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 skills/rezenders/scientific_writing_agent/bootstrap-memorynpx skills add Rezenders/scientific_writing_agent --skill bootstrap-memorygit clone --depth 1 https://github.com/Rezenders/scientific_writing_agentWrote 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/skills/rezenders/scientific_writing_agent/bootstrap-memory)<a href="https://agentmods.dev/skills/rezenders/scientific_writing_agent/bootstrap-memory"><img src="https://agentmods.dev/badge/skills/rezenders/scientific_writing_agent/bootstrap-memory.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 | $0.00061 | $0.01100 |
| Opus 5 | $0.00030 | $0.00550 |
| Sonnet 5 | $0.00012 | $0.00220 |
| Haiku 4.5 | $0.00006 | $0.00110 |
Grade A, and why
bootstrap-memory 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 5d 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bootstrap Memory
Scans CLAUDE.md and the manuscript to extract project-specific knowledge and writes it into all four agent memory directories. Run this once after /setup-paper-project, or any time you want to refresh agent knowledge after major revisions.
When to Use
- After running
/setup-paper-projecton a new manuscript - After a major rewrite that changed terminology, contributions, or section structure
- When agents are giving inconsistent or generic responses that suggest they lack project context
Not For
- Ongoing memory updates during normal editing — agents do this themselves as they work
- Fixing stale or incorrect memories — edit the specific memory file directly
Inputs Required
Tell Claude:
- Memory root (default:
.claude/agent-memory/) - Manuscript root (default:
sections/— or wherever your.texsection files live) - Scope (optional):
full(all four agents) or a specific agent name
Workflow
Phase 1 — Extract from CLAUDE.md
Read CLAUDE.md (and AGENTS.md if present) and extract:
- All canonical macros and their rendered forms
- Terminology distinctions and rules (e.g. "never use X where Y is established")
- Style rules and prohibited patterns (e.g. no em-dashes, no semicolons)
- Annotation macro definitions
- Section structure: file names and their roles
- Build commands
- Implementation reference paths (if present)
Phase 2 — Extract from Manuscript
Read the introduction section and extract:
- Contribution claims (bullet points or numbered list)
- Key defined terms with their first-use definitions
- The paper's central argument in one or two sentences
Scan all section files and extract:
- Acronym definitions — patterns like "X (ABC)" or "\acr{}" on first mention
- Key notation from math environments
- Repeated terminology patterns
Phase 3 — Write Agent Memory Files
Before writing each file, check whether it already exists. If it does, update rather than overwrite — preserve any content that is more specific or detailed than what was just extracted.
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.
- 5d ago First seen · 136 lines · 61 tokens per session scan A f3ff87c6727e
bootstrap-memory is a skill published in the GitHub repository Rezenders/scientific_writing_agent (11 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 1,100 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 2026-08-30.
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