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.
curl -O https://raw.githubusercontent.com/suraj-davariya/ai-job-search/main/.claude/commands/apply.mdgit clone --depth 1 https://github.com/suraj-davariya/ai-job-searchWrote 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/commands/suraj-davariya/ai-job-search/apply)<a href="https://agentmods.dev/commands/suraj-davariya/ai-job-search/apply"><img src="https://agentmods.dev/badge/commands/suraj-davariya/ai-job-search/apply/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/commands/suraj-davariya/ai-job-search/apply"><img src="https://agentmods.dev/badge/commands/suraj-davariya/ai-job-search/apply.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 | $0.00021 | $0.05111 |
| Opus 5 | $0.00010 | $0.02556 |
| Sonnet 5 | $0.00004 | $0.01022 |
| Haiku 4.5 | $0.00002 | $0.00511 |
Grade A, and why
apply 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 11d 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 — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/apply — Job Application Pipeline
Spec:
docs/requirements/functional-requirements-application.md(REQ-2001–2062) Rules:docs/requirements/business-rules-and-validation.md(§2 page budget, §3 cover letter, §4 writing quality, §5 verification, §6 dedup, §9 status enum) Flow:docs/requirements/user-flows.md(§3)
You are running the CareerForge application pipeline: take a job posting and produce a tailored CV and cover letter, compiled to PDF and verified. This is a prompt-as-code command (ARCH-0001) operating on the file-as-DB profile (ARCH-0004).
Pipeline: Steps 0 → 1 → 2 → 3 → 4 → 5 → 6. The reviewer critique (Step 3) and
revision (Step 4) run when --review=full (default) or --review=quick, and are
skipped when --review=none.
Hard Invariants (apply at every step)
- No fabrication (ARCH-0007). Every claim in the CV and cover letter must be verifiable against the candidate profile. Never invent skills, experience, achievements, dates, or company facts.
- Read-before-write. Read the profile and template files before drafting;
read a
.texfile before editing it. - Writing style always applies (business-rules §4). No em-dashes, clichés, buzzwords-without-backing, or apologetic language; first person, active voice.
- Human-in-the-loop (ARCH-0006). Stop at the approval gate (Step 1) before drafting. Flag stretch claims for the user (REQ-2023).
- Token efficiency (REQ-2024). Keep files and draft text in working memory; do not re-read files already in context from an earlier step.
- Provider resilience (NFR-0022, ARCH-0005). If the AI provider rate-limits or fails, stop gracefully with a clear message; do not retry-spam or run high-volume headless batches that can trip provider abuse heuristics.
Profile + template files this command consumes:
| File | Used in |
|---|---|
.claude/skills/job-application-assistant/01-candidate-profile.md |
Steps 1, 2 (source of all claims) |
.claude/skills/job-application-assistant/02-behavioral-profile.md |
Step 1 (behavioral fit), Step 2 (cover-letter voice) |
.claude/skills/job-application-assistant/03-writing-style.md |
Step 2 (always) |
.claude/skills/job-application-assistant/04-job-evaluation.md |
Step 1 (scoring framework) |
.claude/skills/job-application-assistant/05-cv-templates.md |
Step 2/5 (CV LaTeX guide + cutting) |
.claude/skills/job-application-assistant/06-cover-letter-templates.md |
Step 2/5 (cover-letter LaTeX guide) |
.claude/skills/job-application-assistant/08-legitimacy.md |
Step 1 (posting legitimacy gate) |
locale-packs/<code>.json |
Steps 0–2 (target-market conventions; default locale-packs/default.json) |
trust-safety/scam-patterns.json |
Step 1 (red-flag catalog) |
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.
- 11d ago First seen · 385 lines · 21 tokens per session scan A c3d737cadce1
apply is a command published in the GitHub repository suraj-davariya/ai-job-search (22 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 5,111 once invoked, about $0.0001 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 2026-08-30.
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