career-ops
Skill0 starsChanged 3 months agoMITView on GitHub
Use when the user wants help running a job hunt end to end: scanning public job boards, scoring role fit, tailoring a CV or cover letter, and tracking applications in a local tracker. The agent never submits applications.
15 other projects use a version of this.
Adopted by
Most recently taken up by
- career-ops-hq/career-opstheir own version, first seen Nov 6, 2026
- shuheng-mo/career-ops-chinatheir own version, first seen Oct 27, 2026
- limuchuan0619/ai-job-search-chinatheir own version, first seen Oct 20, 2026
- Shri-Phnx/claude-skillstheir own version, first seen Oct 13, 2026
- santifer/career-opstheir own version, first seen Oct 8, 2026
- okashiina/career-ops-idtheir own version, first seen Sep 28, 2026
Other versions15 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 15
- santifer/career-ops★ 81ksame name
- career-ops-hq/career-ops★ 81ksame name
- shuheng-mo/career-ops-china★ 113same name
- karthikrshet/Career-Agents★ 67same name
- Youssifai/internship-finder★ 9same name
- poferraz/career-ops★ 7same name
- Shri-Phnx/claude-skills★ 2same name
- skytiger6724/qwen-skills★ 2same name
- jpoindexter/theft-kit★ 1same name
- limuchuan0619/ai-job-search-china★ 1same name
5 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository110 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/project-bootstrap/templates/agents.mdAGENTS.md
- a11y-auditSkill
- agentic-ragSkill
- agent-reachSkill
- ai3d-genSkill
- ai-coding-dictionarySkill
- ai-toolsSkill
- animation-directionSkill
- api-specSkill
- architecture-diagramsSkill
- architectureSkill
- ascii-artSkill
- ask-bundleSkill
- binary-triageSkill
- bragSkill
- brag-slimSkill
- code-reviewSkill
- computer-useSkill
- context7Skill
- context-hygieneSkill
- creative-engineeringSkill
- cu-realtimeSkill
- data-analystSkill
- databaseSkill
- dead-wireSkill
- debuggingSkill
- deploySkill
- devin-configSkill
- dispatching-parallel-agentsSkill
- dmaSkill
- dockerSkill
- drift-reportSkill
- e2e-testingSkill
- edge-casesSkill
- executionSkill
- fact-checkSkill
- finishing-a-development-branchSkill
- firmware-probeSkill
- frontend-designSkill
- gatesSkill
- ghidraSkill
- ghSkill
- github-actionsSkill
- git-workflowsSkill
- grillingSkill
- handoffSkill
- humanizerSkill
- hyperframesSkill
- i18nSkill
- image-forensicsSkill
- impeccableSkill
- implement-layaSkill
- intakeSkill
- jiraSkill
- knowledge-modelingSkill
- laya-orchestratorSkill
- learn-modeSkill
- mcp-governanceSkill
- media-toolsSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 14 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 58
Read the user's base CV (ask for its path if unknown).
- Very specific: line 66
Write drafts to .devin/scratch/career-ops/<company>-<role-slug>/.
- Distinctive: line 81
Update the tracker on every scan, draft, or user-reported status change.
“Common” is measured: kept by at least 6 in 10 of the 14 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Career Ops
Slim port of the career-ops workflow modes.
Source: MIT, https://github.com/career-ops-hq/career-ops (aka santifer/career-ops)
Out of scope by design: no Go dashboard, no Playwright PDF generation, no credentialed scraping, no browser automation of application forms.
HARD RULE
The agent NEVER submits applications. No clicks on Apply, no form fills on behalf of the user, no uploads to an ATS. The agent finds, scores, drafts, and tracks; the user presses submit. If a listing requires login or captcha to view, skip it and note it in the tracker as inaccessible.
Mode 1: Pipeline scan
Find candidate roles on public boards only:
- Greenhouse public boards:
boards.greenhouse.io/<company> - Ashby:
jobs.ashbyhq.com/<company> - Lever:
jobs.lever.co/<company>
Fetch listing pages with webfetch or the scrape-tools extension.
Public endpoints only; never authenticate, never scrape behind a login.
For each target company or role query the user provides, collect: title, company, location, remote policy, posted date, apply URL, and the job description text.
Mode 2: Score fit
Score each role 1-5 per axis against the user's stated profile. Ask the user for their profile once per session if not known (target stack, seniority, minimum comp, location constraints).
| Axis | What to check |
| Stack match | Overlap between required skills and the user's stack |
| Seniority | Level and years vs the user's experience |
| Comp | Listed range vs the user's floor; unknown comp scores 3 |
| Location | Remote/onsite/hybrid vs the user's constraints |
Total out of 20. Present ranked results as a table with the apply URL. Recommend applying to anything >= 14 unless the user says otherwise.
Mode 3: Tailor CV and cover letter
For a role the user picks:
- Read the user's base CV (ask for its path if unknown).
- Map the job description's required/preferred skills to the CV.
- Produce a tailored CV draft: reorder and rephrase real experience to surface the matching work. Never invent employers, titles, dates, or metrics.
- Produce a cover letter draft: 3 short paragraphs, specific to the company and role, using the project's actual language where apt.
Write drafts to .devin/scratch/career-ops/<company>-<role-slug>/.
The user reviews and edits; the agent does not submit.
Mode 4: Track applications
Maintain .devin/scratch/career-ops/tracker.md as a Markdown table:
| Date | Company | Role | Fit | Status | Applied URL | Notes |
Status vocabulary: found, scored, drafted, submitted, interview,
offer, rejected, withdrawn. The agent sets rows up to drafted;
submitted and later statuses are only recorded after the user confirms
they applied.
Update the tracker on every scan, draft, or user-reported status change.
Workflow
Scan public boards
-> Score each role (stack, seniority, comp, location)
-> Present ranked table; user picks roles
-> Tailor CV + cover letter drafts per role
-> Update tracker (status: drafted)
-> User applies manually, reports back
-> Update tracker statusDoes it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

