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/aipoch/open-science/skill-creatornpx skills add aipoch/open-science --skill skill-creatorgit clone --depth 1 https://github.com/aipoch/open-scienceWrote 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/aipoch/open-science/skill-creator)<a href="https://agentmods.dev/skills/aipoch/open-science/skill-creator"><img src="https://agentmods.dev/badge/skills/aipoch/open-science/skill-creator.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 | $0.00053 | $0.01381 |
| Opus 5 | $0.00026 | $0.00691 |
| Sonnet 5 | $0.00011 | $0.00276 |
| Haiku 4.5 | $0.00005 | $0.00138 |
Grade A, and why
skill-creator 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 4d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Creator
Create one focused, reusable Skill package. Skills are application-managed packages, not Artifacts.
Use the JavaScript control-plane REPL and the native host.skills composer for lifecycle operations.
Native composer
await host.skills.list()
await host.skills.read(name)
await host.skills.read(name, path)
await host.skills.validate(name)
await host.skills.edit(name, path, content)
await host.skills.edit(name, path, replacement, oldString)
await host.skills.publish(name)
await host.skills.publish(name, true)
await host.skills.delete(stableId)
Without oldString, edit creates a file and fails if it exists. With oldString, the old text
must occur exactly once. Never silently overwrite an existing draft file. publish promotes the
complete draft into Personal Skills. delete is privileged and always uses app approval. When a
published Skill and its draft coexist, delete only by the exact draft-<name> or personal-<name>
id returned from list(); never guess from the shared display name.
Choose the current stage
Infer where the user is in the workflow and start there:
- Capture intent and examples.
- Draft or revise the Skill.
- Review the package with the user.
- Optionally evaluate realistic prompts.
- Improve from evidence and repeat.
- Publish only after the user accepts the draft.
Do not force evaluation. Objectively verifiable workflows benefit from test cases; subjective writing or exploratory Skills may be better reviewed directly in conversation.
Capture intent
Extract what is already known from the conversation before asking questions. Confirm only gaps that materially change behavior:
- What should the Skill enable an agent to do?
- When should it trigger, including near-miss cases where it should not?
- What inputs and output formats matter?
- What counts as success, and what failures need explicit handling?
- Are scripts, references, assets, connectors, or example files required?
- Does the user want test cases now?
What ships with it
15 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.
- agents/analyzer.md 989 B
- agents/comparator.md 815 B
- agents/grader.md 1.2 KB
- assets/eval_review.html 3.5 KB
- eval-viewer/generate-review.js 4.0 KB runs code
- eval-viewer/viewer.html 4.6 KB
- references/schemas.md 3.7 KB
- scripts/aggregate-benchmark.js 1.2 KB runs code
- scripts/generate-report.js 1.4 KB runs code
- scripts/improve-description.js 1.6 KB runs code
- scripts/index.js 321 B runs code
- scripts/quick-validate.js 1.9 KB runs code
- scripts/run-eval.js 395 B runs code
- scripts/run-loop.js 793 B runs code
- scripts/utils.js 1.0 KB runs code
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.
- 4d ago First seen · 133 lines · 53 tokens per session scan A 281415eaf8ff
skill-creator is a skill published in the GitHub repository aipoch/open-science (3,497 stars, last pushed 2d ago), licensed Apache-2.0. It adds 53 tokens to every session and 1,381 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.
Other skills, from other repositories
conventions
Calkit conventions and foundational context. Load whenever working in a Calkit project—defines calkit.yaml structure, environments, pipeline stages, CLI commands, and version control conventions.
create-pipeline
Convert an existing repo with ad hoc scripts into a fully reproducible Calkit pipeline. Use when the user invokes /calkit:create-pipeline or asks to make a project reproducible end-to-end.
add-pipeline-stage
Add a single new stage to an existing Calkit pipeline. Use when the user invokes /calkit:add-pipeline-stage or asks to add a script, notebook, or command to the pipeline.
check-reproducibility
Check whether a project is fully traceable, and fix what isn't, including numbers typed into a manuscript that no pipeline output accounts for. Use when the user invokes /calkit:check-reproducibility, asks whether a project is reproducible, or asks where a number in a paper came from.
rrdoctor-verify
Use rrdoctor as the deterministic, offline definition of done for preparing a research repository for Artifact Evaluation or public release.
build-paper-pipeline
Build the pipeline stages a manuscript's TODO comments ask for.