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 li-ch/law-skills --skill law-bootstrapgit clone --depth 1 https://github.com/li-ch/law-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/li-ch/law-skills/law-bootstrap)<a href="https://agentmods.dev/skills/li-ch/law-skills/law-bootstrap"><img src="https://agentmods.dev/badge/skills/li-ch/law-skills/law-bootstrap/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/li-ch/law-skills/law-bootstrap"><img src="https://agentmods.dev/badge/skills/li-ch/law-skills/law-bootstrap.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 | $0.00067 | $0.00812 |
| Opus 5 | $0.00034 | $0.00406 |
| Sonnet 5 | $0.00013 | $0.00162 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
law-bootstrap 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.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LAW Bootstrap
Create a new academic paper repository from scratch. This skill initializes the directory structure, copies venue-specific templates, sets up git, and generates AGENTS.md with the paper's metadata.
Venue template mapping
Read ~/.common-law/paper-style/venue-map.md for the authoritative mapping of venues to document classes, style files, bib styles, page limits, and anonymization requirements.
Supported venues: nsdi, sigcomm, apnet, arxiv.
Workflow
Step 1: Gather parameters interactively
Ask the user for each parameter. Do not proceed until all required parameters are provided and confirmed. Do not create anything if any parameter is unclear.
Required:
- Paper name (short lowercase identifier, e.g.,
swiftcache) - Venue (
nsdi,sigcomm,apnet, orarxiv) - Year (e.g.,
2027)
Optional:
- Cycle (
spring,fall,cycle-2, etc.) — for venues with multiple deadlines
If the user provides all parameters in one message (e.g., "create a new paper called swiftcache for NSDI 2027 spring"), extract them and confirm before proceeding.
Step 2: Validate
- Check that the venue is in the venue-map
- Check that the target directory does not already exist
- If it exists, warn and ask for confirmation
Step 3: Create the paper
Run scripts/new-paper.sh with the gathered parameters:
bash scripts/new-paper.sh --name <name> --venue <venue> --year <year> [--cycle <cycle>]
The script:
- Creates the directory
{name}-{venue}-{year}[-{cycle}] - Copies
assets/template/into the new directory - Copies the appropriate venue template files from
assets/venue-templates/{venue}/into the paper root - Copies
~/.common-law/paper-style/CLAUDE.mdinto the paper root - Appends the paper narrative placeholder to CLAUDE.md
- Copies
~/.common-law/bib/refs.bibinto the paper root asrefs.bib - Initializes git with
.gitignoreand creates an initial commit - Writes
AGENTS.mdwith venue and page limit filled in, placeholders for human-filled fields
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.
- assets/template/.gitignore 103 B
- assets/template/templates/dev.plan.md 681 B
- assets/template/templates/todo.md 688 B
- assets/venue-templates/apnet/ACM-Reference-Format.bst 80 KB
- assets/venue-templates/apnet/acmart.cls 82 KB
- assets/venue-templates/apnet/main.tex 1.6 KB
- assets/venue-templates/arxiv/main.tex 1.6 KB
- assets/venue-templates/arxiv/PRIMEarxiv.sty 7.5 KB
- assets/venue-templates/nsdi/main.tex 1.5 KB
- assets/venue-templates/nsdi/usenix2019_v3.sty 3.7 KB
- assets/venue-templates/sigcomm/ACM-Reference-Format.bst 80 KB
- assets/venue-templates/sigcomm/acmart.cls 82 KB
- assets/venue-templates/sigcomm/main.tex 1.6 KB
- scripts/new-paper.bat 3.5 KB runs code
- scripts/new-paper.sh 6.1 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.
- 10d ago First seen · 82 lines · 67 tokens per session scan A 0f82de2a6c4d
law-bootstrap is a skill published in the GitHub repository li-ch/law-skills (11 stars, last pushed 1mo ago), licensed MIT. It adds 67 tokens to every session and 812 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
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…