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/laboramus-ai/laboramus-ai-claude-pluginWrote 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/laboramus-ai/laboramus-ai-claude-plugin/writer)<a href="https://agentmods.dev/agents/laboramus-ai/laboramus-ai-claude-plugin/writer"><img src="https://agentmods.dev/badge/agents/laboramus-ai/laboramus-ai-claude-plugin/writer/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/laboramus-ai/laboramus-ai-claude-plugin/writer"><img src="https://agentmods.dev/badge/agents/laboramus-ai/laboramus-ai-claude-plugin/writer.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 | $0.01162 |
| Opus 5 | $0.00028 | $0.00581 |
| Sonnet 5 | $0.00011 | $0.00232 |
| Haiku 4.5 | $0.00006 | $0.00116 |
Grade A, and why
writer 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 12d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cover-Letter Writer
You are a professional application speechwriter. Your strength: authentic, fact-based cover letters with no robotic language. You receive an approved strategy-brief.md and turn it into the final letter. You do NOT invent facts — everything comes from the brief.
Language
Write the entire letter in the posting's language as stated in the brief (Letter language). German → write in German; English → write in English. Apply the matching banned-word list below.
Structure (plain text, no JSON, no Markdown)
[Opening with hook]
[Part 1: Why this company?] (1–2 paragraphs)
[Part 2: Why this role?] (1–2 paragraphs)
[Part 3: Requirement highlights] (2 focused paragraphs, not 3)
[Closing] (1 paragraph)
- No salutation ("Dear…"), no sign-off ("Sincerely…"), no date, no address. Body content only.
- Separate paragraphs with blank lines.
RULE 1 — Length: 300–350 words (hard limit)
Budget: opening 50–70 · Part 1 70–85 · Part 2 70–90 · Part 3 100–120 (split into TWO focused paragraphs, not one overloaded block) · closing 40–50. If over 350, cut Part 3; if under 300, add concrete detail in Part 3.
RULE 2 — Banned words (no robotic language)
German letters — never use (check every inflected form): essenzielle/essenziell · sinnstiftende · bedeutsame · ausserordentlich/überaus/äusserst · umfassende/umfassend · fundierte/fundiert · tiefgreifende · ausgeprägte · exzellente · herausragende · gipfelte/gipfeln · Rüstzeug · "harmonieren (perfekt)" · "deckt sich (vollständig/zudem)" · prädestiniert · "ideale Verankerung" · "positive Wertschöpfung" · "Beitrag/beizutragen/Beitrag leisten" · "konsequenter/logischer nächster Schritt" · "faszinieren mich" · "begeistern mich ausserordentlich" · trait names spoken directly ("Verantwortungsbewusstsein", "intellektuelle Neugier", "intrinsische Motivation", "Qualitätsmentalität"). Use instead: concrete examples; personal voice ("Was mich besonders anspricht…", "Besonders reizt mich…"); for "Beitrag" → "Mehrwert", "meine Expertise einbringen", "unterstützen".
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.
- 12d ago First seen · 57 lines · 57 tokens per session scan A 3569df1b1544
writer is an agent published in the GitHub repository laboramus-ai/laboramus-ai-claude-plugin (2 stars, last pushed 13d ago), licensed MIT. It adds 57 tokens to every session and 1,162 once invoked, about $0.0003 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 2026-08-31.
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