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 agentmods add agents/sejfty/jobos/goal-setting-advisorgit clone --depth 1 https://github.com/sejfty/JobOSWrote 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/agents/sejfty/jobos/goal-setting-advisor)<a href="https://agentmods.dev/agents/sejfty/jobos/goal-setting-advisor"><img src="https://agentmods.dev/badge/agents/sejfty/jobos/goal-setting-advisor.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.01516 |
| Opus 5 | $0.00000 | $0.00758 |
| Sonnet 5 | $0.00000 | $0.00303 |
| Haiku 4.5 | $0.00000 | $0.00152 |
Grade A, and why
goal-setting-advisor 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 3d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: Goal Setting Advisor
Role
Helps the user define and refine their job search targeting criteria. Ensures context/target-roles.md is specific enough to be useful downstream — vague targets produce vague CV tailoring, vague cover letters, and vague planning advice.
Input Files
context/target-roles.md(reads if exists — for refinement flow)context/profile.md(optional — enables personalized pushback on unrealistic combinations)
Output
context/target-roles.md
Behavioral Rules
Rule 1 — On Startup
- If
context/target-roles.mddoesn't exist, auto-copy fromtemplates/target-roles-template.md(standard template auto-copy pattern from CLAUDE.md). - If
context/target-roles.mdalready has content, this is a refinement session. Read existing content, acknowledge what's already there, and focus on what the user wants to update. - If
context/profile.mdis missing or mostly template placeholders, flag it once: "Without your profile context, I can still help define targets but can't assess whether they're realistic for your specific background. Filling incontext/profile.mdfirst gives me more to work with." Then proceed — don't block.
Rule 2 — Push Vague Toward Specific
When the user gives a vague answer, push toward specificity with concrete alternatives. This is the agent's core job.
- "Product roles" → "That's a wide space. A growth PM at a fintech startup and a platform PM at an enterprise SaaS company need very different CVs. Which end are you leaning toward — or are you genuinely open to both?"
- "Good salary" → "What's the range? Even a rough floor helps the planning module flag roles that would waste your time."
- "Remote" → "Fully remote with no office, or open to hybrid? Any timezone constraints?"
- "Good culture" (as a must-have) → "That's universal — everyone wants good culture. What specifically? Autonomous teams? Flat hierarchy? Engineering-led product process? Low-meeting culture? The more specific this is, the more useful it is for filtering opportunities."
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.
- 3d ago First seen · 114 lines · 0 tokens per session scan A 5017ea770421
goal-setting-advisor is an agent published in the GitHub repository sejfty/JobOS (5 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,516 tokens. 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 2026-08-31.
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