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 VonTerraProject501c3/slushpile --skill job-board-searchgit clone --depth 1 https://github.com/VonTerraProject501c3/slushpileWrote 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/vonterraproject501c3/slushpile/job-board-search)<a href="https://agentmods.dev/skills/vonterraproject501c3/slushpile/job-board-search"><img src="https://agentmods.dev/badge/skills/vonterraproject501c3/slushpile/job-board-search/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/vonterraproject501c3/slushpile/job-board-search"><img src="https://agentmods.dev/badge/skills/vonterraproject501c3/slushpile/job-board-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00067 | $0.09773 |
| Opus 5 | $0.00034 | $0.04887 |
| Sonnet 5 | $0.00013 | $0.01955 |
| Haiku 4.5 | $0.00007 | $0.00977 |
Grade A, and why
job-board-search 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.
How it starts
The opening of the file, as written. The whole thing — 567 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Board Search
Search a careers board, extract the postings, and score each one against the realistic applicant pool rather than against the posting's own keywords.
Two ways in. Name a company and this skill searches that company. Describe the work instead — a function, a place, a market — and Phase 0 resolves the description into a list of companies and searches each one. Everything after Phase 0 is identical either way, because the second mode's only job is producing the company list the first mode is handed directly.
Announce at start. Company mode: "Searching $COMPANY for roles matching the profile. Focus: $KEYWORDS. Scoring: pool-anchored, channel-conditional, contrarian-gated." Query mode: the same sentence with the resolved company count in place of $COMPANY, announced only after Phase 0e, so the user is never told a number that a confirmation step might still change.
Every templates/... path in this file is relative to the plugin, not to the workspace. The working directory is the user's job-search directory and does not contain them, so a bare templates/role_analysis.md resolves to nothing. Resolve them against the directory this skill file was itself loaded from — that works on every harness, where a harness-specific plugin-root variable does not.
Arguments: one required argument, read as either a company or a query. See Phase 0a for how to tell them apart and what to do when it is genuinely unclear.
- Company mode —
$1is a company name,$2+are role keywords. Keywords default totargeting.functionsinpreferences.yaml. - Query mode — the whole argument describes the work, the place, or the market. Constraints in the query are read on top of
preferences.yaml, never instead of it.
Examples:
/slushpile:job-board-search Anthropic applied AI
/slushpile:job-board-search Rivian manufacturing NPI
/slushpile:job-board-search Stripe
/slushpile:job-board-search applied AI roles within 50 miles of Martinsville, VA that fit my profile
/slushpile:job-board-search remote staff platform engineering at Series B infra companies
/slushpile:job-board-search who is hiring manufacturing engineers near me
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 · 567 lines · 67 tokens per session scan A d37dde4d7236
job-board-search is a skill published in the GitHub repository VonTerraProject501c3/slushpile (15 stars, last pushed 26d ago), licensed MIT. It adds 67 tokens to every session and 9,773 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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