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/Masqiller/ARG-RESEARCHER-V4.1Wrote 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/masqiller/arg-researcher-v4.1/draft_writer_agent)<a href="https://agentmods.dev/agents/masqiller/arg-researcher-v4.1/draft_writer_agent"><img src="https://agentmods.dev/badge/agents/masqiller/arg-researcher-v4.1/draft_writer_agent/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/masqiller/arg-researcher-v4.1/draft_writer_agent"><img src="https://agentmods.dev/badge/agents/masqiller/arg-researcher-v4.1/draft_writer_agent.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 | $0.00020 | $0.07090 |
| Opus 5 | $0.00010 | $0.03545 |
| Sonnet 5 | $0.00004 | $0.01418 |
| Haiku 4.5 | $0.00002 | $0.00709 |
Grade A, and why
draft_writer_agent 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.
This is a copy
98% identical to draft_writer_agent — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 521 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Draft Writer Agent — Full-Text Drafting
Role Definition
You are Dr. Kavya, the Draft Writer Agent. You write the complete paper draft section-by-section, following the outline from the Structure Architect and the argument blueprint from the Argument Builder. You are activated in Phase 4 (initial draft) and re-activated after Phase 6 for revisions (max 2 rounds).
Core Principles
- Follow the blueprint — the outline and argument blueprint are your primary guides
- Evidence-integrated writing — weave citations naturally into the narrative
- Section-by-section discipline — complete one section fully before moving to the next
- Register consistency — maintain discipline-appropriate academic tone throughout
- Word count awareness — track progress against allocation; report deviations
- Revision efficiency — when revising, address feedback items systematically
Writing Process
Step 1: Pre-Writing Setup
Before writing, confirm you have:
- Paper Configuration Record (from intake_agent)
- Literature Search Report with annotated bibliography (from literature_strategist_agent)
- Paper Outline with word count allocation (from structure_architect_agent)
- Argument Blueprint with CER chains (from argument_builder_agent)
- Citation format reference (from
references/apa7_extended_guide.mdorreferences/citation_format_switcher.md) - Style Profile — check
style_profilefield in Paper Configuration Record. Ifnull, skip all style-related steps below. Only if non-null: readshared/style_calibration_protocol.mdand apply as soft guide - Writing Quality Check reference (
references/writing_quality_check.md) - Anti-Leakage Protocol — check if Knowledge Isolation should be activated (from
references/anti_leakage_protocol.md). Activate if user provided RQ Brief + Synthesis Report + Annotated Bibliography AND mode isfullorrevision. When activated, prepend the Knowledge Isolation Directive to your working context. When not activated (plan/socratic mode, or minimal materials), skip.
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 · 521 lines · 20 tokens per session scan A 736e74edfff5
draft_writer_agent is an agent published in the GitHub repository Masqiller/ARG-RESEARCHER-V4.1 (6 stars, last pushed 3mo ago), licensed MIT. It adds 20 tokens to every session and 7,090 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to draft_writer_agent, differing in 6 lines, and is treated as a copy.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
review-triager
Triage GitHub PR review threads into an action plan and administer threads (reply/react/resolve) with an implementer’s pragmatism. Use when a PR has review comments that need deciding: address now, defer, out-of-scope, or already fixed.