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 mperkhou/career-agent-workbench --skill master-resume-yamlgit clone --depth 1 https://github.com/mperkhou/career-agent-workbenchWrote 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/mperkhou/career-agent-workbench/master-resume-yaml)<a href="https://agentmods.dev/skills/mperkhou/career-agent-workbench/master-resume-yaml"><img src="https://agentmods.dev/badge/skills/mperkhou/career-agent-workbench/master-resume-yaml/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/mperkhou/career-agent-workbench/master-resume-yaml"><img src="https://agentmods.dev/badge/skills/mperkhou/career-agent-workbench/master-resume-yaml.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 | $0.00042 | $0.00509 |
| Opus 5.5 | $0.00017 | $0.00204 |
| Sonnet 5.5 | $0.00008 | $0.00102 |
| Haiku 4.5 | $0.00004 | $0.00051 |
Grade A, and why
master-resume-yaml 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 2mo 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Master Resume YAML
Follow root AGENTS.md and resolve the external workspace through the normal
bootstrap/private-dotenv contract. This skill edits private profile evidence;
it never copies that evidence into the public repository or a test fixture.
Inputs and target
- Human source: the configured
MASTER_RESUME_TEXTmember, conventionallyprofile/MP-MASTER-RESUME.txtinside the private workspace. - Target MRO: the configured
MASTER_RESUMEmember, conventionallyprofile/MASTER-RESUME.yml. - Renderer:
scripts/render_resume_html.pyand the packaged resume template.
Read both sources before editing. Preserve intentional existing YAML structure unless the user explicitly requests a rebuild.
Required shape
Keep renderer-owned sections such as header, summary, Core Technical Skills, experience, education, certifications, and portfolio as mappings with explicit render state. Core-skill categories contain factual primary/additional items and empty job-specific match lists. Experience bullets retain source text, category links, supported skill links, and neutral zero match counters.
Every linked skill must exist in its declared Core Technical Skills category. Preserve meaningful compound phrases. Add missing evidence-supported skills to the appropriate category before linking them; never invent tools, scope, metrics, certifications, or responsibilities.
Passes
- Reconcile source sections and the bare YAML mapping.
- Normalize Core Technical Skills categories without job-specific matches.
- Link every experience bullet to supported categories and skills.
- Confirm neutral
jod_match_countandbullet_point_total_match_countvalues. - Render and visually review a private preview.
The MRO remains neutral. Per-job JOD matching and pruning belong in ARO generation, not this skill.
Validation and handoff
Use .venv/bin/python to parse YAML and render a preview into the configured
private tmp directory. Run focused resume-renderer tests and make lint for
code changes. Report only the selected source/target classes, bullet/category
counts, invariant booleans, and validation results; do not paste private
content, paths, or identifiers into public evidence.
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.
- 2mo ago First seen · 57 lines · 42 tokens per session scan A b6a9bf4977c3
master-resume-yaml is a skill published in the GitHub repository mperkhou/career-agent-workbench (0 stars, last pushed 2mo ago), licensed MIT. It adds 42 tokens to every session and 509 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
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