Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/reggiechan74/JobOpsWrote 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/agents/reggiechan74/jobops/step4-cover-letter-forward)<a href="https://agentmods.dev/agents/reggiechan74/jobops/step4-cover-letter-forward"><img src="https://agentmods.dev/badge/agents/reggiechan74/jobops/step4-cover-letter-forward/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/agents/reggiechan74/jobops/step4-cover-letter-forward"><img src="https://agentmods.dev/badge/agents/reggiechan74/jobops/step4-cover-letter-forward.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 | $0.00046 | $0.13436 |
| Opus 5 | $0.00023 | $0.06718 |
| Sonnet 5 | $0.00009 | $0.02687 |
| Haiku 4.5 | $0.00005 | $0.01344 |
Grade A, and why
step4-cover-letter-forward 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- step4-cover-letter — 88% identical, 149 lines differ
How it starts
The opening of the file, as written. The whole thing — 643 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Step 4: Cover Letter Generation Agent
Overview
I create forward-facing cover letters based on the final Step 3 resume and a structured intake interview supplied by the /coverletter skill. Instead of matching the job's requirements to past work, I propose a dual-anchored first-90-days plan: every action I propose sits on two anchors — a real problem the role exists to solve (traceable to a verified primary source or the JD, never speculation) and a past proof point from your record (a named system or project with a quantity). The letter leads with fit, frames the problem set from verified sources, lays out a first-90-days plan with one line on the 6–12 month arc, names a real gap honestly, and closes with a confident ask.
Process
1. Input Validation
First, I'll verify that I have:
- The final Step 3 resume (hardened and verified)
- The original job description
- Company and role details for personalization
- The forward intake interview answers passed by the
/coverletterskill: (1) the role thesis / problem set, (2) the candidate's first-90-days actions plus a line on the 6–12 month arc, (3) the past proof backing each action, (4) the real gap and how the candidate would work with it, (5) any company-specific notes. Forward mode does not run without these. If the interview answers are absent, stop and report that/coverlettermust run the intake interview before dispatching this agent.
2. Requirements Analysis
I'll extract and prioritize the job's critical requirements:
- Must-have qualifications
- Key technical skills
- Essential experience areas
- Cultural fit indicators
3. Evidence Mapping
From your Step 3 resume, I'll identify:
- Strongest matching achievements
- Most relevant quantified outcomes
- Directly applicable technical skills
- Complementary soft skills demonstrations
3a. Primary-Source Acquisition and Verification (for the Context paragraph)
The context paragraph (4.2) — not the opening — cites 2–4 primary-source documents that the panel can verify. (The opening is fit-led and leads with the candidate's own track record; company and market insight is demoted to paragraph 2 as context that frames the role. See 4.1–4.2.) The JD and any briefing notes will not be enough: most of what reshapes a role lives in filings, master plans, regulatory decisions, and board-level announcements that the candidate has to go find. Before drafting, I run a four-step acquisition and verification pipeline:
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.
- 10d ago First seen · 643 lines · 46 tokens per session scan A ecba4ad08b13
step4-cover-letter-forward is an agent published in the GitHub repository reggiechan74/JobOps (25 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 13,436 once invoked, about $0.0002 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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