Borrowing it
Nothing to install: this file belongs to colophon-group/jobseek. 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/colophon-group/jobseek/main/.claude/commands/jobseek-label-daily.mdgit clone --depth 1 https://github.com/colophon-group/jobseekWrote 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/colophon-group/jobseek/jobseek-label-daily)<a href="https://agentmods.dev/commands/colophon-group/jobseek/jobseek-label-daily"><img src="https://agentmods.dev/badge/commands/colophon-group/jobseek/jobseek-label-daily/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/colophon-group/jobseek/jobseek-label-daily"><img src="https://agentmods.dev/badge/commands/colophon-group/jobseek/jobseek-label-daily.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 | $0.00057 | $0.02749 |
| Opus 5 | $0.00028 | $0.01375 |
| Sonnet 5 | $0.00011 | $0.00550 |
| Haiku 4.5 | $0.00006 | $0.00275 |
Grade C, and why
jobseek-label-daily scanned grade C with 2 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 13d 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.
- Never `rm -rf`. Rejected postings stay on disk (in the same `postings/` Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Never invoke `gh`, `git`, `curl`, `mkdir`, `rm`, `mv`, `cat`, How it starts
The opening of the file, as written. The whole thing — 319 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the orchestrator for the daily labelled-postings routine. Follow
this playbook verbatim. Do not improvise the pipeline, do not read or modify
any subagent system prompts, do not make direct Anthropic API calls. Every
LLM step is an Agent(...) invocation; every deterministic step is a
labeller CLI call via Bash.
Arguments
Parse any arguments passed to the command:
--date YYYY-MM-DD(optional; default: today UTC)--count N(optional; default: 24)
Bind these to RUN_DATE and SAMPLE_SIZE for the rest of the run.
Invariants
-
Read/Write files only under
data/postings-labelled/(relative toapps/crawler). The_runs/{RUN_DATE}/<id>/subtree is where per-posting intermediates live; the final gold record is a single file atpostings/{RUN_DATE}/<id>.jsonwhoselabelling_meta.qa_verdictis the status (acceptedorrejected). -
Never read any file under
.claude/agents/orapps/crawler/src/labeller/prompts/. Subagents load their own prompts. -
Every
Agentinvocation usessubagent_type="jobseek-labeller-<task>"andmodel="sonnet". Thepromptargument is exactly two lines:INPUT: <path-to-rendered-input.md> OUTPUT: <path-to-write-output.json>Paths may contain spaces; the
INPUT:/OUTPUT:prefixes are fixed. -
After every
Agentcall, runlabeller validate ...in Bash. If it fails, retry the subagent up to 2 times by re-rendering the task input with--previous-error "<validator output>"and re-invoking. If still failing after 2 retries, record the failure reason and move to the next posting (the posting will ultimately be merged withqa_verdict=rejected).
Step 0 — working directory
Run everything from apps/crawler:
cd apps/crawler
Step 1 — sample
labeller sample --date $RUN_DATE --count $SAMPLE_SIZE \
--out data/postings-labelled/_runs/$RUN_DATE/sample.json
Read the sample file. It has a postings array with posting IDs. Let IDS
be that list.
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.
- 13d ago First seen · 319 lines · 57 tokens per session scan C f912214f0b59
jobseek-label-daily is a command published in the GitHub repository colophon-group/jobseek (191 stars, last pushed yesterday), licensed MIT. It adds 57 tokens to every session and 2,749 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
setup
Set up your job search profile. Paste your resume or answer a few questions. Takes 5 minutes. Needed before evaluating jobs.
quick-eval
Quick job evaluation. Paste a JD and get a score plus one-paragraph summary. Faster than a full evaluate. Use when someone says 'quick eval', 'quick score', or 'just give me a number'.
resume
Generate a tailored resume and cover letter from a job description, score both, create DOCX files, and update the tracker.
resume-team
Run the role-separated, fail-closed Resume Team workflow against a job description.
writing-coach
Human-voice writing coach — rewrite resumes and cover letters with brevity, burstiness, plain language, and authentic impact. Blocks AI-sounding prose.
cover-letter
Create a one-page cover letter for a job description and generate the final DOCX.