How do I install the Hmmemit skill?

Run npx skillmds@latest add vimalinx/hmmemit in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Hmmemit safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Hmmemit?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Hmmemit free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Hmmemit?

vimalinx (@vimalinx) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Hmmemit by vimalinx — Agent Skill

Name: Hmmemit
Rating: 4.2 (5 reviews)
Author: vimalinx

File contents

hmmemit

Quick Start

Command: hmmemit [-options] <hmmfile>
Local executable: /home/vimalinx/miniforge3/envs/bio/bin/hmmemit
Help reference: See references/help.md for --help failure behavior and hmmemit -h output

When To Use This Tool

Use hmmemit when you need synthetic positives or consensus representatives derived from profile HMMs.
Default mode samples unaligned sequences from the core probability model; -a emits alignments, -c emits simple consensus sequences, -C emits thresholded fancy consensus sequences, and -p samples from the fully configured search profile.
It is useful for benchmark generation, smoke tests, demo data, or sanity-checking what a model prefers.

Common Patterns

# Sample one sequence per model from the core model
hmmemit profiles.hmm > samples.fa

# Emit 20 aligned synthetic sequences per model
hmmemit -a -N 20 profile.hmm > emitted.sto

# Emit plurality-rule consensus sequences
hmmemit -c profile.hmm > consensus.fa

# Sample homolog-like sequences from the fully configured search profile
hmmemit -p -L 800 --glocal -N 10 profile.hmm > profile-samples.fa

Recommended Workflow

Decide whether you want sampled sequences, alignments, or consensus output.
Set -N and --seed before generating benchmark data so the run is reproducible and large enough for the test you care about.
Use -p only when you explicitly want search-profile behavior such as local or glocal configuration and length modeling.
Redirect the emitted output immediately into a named FASTA or Stockholm file.
If you generated multiple models' output from a library, keep the original HMM names so downstream provenance remains clear.

Guardrails

-h works; --help and --version are rejected by the local executable.
Despite the short usage string saying <hmmfile (single)>, runtime testing shows the tool will iterate across a multi-model HMM library and emit output for each model.
-L, --local, --unilocal, --glocal, and --uniglocal only apply with -p.
--minl and --minu only make sense with -C.
hmmfile may be - to read a profile stream from stdin.

---name: hmmemitdescription: Use when sampling synthetic sequences, alignments, or consensus sequences from one or more profile HMMs.---# hmmemit## Quick Start- **Command:** `hmmemit [-options] <hmmfile>`- **Local executable:** `/home/vimalinx/miniforge3/envs/bio/bin/hmmemit`- **Help reference:** See `references/help.md` for `--help` failure behavior and `hmmemit -h` output## When To Use This Tool- Use `hmmemit` when you need synthetic positives or consensus representatives derived from profile HMMs.- Default mode samples unaligned sequences from the core probability model; `-a` emits alignments, `-c` emits simple consensus sequences, `-C` emits thresholded fancy consensus sequences, and `-p` samples from the fully configured search profile.- It is useful for benchmark generation, smoke tests, demo data, or sanity-checking what a model prefers.## Common Patterns```bash# Sample one sequence per model from the core modelhmmemit profiles.hmm > samples.fa``````bash# Emit 20 aligned synthetic sequences per modelhmmemit -a -N 20 profile.hmm > emitted.sto``````bash# Emit plurality-rule consensus sequenceshmmemit -c profile.hmm > consensus.fa``````bash# Sample homolog-like sequences from the fully configured search profilehmmemit -p -L 800 --glocal -N 10 profile.hmm > profile-samples.fa```## Recommended Workflow1. Decide whether you want sampled sequences, alignments, or consensus output.2. Set `-N` and `--seed` before generating benchmark data so the run is reproducible and large enough for the test you care about.3. Use `-p` only when you explicitly want search-profile behavior such as local or glocal configuration and length modeling.4. Redirect the emitted output immediately into a named FASTA or Stockholm file.5. If you generated multiple models' output from a library, keep the original HMM names so downstream provenance remains clear.## Guardrails- `-h` works; `--help` and `--version` are rejected by the local executable.- Despite the short usage string saying `<hmmfile (single)>`, runtime testing shows the tool will iterate across a multi-model HMM library and emit output for each model.- `-L`, `--local`, `--unilocal`, `--glocal`, and `--uniglocal` only apply with `-p`.- `--minl` and `--minu` only make sense with `-C`.- `hmmfile` may be `-` to read a profile stream from stdin.

Frequently asked questions

Hmmemit