career-engine-edit

career-engine-edit is a skill for Claude Code from spinningrachel/career-engine. It costs 102 tokens per session (23,651 once invoked), scanned C, original, MIT.

A workflow for revising job-application materials already stored in a Notion tracker, including CVs, cover letters, coaching details, and reviewer feedback.

In plain words
What is it for?
It is for processing applications marked “Needs editing,” running a career review first, and routing each role through the appropriate revision steps.
Why use it?
It ensures flagged applications are improved from their existing content instead of being treated as new applications or starting from blank documents.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_ROOT} variable. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions subagents.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the career-engine plugin — 29 skills, 16 agents, 1 hook shipped together

Good fit It is for processing applications marked “Needs editing,” running a career review first, and routing each role through the appropriate revision steps.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add spinningrachel/career-engine
Claude Code
/plugin install career-engine

Made for: Claude Code.

Or install career-engine, the plugin that ships this one along with the rest of its 29 skills, 16 agents, 1 hook.

Wrote 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.

agentmods badge for career-engine-edit

README.md
[![agentmods](https://agentmods.dev/badge/skills/spinningrachel/career-engine/career-engine-edit/github.svg)](https://agentmods.dev/skills/spinningrachel/career-engine/career-engine-edit)
Your own site
<a href="https://agentmods.dev/skills/spinningrachel/career-engine/career-engine-edit"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/career-engine-edit/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.

agentmods 80×15 button for career-engine-edit

Your own site · 80×15
<a href="https://agentmods.dev/skills/spinningrachel/career-engine/career-engine-edit"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/career-engine-edit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 23,651 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00102 $0.23651
Opus 5 $0.00051 $0.11825
Sonnet 5 $0.00020 $0.04730
Haiku 4.5 $0.00010 $0.02365

Measured 9d ago against content hash d3aba228bc34, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade C, and why

career-engine-edit scanned grade C with 1 finding 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

For each role fetched in Step E0, extract the structured JD from `$RUN_PIPE/needs-editing-role-properties.md` (read once here, not re-read per step). The `JD Body` property was already captured in Step E0 as part of the
skills/career-engine-edit/SKILL.md · 562 lines

How it starts

The opening of the file, as written. The whole thing — 562 lines — stays where its author put it; the contents beside it link to each section on GitHub.

New Application — Editing Pipeline

Registry: this pipeline is listed in the Pipeline Registry in skills/career-engine/SKILL.md. Actions owned by another pipeline's registry row are out of scope here — route to that pipeline instead of improvising.

This skill handles the editing pipeline for roles the user has flagged as needing revision. It runs separately from the main pipeline and is triggered by Status = Needs editing in the Job Applications database.

The key difference from the main pipeline: agents are not starting from scratch. Existing CV text, cover letter text, coach properties, and reviewer feedback are all in the Notion row. The goal is to improve what exists, informed by what is already documented there.

Needs editing always means edit from the Notion entry. Every role with Status = Needs editing uses whatever is already inside its Notion row as the starting point — existing CV text, cover letter, coach properties, reviewer notes. Nothing is discarded. This rule holds regardless of what state.json says. state.json is crash recovery only (see State file section below).

career-data data root (R-37). The personal-data files — 01-writing-rules.md, 02-professional-background.md, 03-framework.md, linkedin-profile.md, pipeline-preferences.json, delivered-letters/, and the user's .dotx — load from ${CAREER_DATA}/references/, the path the orchestrator resolves in its career-data discovery preflight. Every other file (self-checks, REFERENCES.md, skill docs, default .dotx templates) stays on ${CLAUDE_PLUGIN_ROOT}. If ${CAREER_DATA} is not set (direct or standalone invocation outside the orchestrator), locate the career-data skill yourself, confirm career-data-marker.json, and apply the orchestrator's healthy / damaged / absent outcomes before reading. A configured user's missing career-data is a hard stop — never silently fall back to blank templates.

Universal spawn parameter — gap_handling_mode (2026-07-14). Resolve $GAP_HANDLING_MODE once at run start from ${CAREER_DATA}/references/pipeline-preferences.jsongap_handling (disabled when the value is disabled or empty, enabled otherwise — an absent key on an older config means enabled). Every subagent spawn in this pipeline passes gap_handling_mode=$GAP_HANDLING_MODE, exactly like CAREER_DATA — every agent, every round, every re-spawn and crash-recovery fallback, no exceptions. When disabled, no agent may produce, request, or enforce gap framing anywhere (see the identical rule in career-engine-new-application/SKILL.md for the per-agent meaning). A one-word routing token — for the letter-writer it rides inside its input contract's routing-token allowance, never as content.

Read the full file on GitHub · 562 lines

Changes

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.

  1. 9d ago First seen · 562 lines · 102 tokens per session scan C d3aba228bc34

Subscribe to this mod's changes

career-engine-edit is a skill published in the GitHub repository spinningrachel/career-engine (4 stars, last pushed 28d ago), licensed MIT. It adds 102 tokens to every session and 23,651 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.