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 andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2- --skill comparegit clone --depth 1 https://github.com/andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2-Wrote 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/andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2-/compare)<a href="https://agentmods.dev/skills/andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2-/compare"><img src="https://agentmods.dev/badge/skills/andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2-/compare/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/andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2-/compare"><img src="https://agentmods.dev/badge/skills/andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2-/compare.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 | $0.00050 | $0.00745 |
| Opus 5 | $0.00025 | $0.00373 |
| Sonnet 5 | $0.00010 | $0.00149 |
| Haiku 4.5 | $0.00005 | $0.00075 |
Grade A, and why
compare 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 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.
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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compare Opportunities
Side-by-side comparison of evaluated job opportunities.
Step 0: Load Evaluations
Read all files in data/evaluations/. Parse the scores, archetype, company,
role, location, and compensation from each.
Step 1: Select Opportunities
- If user specified companies/roles: match to evaluations (fuzzy OK)
- If "compare my top options" or no argument: select top 3-5 by score with non-terminal status (Evaluated, Resume Ready, Applied, Interview)
- If fewer than 2 evaluations exist:
"You need at least 2 evaluated jobs to compare. Evaluate more postings first by pasting a JD."
Step 2: Comparison Table
## Opportunity Comparison
| Dimension | {Company A: Role} | {Company B: Role} | {Company C: Role} |
|---|---|---|---|
| **Score** | {X.X}/5.0 | {X.X}/5.0 | {X.X}/5.0 |
| **Archetype** | {type} | {type} | {type} |
| **Seniority** | {level} | {level} | {level} |
| **Location** | {loc} | {loc} | {loc} |
| **Compensation** | {range or "Not disclosed"} | {range} | {range} |
| **Strongest match** | {top requirement match} | ... | ... |
| **Biggest gap** | {main risk} | ... | ... |
| **Status** | {current status} | ... | ... |
Step 3: Pros and Cons
For each opportunity, list 3 specific pros and 2 specific cons. These must reference actual evaluation data, not generic statements.
### {Company A} - {Role}
**Pros:**
- {specific strength from Block B match}
- {compensation/location advantage}
- {career trajectory fit}
**Cons:**
- {specific gap or risk}
- {concern from evaluation}
Step 4: Recommendation
## My Recommendation
**Best overall match:** {Company - Role} ({score}/5.0)
{2-3 sentences: why this one stands out, what makes it the strongest fit}
**Best growth opportunity:** {Company - Role}
{1-2 sentences: highest upside if you can close the gaps}
**Safest option:** {Company - Role}
{1-2 sentences: most likely to result in an offer}
If scores are very close (within 0.3), say so:
"These are genuinely close. The tiebreaker is which company and role excites you most. Numbers can't measure that."
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 · 88 lines · 50 tokens per session scan A 69444284b849
compare is a skill published in the GitHub repository andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2- (490 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 745 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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