Agent skill

Resume Evidence Workflow

by Elowwwen in Elowwwen/resume-evidence-workflow

Build a reusable career-evidence bank, match it to a job description (JD), select the best installed resume skill, and deliver an application-ready resume.

MITAuto-check passedBusiness, Finance & HR

Install Resume Evidence Workflow

skills CLI
$ npx skills add Elowwwen/resume-evidence-workflow --skill resume-evidence-workflow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Elowwwen/resume-evidence-workflow resume-evidence-workflow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
resume-evidence-workflow
GitHub stars
166
Token cost
~2.4k tokens
SKILL.md length
1,204 words
Files
22 (incl. references, assets)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Build a reusable career-evidence bank, match it to a job description (JD), select the best installed resume skill, and deliver an application-ready resume.

  • Works in 6 steps: inventory existing material; → deep-dive and maintain a portable… → decode the job description (JD) and map… → …
  • Career deep-dives
  • SKILL.md covers Preserve evidence and user…, Stage A: inventory and deep dive, Stage B: decode the job… and Stage C: choose a resume skill, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Resume Evidence Workflow is an agent skill from Elowwwen/resume-evidence-workflow. Build a reusable career-evidence bank, match it to a job description (JD), select the best installed resume skill, and deliver an application-ready resume. Use for career deep-dives, evidence-backed resume tailoring, or choosing among resume skills for a specific market, role, and language. Accept typed, dictated, transcribed, and audio-derived narratives. Do not use merely to format a finished resume or answer one isolated interview question.

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 24 other files, including reference files and assets (for example `README.md`, `agents/openai.yaml` and `references/application-ready-resume.md`).

It sits in Business, Finance & HR, covering Resume and CV writing, Recruiting and HR and Interview preparation. The repository describes itself as: 一套以经历为基础的 AI 简历工作流,用于经历深挖、JD 匹配、简历改写,并覆盖可辅助面试的经历过程。 The licence is MIT.

When your agent uses it

  • Career deep-dives
  • Evidence-backed resume tailoring
  • Choosing among resume skills for a specific market

Example prompts

  • “/resume-evidence-workflow”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. inventory existing material;
  2. deep-dive and maintain a portable Markdown evidence bank plus reusable base-resume files;
  3. decode the job description (JD) and map requirements to evidence;
  4. select the best available resume skill;
  5. rewrite, verify, and deliver an application-ready resume;
  6. write newly confirmed or corrected facts back to the evidence bank.

What it can do on your machine

Read from SKILL.md and the folder at commit c06d98d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Resume Evidence Workflow loads about 2.4k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 118 tokens; SKILL.md has 1,204 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~118
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~16k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Elowwwen/resume-evidence-workflow at commit c06d98d, republished under its MIT licence (© Elowwwen). 1,204 words, ~2,423 tokens.

Download SKILL.mdSave it as .claude/skills/resume-evidence-workflow/SKILL.md (or your agent's skills folder). This skill also uses 21 other files; get the full folder from GitHub.
name
resume-evidence-workflow
description
Build a reusable career-evidence bank, match it to a job description (JD), select the best installed resume skill, and deliver an application-ready resume. Use for career deep-dives, evidence-backed resume tailoring, or choosing among resume skills for a specific market, role, and language. Accept typed, dictated, transcribed, and audio-derived narratives. Do not use merely to format a finished resume or answer one isolated interview question.

Resume Evidence Workflow

Run only the stage the user currently needs. Resume from existing files instead of restarting completed work. The full path is:

  1. inventory existing material;
  2. deep-dive and maintain a portable Markdown evidence bank plus reusable base-resume files;
  3. decode the job description (JD) and map requirements to evidence;
  4. select the best available resume skill;
  5. rewrite, verify, and deliver an application-ready resume;
  6. write newly confirmed or corrected facts back to the evidence bank.

When no job description (JD) is available, complete the evidence stage and preserve it for later tailoring. Do not imply that the complete product ends there.

Preserve evidence and user decisions

The evidence bank preserves what the user supplied and confirmed. The application resume may use a presentation choice explicitly requested by the user without rewriting the underlying evidence record.

Do not proactively add information that the user neither supplied nor requested. When the user explicitly asks for a different presentation of dates, titles, responsibilities, results, metrics, or other content, treat that request as the user's decision and pass it through to the selected resume skill. If a choice has a material downstream explanation risk, mention that risk once and continue without moralizing or requiring another confirmation. Read evidence and user agency when the evidence record and resume presentation differ.

Never place a real user's identifying facts in public documentation, demonstrations, screenshots, tests, or case libraries. Use wholly fictional identities, organizations, dates, metrics, and stories.

