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 skills/tmargolis/career-navigator/benchmarknpx skills add tmargolis/career-navigator --skill benchmarkgit 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/benchmark)<a href="https://agentmods.dev/skills/tmargolis/career-navigator/benchmark"><img src="https://agentmods.dev/badge/skills/tmargolis/career-navigator/benchmark.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 | $0.00041 | $0.01227 |
| Opus 5 | $0.00020 | $0.00613 |
| Sonnet 5 | $0.00008 | $0.00245 |
| Haiku 4.5 | $0.00004 | $0.00123 |
Grade A, and why
benchmark 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 4d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark the user's pipeline performance against industry norms for their role, level, company size, and geography.
Workflow
1. Check data threshold
Application data uses the split layout defined in references/tracker-schema.md — read it before any read or write.
Read {user_dir}/CareerNavigator/tracker.json. Count the total number of applications (any status) from the summary rows — no detail files needed for this check. If fewer than 5:
"You need at least 5 applications to run a meaningful benchmark — you have {n} so far. Keep logging applications via
/career-navigator:track-applicationand run this again once you have more history."
Stop here if below threshold.
If ≥5 but fewer than 10 resolved outcomes, proceed with a note that results are preliminary.
2. Load the stage history the conversion math needs
Every PIPELINE CONVERSION and TIMELINES figure below is computed from stage_history[], and tracker.json alone contains no stage history — it moved to the per-application detail files. Computing app → response, screen → interview, interview → offer, or days-to-response from tracker.json by itself silently yields zeros and reports the user as far below norm when they are not.
- Read
{user_dir}/CareerNavigator/tracker.jsonand takeapplications[]. - Iterate every row and load its
detail_file(relative toCareerNavigator/) for that application'sstage_history[]. Skip a row only when itsstage_countis0— that row genuinely has no stages to count. - Use the summary fields where they answer the question directly:
latest_stageandlatest_stage_dategive the current funnel position and last movement date, andstage_count/notes_count/contact_countgive volumes without a read.
3. Invoke analyst — Operation 4
Hand off to the analyst agent with:
CareerNavigator/tracker.json(summary rows) plus the loadedapplications/<application_id>.jsondetail files — pass both; conversion and timeline math is impossible from summary rows alone- The full
CareerNavigator/artifacts-index.json - The full
CareerNavigator/profile.md - Instruction to run Operation 4: Market Benchmark
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.
- 4d ago First seen · 97 lines · 41 tokens per session scan A 1ef342316d6d
benchmark is a skill published in the GitHub repository tmargolis/career-navigator (14 stars, last pushed 6d ago), licensed Apache-2.0. It adds 41 tokens to every session and 1,227 once invoked, about $0.0002 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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