A candidate-profile setup command that gathers career information from documents, an imported CV, or an interview and stores it in Markdown files.

Use it to create or update a candidate profile by replacing placeholder fields with real details from documents or answers.

It turns scattered career information into a maintained profile and avoids proposing information that is already recorded when run again.

How suraj-davariya/ai-job-search configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to suraj-davariya/ai-job-search. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/suraj-davariya/ai-job-search/main/.claude/commands/setup.md

Clone the repo

git clone --depth 1 https://github.com/suraj-davariya/ai-job-search

Made for: Claude Code.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/suraj-davariya/ai-job-search/setup/github.svg)](https://agentmods.dev/commands/suraj-davariya/ai-job-search/setup)

Your own site

<a href="https://agentmods.dev/commands/suraj-davariya/ai-job-search/setup"><img src="https://agentmods.dev/badge/commands/suraj-davariya/ai-job-search/setup/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/suraj-davariya/ai-job-search/setup"><img src="https://agentmods.dev/badge/commands/suraj-davariya/ai-job-search/setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 3,556 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. 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.

Model	Per session	Once invoked
Fable 5.1	$0.00017	$0.03556
Opus 5.5	$0.00007	$0.01422
Sonnet 5.5	$0.00003	$0.00711
Haiku 4.5	$0.00002	$0.00356

Measured 2mo ago against content hash 711e934ceb5c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

setup 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 2mo 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.

.claude/commands/setup.md · 299 lines

How it starts

The opening of the file, as written. The whole thing — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/setup — Candidate Profile Onboarding

Spec: docs/requirements/functional-requirements-onboarding.md (REQ-0001–0017) Data model: docs/requirements/data-requirements.md (§1–§9, §13, §17) Merge rules: docs/requirements/business-rules-and-validation.md (§7) Flow: docs/requirements/user-flows.md (§1)

You are running the CareerForge onboarding workflow. Your job is to populate the user's profile files — replacing every [UPPER_SNAKE_CASE] placeholder token with their real data — through one of three convergent paths.

This is a prompt-as-code command (ARCH-0001): there is no compiled program and no settings/profile.json. The profile lives in Markdown files (file-as-DB, ARCH-0004). You read those files, gather the user's data, and write it back.

Hard Invariants (apply to every step, every write)

Read-before-write (REQ-0002). Always read a target file's current contents before proposing changes to it. Existing file state is the idempotency baseline — anything already present is not proposed again.
Idempotency (business-rules §7.3). Re-running /setup with the same inputs produces no new changes. Never re-propose content already present in a file in any form.
No fabrication (ARCH-0007). Never invent a token value. If you don't have data for a token, ask the user or leave the token in place — never guess a name, date, employer, skill, or achievement.
No writes without confirmation (REQ-0009). Present all proposed changes and obtain explicit user approval before writing any file.
Human-in-the-loop (ARCH-0006). The user reviews and approves; you draft and execute. When in doubt, ask.

Target files (the convergence set — REQ-0016):

File	Tokens populated
`.claude/skills/job-application-assistant/01-candidate-profile.md`	Identity, education, experience, projects, skills, publications, awards, references, `[AI_TOOL_NAME]`
`.claude/skills/job-application-assistant/02-behavioral-profile.md`	Overview, drives, behaviors, preferences, growth areas, posting keywords, management style, application usage
`.claude/skills/job-application-assistant/04-job-evaluation.md`	Strong/moderate/weak skills, strong/moderate/entry experience, career goals, energizing/draining tasks
`.claude/skills/job-application-assistant/05-cv-templates.md`	`[PROFILE_STATEMENT_*]` (one per applicable role type)
`.claude/skills/job-application-assistant/07-interview-prep.md`	`[STAR_]` examples and `[STUB_]` Path-A stubs
`CLAUDE.md` (user fork — from `CLAUDE.md.template`)	Union of the above + workflow sections
`.claude/skills/job-scraper/search-queries.md`	Search query + location-tier tokens

Read the full file on GitHub · 299 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.

2mo ago First seen · 299 lines · 17 tokens per session scan A 711e934ceb5c

Subscribe to this mod's changes

setup is a command published in the GitHub repository suraj-davariya/ai-job-search (24 stars, last pushed 4mo ago), licensed MIT. It adds 17 tokens to every session and 3,556 once invoked, about $0.0001 per session on Opus 5.5. 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.

agentic-ai ai-agents ai-job-applications ai-job-apply ai-job-search anthropic

setup next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
setupsuraj-davariya/ai-job-search	Command	24	4mo ago	MIT	A	17	Claude Code
cost-optimizewshobson/agents	Command	42k	yesterday	MIT	A	26	Claude Code
refactor-cleanwshobson/agents	Command	42k	yesterday	MIT	A	26	Claude Code
deps-auditwshobson/agents	Command	42k	yesterday	MIT	A	23	Claude Code
export-closedloop-learningsclosedloop-ai/claude-plugins	Command	123	today	Apache-2.0	A	13	Claude Code
research-verifydrobins25/craft	Command	73	yesterday	MIT	A	28	Claude Code
spreadsheet-auditintellegix/intellegix-code-agent-toolkit	Command	57	4d ago	MIT	A	0	Claude Code

ai-job-search: Command for Claude Code