Stage A: inventory and deep dive

Inspect supplied resumes, profiles, portfolios, notes, transcripts, and existing evidence files before asking questions. Accept document-led and narrative-led entry. If speech or transcription is involved, read voice-input.md.

When a resume is supplied for the first time, read resume-workspace.md and offer to preserve a reusable 基础简历.md and 简历版式档案.md beside the evidence bank. After these files exist, treat them as the default resume source for later job-description (JD) tailoring. Do not ask the user to upload or reparse the same PDF for every job description (JD). Re-import only when the user says the source resume changed, requests a different design, or the saved files are missing or materially incomplete.

At the start of an experience, give a non-binding estimate of the likely core questions and name the main directions. Let one complete answer resolve several themes. Use clear natural language rather than resume or interview jargon; preserve professional terms the user already uses accurately.

Use three passes:

  1. Recall: establish what the work was, why it began, what the user personally did, and what followed.
  2. Lateral scan: read career-value-radar.md and select only plausible hidden branches such as monetization, governance, partnerships, systems, user insight, or reuse.
  3. Selective deepening: read question-and-stop-rules.md. Continue only when an answer may reveal distinct value, clarify the evidence record, or change later resume selection.

After a substantial answer, briefly show only the neutral information that would be added or changed in the evidence bank, using slightly professional but not fully optimized resume language. This lets the user correct the record without rereading the file. Stop when added detail would be repetitive, trivial, unrecoverable, or unlikely to affect future use.

When creating or changing the bank, read evidence-schema.md. For substantial multi-project work, also read project-logic-and-interview-evidence.md. Use behavioral-question-coverage.md only as a lightweight event-discovery lens when process evidence is likely; do not turn this workflow into interview preparation.

Stage B: decode the job description (JD)

Keep the job description (JD) visible through the rewrite. Extract its business objective, must-haves, preferred signals, role family, seniority, market, language, ATS terms, and likely evidence standard.

Before requesting a resume, look for the reusable files defined in resume-workspace.md. Use 基础简历.md for current selection and wording, 简历版式档案.md for layout, and the evidence bank for deeper or newly relevant facts. A PDF is a calibration source, not a recurring prerequisite.

Before rewriting, show a requirement-to-evidence matrix distinguishing direct, adjacent, weak, and absent evidence. Explain intended emphasis, compression, movement, and gaps. Do not rewrite first and rationalize the match afterward.

Stage C: choose a resume skill

Read jd-and-skill-routing.md. Use installed skill descriptions to shortlist plausible candidates, then read only the complete SKILL.md files of the best two or three. Select one primary content-rewrite skill and, only if needed, one separate artifact/rendering skill.

If no suitable skill is installed, offer either a conservative direct rewrite using application-ready-resume.md, or a read-only search for up to three relevant public skills. Do not install or execute third-party code without the user's choice and required permission.

Show full SKILL.md (460 more words)Show less

Stage D: rewrite and deliver

Before deleting or materially merging an experience, project, overview, bullet, education item, or user-supplied section, show the proposal and obtain approval. Lack of job-description relevance is a reason to recommend removal, not authorization to remove it.

Before drafting, ask whether the user wants self-positioning/professional summary, self-evaluation, or an intended position, and whether the resume is dedicated to one job description (JD) or reused across roles.

Read resume-section-structure.md before arranging sections. Determine sections from the candidate's actual career stage and relationship types. Formal employment, internships, and non-employment experience must remain distinguishable; section names may adapt to the job description (JD) without obscuring or upgrading the relationship type.

Give the selected skill the job description (JD), matching matrix, relevant evidence, required retained content, and the user's explicit presentation instructions. Let that skill determine the writing method. Then read application-ready-resume.md for workflow and artifact validation. If HTML is selected, additionally read editable-html-output.md and use assets/editable-resume-base.html. A static HTML page is not an acceptable substitute for the editable artifact. Include the template’s description-only copy panel for application forms: one experience body per block, excluding employer, role, dates and other metadata; see the HTML reference for markup and validation.

Before drafting repeated experience angles from scratch, read reusable resume content. Reuse a verified expression only when its evidence boundary and target angle still fit the current job description (JD); tailor it rather than copying mechanically.

If the reusable workspace already contains 基础简历.html, copy that master and patch only the content blocks and approved section changes. Do not rewrite its HTML shell, CSS, toolbar, or print script for each job description (JD). Use the generic asset only when no compatible master exists.

Stage E: update memory

During job-description matching and rewriting, promptly record genuinely new evidence, corrections, newer metric snapshots, later project developments, or changed status. Check for an existing equivalent record first. Tell the user concisely what neutral fact will be added or changed so they can stop, merge, or correct the update.

Do not automatically overwrite 基础简历.md with every tailored version. Update it only when the user adopts a change as a new general default. Updating evidence does not automatically change the base resume; updating the base resume does not replace more precise evidence.

