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 zhiweio/resume-as-code --skill timeline-polishinggit clone --depth 1 https://github.com/zhiweio/resume-as-codeWrote 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/zhiweio/resume-as-code/timeline-polishing)<a href="https://agentmods.dev/skills/zhiweio/resume-as-code/timeline-polishing"><img src="https://agentmods.dev/badge/skills/zhiweio/resume-as-code/timeline-polishing/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/zhiweio/resume-as-code/timeline-polishing"><img src="https://agentmods.dev/badge/skills/zhiweio/resume-as-code/timeline-polishing.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 | $0.00088 | $0.01039 |
| Opus 5 | $0.00044 | $0.00519 |
| Sonnet 5 | $0.00018 | $0.00208 |
| Haiku 4.5 | $0.00009 | $0.00104 |
Grade A, and why
timeline-polishing 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 10d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Timeline Polishing
Convert raw, free-form descriptions of past experiences into rich, structured YAML files that live in the candidate's master timeline library under data/timeline/. These polished entries are the source of truth that the resume-generation skill later draws from.
When to trigger
Activate when the user provides raw notes (a paragraph, bullet list, journal entry, old job description, etc.) about either:
- A past job, role, internship, or employment period — polish as work experience.
- A specific project, deliverable, academic project, or hackathon — polish as a project.
If the type is ambiguous, ask the user one clarifying question before proceeding.
Inputs you will receive
- Raw text describing the experience.
- Optional: target language. If unspecified, detect it from the input; default to English.
Outputs you will produce
A single YAML file under data/timeline/:
- Path:
data/timeline/{Type}_{TimeRange}_{Title}.ymlType—WorkorProject.TimeRange—YYYYMMDD-YYYYMMDDfor completed entries, orYYYYMMDD-Nowfor ongoing entries (e.g.20221114-20240531,20221114-Now).Title— the job title or project name.
Workflow
1. Classify the input
Decide whether the description is a work experience or a project. If unclear, ask the user.
2. Polish using the matching methodology
- Work experience → follow references/work-experience.md. Methodology: Enhanced STAR (business-focused Situation, Task, Action, Result). Goal: reframe every achievement with business-first storytelling — lead with business challenges and outcomes, show problem-solving methodology, quantify in business terms, use transferable language that works across industries.
- Project → follow references/project.md. Methodology: Enhanced 3W (business-focused What, Why, How). Goal: reframe every achievement with business-first storytelling — define scope by business value, explain business drivers, show decision-making methodology and trade-off analysis, quantify outcomes in business terms.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 70 lines · 88 tokens per session scan A f966e6daacf2
timeline-polishing is a skill published in the GitHub repository zhiweio/resume-as-code (89 stars, last pushed 1mo ago), licensed MIT. It adds 88 tokens to every session and 1,039 once invoked, about $0.0004 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.
Other skills, from other repositories
cv-resume-builder
Optimize resumes and CVs for impact, ATS compatibility, and audience targeting. Supports multiple formats (chronological, functional, hybrid), accomplishment framing (STAR/XYZ), and tailoring for specific roles. Triggers on resume review, CV update, job application prep, or career document requests.
apply-high-performer-retention
Use when a manager wants to proactively retain top-performing direct reports — because high performers have the most options to leave and require active, differentiated management attention to stay engaged and challenged.
run-career-conversation
Use when a manager wants to have a structured career development conversation with a direct report — separate from weekly one-on-ones and performance reviews — to understand their long-term aspirations, identify growth gaps, and create a concrete development plan.
run-reference-check
Use when evaluating a finalist candidate for a role — to conduct structured phone reference calls that surface specific performance evidence, development needs, and potential red flags that interviews cannot reveal.
write-role-scorecard
Use when defining a role before hiring for it — to specify the outcomes the new person must achieve, the competencies required to achieve them, and the cultural requirements, so that interview questions target evidence of actual job performance rather than proxies like credentials or experience.
run-behavioral-interview
Use when conducting a job interview — to ask structured behavioral questions using the STAR method so that candidate evaluation is based on demonstrated past behavior rather than self-reported traits or hypothetical answers.