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 13d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST \ How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Job Post to Buyer Pain Map
Take LinkedIn job posts. Decode them into a structured buyer pain map with scores, pains, and outreach angles.
Critical rule: Every inferred pain must cite specific language from the job description that supports it. Never hallucinate pains that are not grounded in the text. If a post is too generic to infer pain, say so explicitly and assign a low signal strength score.
Ethical rule: Do not infer personal attributes or protected characteristics about candidates. Focus strictly on company-level operational pain and organizational needs.
Step 1: Setup Check
Confirm required env vars:
echo "GEMINI_API_KEY: ${GEMINI_API_KEY:+set}"
If GEMINI_API_KEY is missing: Stop. Tell the user: "GEMINI_API_KEY is required. Get it at aistudio.google.com. Add it to your .env file."
Step 2: Collect Inputs
The skill needs 3 required inputs. Collect them before proceeding.
2a: Product Brief
Ask: "Describe your product in 2-5 sentences. What do you do, what is your core value prop, and who do you target?"
If the user already included this in their prompt: Extract it. Confirm: "Product brief captured: [summary]."
2b: ICP Description
Ask: "Describe your ideal customer profile in 2-6 bullets: industries, company sizes, roles you sell to, tech stack hints."
If the user already included this in their prompt: Extract it. Confirm: "ICP captured: [summary]."
2c: Hiring Posts
Ask: "Paste the job descriptions you want analyzed. For each post, include the company name, job title, and the full description text. You can paste 1-15 posts."
Accepted formats:
- Raw pasted text with company name and job title clearly labeled
- Structured JSON objects with fields:
company_name,job_title,location(optional),seniority(optional),team_or_function(optional),job_description_text,job_url(optional) - Multiple posts separated by clear delimiters (--- or numbered)
If any field is missing: Infer what you can from the description text. If company_name or job_description_text is missing, ask for it before proceeding.
What ships with it
6 files 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.
- 13d ago First seen · 302 lines · 134 tokens per session scan A e6310d0cf72c
linkedin-job-post-to-buyer-pain-map is a skill published in the GitHub repository Varnan-Tech/opendirectory (640 stars, last pushed 27d ago), licensed MIT. It adds 134 tokens to every session and 3,335 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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