After the user accepts the final resume, make at most one incremental reuse-library update pass. Tell the user which reusable module was added, changed, or left unchanged. Do not spend a separate generation pass when nothing materially reusable changed. Read reusable resume content for duplicate, replacement, and notification boundaries.

Do not route into mock interviews or generate interview packages as part of this workflow. The evidence bank can nevertheless preserve compact examples of decisions, collaboration, difficulty, and retrospective learning that the user may reuse elsewhere.

© Elowwwen, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 21 other files (references, assets) in the repository root of Elowwwen/resume-evidence-workflow.

  • SKILL.md
  • LICENSE
  • README.md
  • agents/openai.yaml
  • assets/editable-resume-base.html
  • assets/support-alipay.jpg
  • assets/support-wechat.jpg
  • references/application-ready-resume.md
  • references/behavioral-question-coverage.md
  • references/career-value-radar.md
  • references/editable-html-output.md
  • references/evidence-and-agency.md
  • references/evidence-schema.md
  • references/jd-and-skill-routing.md
  • references/project-logic-and-interview-evidence.md
  • references/question-and-stop-rules.md
  • references/resume-section-structure.md
  • references/resume-workspace.md
  • … and 4 more

Open the folder on GitHubat commit c06d98d

Compare with similar skills

Resume Evidence Workflow next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Resume Evidence Workflow compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Resume Evidence Workflow this skillElowwwen/resume-evidence-workflow166—~2.4kAutomated safety check: PassMIT
Offer Negotiationreactive-resume/reactive-resume44k—~10kAutomated safety check: PassMIT
LLM Intern Skillwanyichen06/LLMInternSkill326—~1.2kAutomated safety check: PassMIT
Resume Tailorreactive-resume/reactive-resume44k—~8.3kAutomated safety check: PassMIT
Offer Toolkit Skillyanliudesign/offer-toolkit-skill520—~1.2kAutomated safety check: PassMIT
Resume Critiquelow-hands/MyCareer108—~872Automated safety check: PassMIT

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Questions about Resume Evidence Workflow

What does Resume Evidence Workflow do?

Build a reusable career-evidence bank, match it to a job description (JD), select the best installed resume skill, and deliver an application-ready resume. Resume Evidence Workflow is an agent skill from Elowwwen/resume-evidence-workflow. Build a reusable career-evidence bank, match it to a job description (JD), select the best installed resume skill, and deliver an application-ready resume.

When should I use Resume Evidence Workflow?

Resume Evidence Workflow fits situations like: career deep-dives; evidence-backed resume tailoring; choosing among resume skills for a specific market.

How do I install Resume Evidence Workflow in Claude Code?

Run `npx skills add Elowwwen/resume-evidence-workflow --skill resume-evidence-workflow -a claude-code`. Or copy the skill folder (the Elowwwen/resume-evidence-workflow repository) into .claude/skills/resume-evidence-workflow in your project. Claude Code loads it when a task matches its description.

How do I install Resume Evidence Workflow in Codex?

Run `npx skills add Elowwwen/resume-evidence-workflow --skill resume-evidence-workflow -a codex`. Or copy the skill folder (the Elowwwen/resume-evidence-workflow repository) into .agents/skills/resume-evidence-workflow in your project. Codex loads it when a task matches its description.

Can I use Resume Evidence Workflow in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Elowwwen/resume-evidence-workflow --skill resume-evidence-workflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/resume-evidence-workflow, .gemini/skills/resume-evidence-workflow, .github/skills/resume-evidence-workflow and .opencode/skills/resume-evidence-workflow in your project.

What does Resume Evidence Workflow need to run?

SKILL.md names no scripts, command-line tools or credentials: Resume Evidence Workflow is instructions for the agent only.

Does Resume Evidence Workflow access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Resume Evidence Workflow safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Resume Evidence Workflow use?

Resume Evidence Workflow is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Resume Evidence Workflow use?

About 2.4k tokens (SKILL.md is roughly 9.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 14k tokens, read only when the agent opens those files.

What are the alternatives to Resume Evidence Workflow?

Skills that share tags, products or a category with Resume Evidence Workflow: Offer Negotiation (reactive-resume/reactive-resume, 44k stars), LLM Intern Skill (wanyichen06/LLMInternSkill, 326 stars), Resume Tailor (reactive-resume/reactive-resume, 44k stars) and Offer Toolkit Skill (yanliudesign/offer-toolkit-skill, 520 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Resume Evidence Workflow?

Elowwwen (a GitHub user) maintains it in Elowwwen/resume-evidence-workflow, which has 166 GitHub stars. The repository was last updated on September 29, 2026.

Source: Elowwwen/resume-evidence-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.