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 tmargolis/career-navigator --skill content-suggestgit clone --depth 1 https://github.com/tmargolis/career-navigatorWrote 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/tmargolis/career-navigator/content-suggest)<a href="https://agentmods.dev/skills/tmargolis/career-navigator/content-suggest"><img src="https://agentmods.dev/badge/skills/tmargolis/career-navigator/content-suggest/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/tmargolis/career-navigator/content-suggest"><img src="https://agentmods.dev/badge/skills/tmargolis/career-navigator/content-suggest.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00029 | $0.00357 |
| Opus 5 | $0.00015 | $0.00179 |
| Sonnet 5 | $0.00006 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
content-suggest 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 9d 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.
What it actually says
Invoke writer in content-suggest mode.
Invocation
- Use the exact agent name
writer. Retry once if invocation fails.
Workflow
- Read
{user_dir}/CareerNavigator/profile.md,{user_dir}/CareerNavigator/ExperienceLibrary.json, andvoice-profile.mdif present. - Ask
writerfor 5–8 topic ideas with: why it fits, risk level (low drama vs spicy), and suggested format (short post vs thread vs link + comment). - If the user wants a full draft of one topic: ensure
writervoice preflight is satisfied (voice-profile.mdhas## User writing samplesor## User writing samples (launch), or ask once for posts / skip—same pattern asdraft-outreach). Then invokewriterto draft one post.writermust save the draft as.mdunder{user_dir}/LinkedIn Posts/(create the folder if needed), appendartifacts-index.jsonwith"type": "linkedin_post", and tell the user the file path to open and edit. Offerevaluate-postbefore they publish.
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.
- 9d ago First seen · 23 lines · 29 tokens per session scan A 6e2d9d1d510a
content-suggest is a skill published in the GitHub repository tmargolis/career-navigator (13 stars, last pushed 10d ago), licensed Apache-2.0. It adds 29 tokens to every session and 357 once invoked, about $0.0001 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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