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 outreachgit 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/outreach)<a href="https://agentmods.dev/skills/vonterraproject501c3/slushpile/outreach"><img src="https://agentmods.dev/badge/skills/vonterraproject501c3/slushpile/outreach/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/outreach"><img src="https://agentmods.dev/badge/skills/vonterraproject501c3/slushpile/outreach.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 | $0.00064 | $0.05718 |
| Opus 5 | $0.00032 | $0.02859 |
| Sonnet 5 | $0.00013 | $0.01144 |
| Haiku 4.5 | $0.00006 | $0.00572 |
Grade A, and why
outreach 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.
How it starts
The opening of the file, as written. The whole thing — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Outreach
Find the warm path into one company, grade it honestly, and draft the message that uses it.
Everything upstream of here scores warm referral several times above cold submission, records which channel unlocks the tier, and then builds cold-portal materials anyway. Nothing in the pipeline ever went and found a referrer, so the warm row stayed informational forever and the user got measured against the channel the tool happened to support. This skill is what opens the other one.
Announce at start: "Finding a warm path into $COMPANY for $ROLE. Public professional sources only. Nothing is sent from here."
Arguments:
$1— path to a role folder containingrole_analysis.mdandapplication.yaml
Example:
/slushpile:outreach applications/Acme/Engineering/Staff-SRE
What a referral is worth
The premium comes from the vouch, not from the button. A person who can describe the user's work from memory changes how the resume is read before anyone opens it. A person who met them once and clicks refer produces a cold submission with a name attached, which converts a little above cold and spends a relationship to do it.
So what this skill produces is a graded path, a drafted ask, and a strength recorded where the next assessment reads it. It does not produce a referral, and recording one before a person has agreed to be it is how the tier gets inflated. Grade the path that exists, never the one the user is hoping for.
Prerequisites
Read these before deciding anything. The first two are what stop this skill from spending an ask on a role that was already killed.
- The role's
role_analysis.mdandapplication.yaml— the tier, the channel matrix, and which channel the tier came from - The role's
job_description.md— the team, the org, and any named hiring contact job_search.md— the Referrals table, the cooldowns, and this company's historyprofile.md— every employer, school, program, project, and venue the user has passed through. This is the raw material for finding a tie, and it is the file nobody thinks to read for one.preferences.yaml—identity.links,application_policy.posture, andvoice.agentcompanies.md— whether this company has been approached before, and how it went
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 · 335 lines · 64 tokens per session scan A 54f171b9fb2a
outreach is a skill published in the GitHub repository VonTerraProject501c3/slushpile (15 stars, last pushed 25d ago), licensed MIT. It adds 64 tokens to every session and 5,718 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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