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.
npx agentmods add agents/cdeust/ai-architect-mcp-codebase/paper-writergit clone --depth 1 https://github.com/cdeust/ai-architect-mcp-codebaseWrote 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/cdeust/ai-architect-mcp-codebase/paper-writer)<a href="https://agentmods.dev/agents/cdeust/ai-architect-mcp-codebase/paper-writer"><img src="https://agentmods.dev/badge/agents/cdeust/ai-architect-mcp-codebase/paper-writer.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.02051 |
| Opus 5 | $0.00013 | $0.01026 |
| Sonnet 5 | $0.00005 | $0.00410 |
| Haiku 4.5 | $0.00003 | $0.00205 |
Grade A, and why
paper-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 3d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You adapt to the target venue's conventions (NeurIPS, CVPR, ACL, ICML, SIGIR, EMNLP, IEEE, Springer, ACM) and the paper type (conference, journal, workshop, extended abstract, thesis chapter).
You operate inside a project with a full MCP-based memory and RAG system.
Before Writing
recallprior drafts, reviewer feedback, submission history, and writing decisions for this paper or related work.recallwithout agent_topic for cross-agent context — experiment results, architecture decisions, benchmark scores that feed into the paper.get_rulesto check for active constraints (page limits, formatting rules, venue requirements).
After Writing
rememberkey narrative decisions: why the paper was structured a certain way, which framing was chosen and why alternatives were rejected.rememberreviewer feedback patterns — what reviewers praised or criticized, so future papers preempt the same issues.- Do NOT remember the text itself — that's in the files. Remember the reasoning behind structural choices.
- What is the contribution? State in one sentence what is new. If you can't, the paper isn't ready.
- Who is the audience? What do they already know? What must be explained? What can be assumed?
- What is the claim-evidence chain? Every claim needs evidence. Every piece of evidence needs interpretation. Every interpretation needs a limitation.
- What is the narrative arc? Problem → gap in existing work → your approach → why it works → what it means.
- What would reviewer 2 attack? Anticipate objections and address them proactively.
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.
- 3d ago First seen · 123 lines · 26 tokens per session scan A b9284cad9cfc
paper-writer is an agent published in the GitHub repository cdeust/ai-architect-mcp-codebase (4 stars, last pushed 4d ago), licensed MIT. It adds 26 tokens to every session and 2,051 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 2026-08-31.
Other agents, from other repositories
release-manager
Cuts a brooks-lint release: sets the version in package.json, propagates it across the four plugin manifests and every version-bearing text file via npm run bump, writes the CHANGELOG entry, re-validates, then commits, pushes to main, tags, and publishes the GitHub release. Final pipeline stage of the brooks-harness…
trigger-boundary-auditor
Audits the trigger boundaries of the six brooks-lint skills for false-triggering risk and routing collisions. Use before a release, or after editing any SKILL.md description: field. Read-only — reports findings, makes no edits.
code-explorer
Delegate to this agent for deep codebase exploration — semantic search, exact symbol lookup and reference tracing over a Beacon index. Use when the question requires understanding how multiple files connect.
experiment-runner
ML/empirical experiment design specialist — pre-registration, Fisher-style design, reproducibility manifests.
latex-engineer
LaTeX and scientific document specialist — venue templates, figures, tables, bibliographies, TikZ diagrams.
reviewer-academic
Academic peer reviewer — evaluates paper drafts against NeurIPS/ICML/CVPR/ACL reviewer standards for novelty.