OPC Skills is a collection of reusable instruction folders, scripts, and resources that extend coding agents with specialized tasks for solopreneurs and one-person companies. Its skills cover areas such as search optimization, demand research, domain discovery, branding, social-media assets, and platform-specific research. The catalogue entries are the project's own skills, plugins, and hook.
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 skills add ReScienceLab/opc-skills --skill archivegit clone --depth 1 https://github.com/ReScienceLab/opc-skillsWrote 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/resciencelab/opc-skills/archive)<a href="https://agentmods.dev/skills/resciencelab/opc-skills/archive"><img src="https://agentmods.dev/badge/skills/resciencelab/opc-skills/archive/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/skills/resciencelab/opc-skills/archive"><img src="https://agentmods.dev/badge/skills/resciencelab/opc-skills/archive.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00065 | $0.00498 |
| Opus 5.5 | $0.00026 | $0.00199 |
| Sonnet 5.5 | $0.00013 | $0.00100 |
| Haiku 4.5 | $0.00006 | $0.00050 |
Grade A, and why
archive 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 1mo 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:
- archive — 100% identical, 0 lines differ
What it actually says
Archive Skill
Capture, index, and reuse project knowledge across sessions.
When to Archive
- After completing a significant task (deploy, migration, major feature)
- After resolving a tricky debugging session
- When the user says "archive this"
- After any multi-step process with learnings worth preserving
When to Consult Archives
- Before debugging infrastructure, deploy, or CI issues
- Before repeating a process done in a past session
- When encountering an error that may have been solved before
Search: grep -ri "keyword" .archive/
Index: .archive/MEMORY.md
Archive Workflow
- Read
.archive/MEMORY.md— check for related existing archives - Create
.archive/YYYY-MM-DD/directory if needed - Write markdown file with YAML frontmatter (see
references/TEMPLATE.md) - Update
.archive/MEMORY.md: add one-line entry under the right category - If related archives exist, add
relatedfield in frontmatter
Lookup Workflow
- Read
.archive/MEMORY.mdto find relevant entries - Read the specific archive file for detailed context
- Apply learnings to current task
Categories
- infrastructure — AWS, ECS, IAM, networking, secrets, CloudWatch
- release — TestFlight, versioning, Git Flow, CHANGELOG
- debugging — Bug fixes, error resolution, gotchas
- feature — Feature design, implementation notes
- design — UI/UX, icons, visual design
Rules
.archive/must be in.gitignore— local-only notes- Keep entries concise but reproducible
- Focus on problems, fixes, and exact commands
- Always update MEMORY.md after creating an archive
- Use descriptive filenames (e.g.,
cloudwatch-logging.mdnotsession.md) - Include YAML frontmatter with
tags,category, and optionalrelated
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 56 lines · 65 tokens per session scan A 7c8b4b025bdd
archive is a skill published in the GitHub repository ReScienceLab/opc-skills (1,873 stars, last pushed today), licensed Apache-2.0. It adds 65 tokens to every session and 498 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
context-okf-llm-ingest
Use when extracting a codebase's implementation decisions with an LLM/agent into Open Knowledge Format (OKF) files, following the repository's configured PR or candidate review gate.
create-opc-wiki
Scaffold a personal LLM wiki (Karpathy pattern) — multi-agent, MCP-ready, with SEO/GEO publish target. Compiles knowledge into a persistent wiki instead of re-deriving from raw docs on every query. One paste from any agent (OpenClaw, Claude Code, Codex, Cursor, Hermes) installs it.
wiki-lint
Audit wiki health: broken links, orphans, contradictions, stale content, lifecycle and tag issues. Use for maintenance or health checks. Default is report-only; use wiki-dedup for page-identity merges.
wiki-status
Report wiki ingestion/completeness state, pending source delta, structural insights, or maintenance equilibrium. Use for remaining-work/status questions, hubs and bridges, or whether maintenance skills still have pending changes. wiki-digest summarizes learned knowledge instead.
wiki-dashboard
Create dynamic, queryable Obsidian dashboard views using Bases or Dataview. Use for auto-updating tables, indexes, or structured views of vault content; not for ordinary question answering.
hermes-history-ingest
Ingest Hermes agent history into Obsidian as distilled knowledge. Use for importing or mining /.hermes sessions, memories, or logs; use wiki-agent for targeted topic-only cross-agent recall.