How do I install the Mfa Pipeline Orchestrator skill?

Run npx skillmds@latest add gabrielmoreira/mfa-pipeline-orchestrator 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 Mfa Pipeline Orchestrator safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Mfa Pipeline Orchestrator?

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 Mfa Pipeline Orchestrator free to use?

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

Who published Mfa Pipeline Orchestrator?

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

Mfa Pipeline Orchestrator by gabrielmoreira

Name: Mfa Pipeline Orchestrator
Rating: 4.2 (5 reviews)
Author: gabrielmoreira

Mfa Pipeline Orchestrator

Orchestrate the full metabolic flux analysis pipeline from model loading to phenotype prediction and publication figures. Triggers when the user provides an organism name, BIGG model ID, or custom reaction list and wants end-to-end metabolic modelling run automatically.

gabrielmoreira Updated Sep 9, 2026 17 repo stars

File contents

MFA Pipeline Orchestrator

Overview

Coordinates all mfa-agent sub-agents in sequence, tracking progress via progress/ markdown files so any failed step can be resumed independently.

Full pipeline:

Model source (BIGG ID / custom reactions)
  → [model-builder]     models/<Model>.json  +  validation report
  → [fba-runner]        simulations/fba_fluxes.csv  +  scan_summary.json
  → [flux-analyzer]     analysis/essentiality.csv  +  phase_plane.png
  → [metabolic-pheno-analyzer]  output/figures/*.pdf  +  yield table

Workflow

Step 0: Parse User Request

Extract and record in progress/step0_inputs.md:

Model source (BIGG ID or custom)
Organism and condition (aerobic/anaerobic, carbon source, concentration)
Objective reaction (biomass or product)
Gene knockouts to apply
Analysis goals (essentiality, phase plane, yield optimisation, WT vs. mutant comparison)
Target product (if yield analysis requested)

Step 1: Invoke model-builder

Provide: model source, medium constraints, objective, knockouts. Wait for progress/step1_metabolic_model.md. Read: model file path, WT growth rate, model statistics.

Step 2: Invoke fba-runner

Provide: model path, simulation types requested (FBA, pFBA, FVA, knockout screen), carbon source sweep if requested. Wait for progress/step2_fba_simulation.md. Read: flux CSV paths, essential gene count, secretion fluxes.

Step 3: Invoke flux-analyzer

Provide: model path, FBA results, analysis goals (essentiality, phase plane, sampling), nutrient pair for phase plane. Wait for progress/step3_flux_analysis.md. Read: essential genes, phase plane optimum, engineering targets.

Step 4: Invoke metabolic-pheno-analyzer

Provide: model path, all previous results, target product, publication requirements. Wait for progress/step4_metabolic_phenotype.md. Read: max theoretical yield, figure paths.

Progress File Specification

`progress/step1_metabolic_model.md`

# Step 1: Metabolic Model
## Status: PASS / FAIL
## Model: <BIGG_ID>.json
## Reactions: N  Metabolites: M  Genes: G
## WT growth rate: X h⁻¹
## Validation: mass balance errors=0, dead-ends=N

`progress/step2_fba_simulation.md`

# Step 2: FBA Simulation
## Status: PASS / FAIL
## Runs: FBA, pFBA, FVA, knockout screen
## WT growth rate: X h⁻¹ (pFBA: Y h⁻¹)
## Essential genes: N
## Key secretion products: [ethanol: X mmol/gDW/h, ...]
## Files: simulations/fba_fluxes.csv, simulations/gene_essentiality.csv

`progress/step3_flux_analysis.md`

# Step 3: Flux Analysis
## Status: PASS / FAIL
## Essential gene count: N
## Phase plane optimum: glucose=X, O2=Y → growth=Z h⁻¹
## Top engineering targets: [gene1, gene2, gene3]
## Files: analysis/phase_plane.png, analysis/essentiality.csv

Key Conventions

Never re-run completed steps — check progress file status before invoking sub-agents
Maximum total sub-agent retries: 10 across all steps
All file paths relative to working directory
The orchestrator does not run FBA itself — all computation delegated to sub-agents

---name: mfa-pipeline-orchestratordescription: Orchestrate the full metabolic flux analysis pipeline from model loading to phenotype prediction and publication figures. Triggers when the user provides an organism name, BIGG model ID, or custom reaction list and wants end-to-end metabolic modelling run automatically.--- # MFA Pipeline Orchestrator ## Overview Coordinates all mfa-agent sub-agents in sequence, tracking progress via `progress/` markdown files so any failed step can be resumed independently. **Full pipeline:** ``` Model source (BIGG ID / custom reactions) → [model-builder] models/<Model>.json + validation report → [fba-runner] simulations/fba_fluxes.csv + scan_summary.json → [flux-analyzer] analysis/essentiality.csv + phase_plane.png → [metabolic-pheno-analyzer] output/figures/*.pdf + yield table ``` ## Workflow ### Step 0: Parse User Request Extract and record in `progress/step0_inputs.md`: - Model source (BIGG ID or custom) - Organism and condition (aerobic/anaerobic, carbon source, concentration) - Objective reaction (biomass or product) - Gene knockouts to apply - Analysis goals (essentiality, phase plane, yield optimisation, WT vs. mutant comparison) - Target product (if yield analysis requested) ### Step 1: Invoke model-builder Provide: model source, medium constraints, objective, knockouts. Wait for `progress/step1_metabolic_model.md`. Read: model file path, WT growth rate, model statistics. ### Step 2: Invoke fba-runner Provide: model path, simulation types requested (FBA, pFBA, FVA, knockout screen), carbon source sweep if requested. Wait for `progress/step2_fba_simulation.md`. Read: flux CSV paths, essential gene count, secretion fluxes. ### Step 3: Invoke flux-analyzer Provide: model path, FBA results, analysis goals (essentiality, phase plane, sampling), nutrient pair for phase plane. Wait for `progress/step3_flux_analysis.md`. Read: essential genes, phase plane optimum, engineering targets. ### Step 4: Invoke metabolic-pheno-analyzer Provide: model path, all previous results, target product, publication requirements. Wait for `progress/step4_metabolic_phenotype.md`. Read: max theoretical yield, figure paths. ## Progress File Specification ### `progress/step1_metabolic_model.md` ```markdown # Step 1: Metabolic Model ## Status: PASS / FAIL ## Model: <BIGG_ID>.json ## Reactions: N Metabolites: M Genes: G ## WT growth rate: X h⁻¹ ## Validation: mass balance errors=0, dead-ends=N ``` ### `progress/step2_fba_simulation.md` ```markdown # Step 2: FBA Simulation ## Status: PASS / FAIL ## Runs: FBA, pFBA, FVA, knockout screen ## WT growth rate: X h⁻¹ (pFBA: Y h⁻¹) ## Essential genes: N ## Key secretion products: [ethanol: X mmol/gDW/h, ...] ## Files: simulations/fba_fluxes.csv, simulations/gene_essentiality.csv ``` ### `progress/step3_flux_analysis.md` ```markdown # Step 3: Flux Analysis ## Status: PASS / FAIL ## Essential gene count: N ## Phase plane optimum: glucose=X, O2=Y → growth=Z h⁻¹ ## Top engineering targets: [gene1, gene2, gene3] ## Files: analysis/phase_plane.png, analysis/essentiality.csv ``` ## Key Conventions - **Never re-run completed steps** — check progress file status before invoking sub-agents - **Maximum total sub-agent retries: 10** across all steps - **All file paths relative to working directory** - **The orchestrator does not run FBA itself** — all computation delegated to sub-agents

Frequently asked questions