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 dcassil/resume-kit --skill review-resumegit clone --depth 1 https://github.com/dcassil/resume-kitWrote 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/dcassil/resume-kit/review-resume)<a href="https://agentmods.dev/skills/dcassil/resume-kit/review-resume"><img src="https://agentmods.dev/badge/skills/dcassil/resume-kit/review-resume/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/dcassil/resume-kit/review-resume"><img src="https://agentmods.dev/badge/skills/dcassil/resume-kit/review-resume.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 | $0.00138 | $0.01995 |
| Opus 5 | $0.00069 | $0.00997 |
| Sonnet 5 | $0.00028 | $0.00399 |
| Haiku 4.5 | $0.00014 | $0.00199 |
Grade A, and why
review-resume 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.
How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Renamed:
review-resumewasreview-tailored-resumebefore v1.0.0 (see RIT-A-0005).
review-resume — subagent critique → structured findings (advice-only)
Take the (NEW tailored resume, ORIGINAL resume, JOB description) triple, hand it
to a reviewer subagent, and capture that reviewer's critique as a consistent,
machine-parseable markdown file under resume-kit/review/. This skill does ONE
thing: produce a review. It never mutates the resume — it only writes advice.
All state lives under resume-kit/ in the current project. config.json tracks
active_resume and active_job; the mutable in-progress resume lives at
resume-kit/working/<session>/resume.json.
Prerequisites
Run the shared Prerequisites gate first — see
_shared/prerequisites.md.
- Required inputs (all three):
- The NEW / tailored resume JSON —
resume-kit/working/<session>/resume.json(aResumeDocumentproduced by the tailoring skills). - The ORIGINAL resume JSON —
config.jsonactive_resume(the pristineresume-kit/resumes/<name>-original.json). - The JOB JSON —
config.jsonactive_job(aJobDescriptionunderresume-kit/jobs/).
- The NEW / tailored resume JSON —
- If any is missing: STOP. Do not guess or review on partial inputs. Name the
specific upstream skill to run first:
- No original resume JSON → run parse-resume.
- No job JSON → run parse-job.
- No tailored
working/<session>/resume.jsonyet → run the tailoring skills first (see resume-workflow —update-keywords/update-terminology).
Determine <session> from the tailored resume's path
(resume-kit/working/<session>/resume.json); reuse that same <session> for the
review filename so review and working copy stay paired.
Run me in a subagent
This is a self-contained, high-token critique task. The main agent should
dispatch it to a subagent (the Task tool / a general-purpose agent),
consistent with parse-resume, parse-job, and learn-terminology. Hand the
subagent: the three resolved JSON paths, the rubric below, and this skill. The
subagent reads the documents, critiques them, writes
resume-kit/review/<session>.md, and returns only a short summary (the overall
verdict + counts) — do NOT stream the full resume/job text back into the main
context.
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 · 172 lines · 138 tokens per session scan A 0526bebc9c8d
review-resume is a skill published in the GitHub repository dcassil/resume-kit (0 stars, last pushed 29d ago), licensed Apache-2.0. It adds 138 tokens to every session and 1,995 once invoked, about $0.0007 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…