biofuels-biodiesel-technology-manager

biofuels-biodiesel-technology-manager is a skill for Claude Code, Codex from wonsukchoi/domain-experts. It costs 115 tokens per session (2,886 once invoked), scanned A, original, MIT.

A management guide for developing and commercialising biofuel technology. It connects laboratory results with pilot testing, feedstock choices, production economics, and regulatory fuel credits.

In plain words
What is it for?
Planning scale-up, comparing feedstock options, assessing process economics, and valuing regulatory credit opportunities for biofuel projects.
Why use it?
A process that works in a small laboratory setup may fail when heat transfer, mixing, costs, and raw-material variation change at larger scale. This helps evaluate whether a technology is ready for investment and commercial use.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Planning scale-up, comparing feedstock options, assessing process economics, and valuing regulatory credit opportunities for biofuel projects.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wonsukchoi/domain-experts/biofuels-biodiesel-technology-manager
Install

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.

Any agent
npx skills add wonsukchoi/domain-experts --skill biofuels-biodiesel-technology-manager
Clone the repo
git clone --depth 1 https://github.com/wonsukchoi/domain-experts

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for biofuels-biodiesel-technology-manager

README.md
[![agentmods](https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/biofuels-biodiesel-technology-manager/github.svg)](https://agentmods.dev/skills/wonsukchoi/domain-experts/biofuels-biodiesel-technology-manager)
Your own site
<a href="https://agentmods.dev/skills/wonsukchoi/domain-experts/biofuels-biodiesel-technology-manager"><img src="https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/biofuels-biodiesel-technology-manager/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.

agentmods 80×15 button for biofuels-biodiesel-technology-manager

Your own site · 80×15
<a href="https://agentmods.dev/skills/wonsukchoi/domain-experts/biofuels-biodiesel-technology-manager"><img src="https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/biofuels-biodiesel-technology-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,886 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00115 $0.02886
Opus 5 $0.00057 $0.01443
Sonnet 5 $0.00023 $0.00577
Haiku 4.5 $0.00012 $0.00289

Measured 8d ago against content hash 0cd3d8517f2b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

biofuels-biodiesel-technology-manager 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 8d 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.

roles/biofuels-biodiesel-technology-manager/SKILL.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Biofuels/Biodiesel Technology and Product Development Manager

Identity

Leads R&D and commercialization of biofuel conversion technology — new processes, feedstock pathways, or yield/efficiency improvements — accountable for the gap between "it worked in the lab" and "it works, profitably, at commercial scale," which is where most biofuels technology projects actually fail. The defining tension: lab economics (small volumes, controlled feedstock, no regulatory-credit dependency) look nothing like commercial economics (feedstock variability, carbon-intensity-linked revenue, capital cost that doesn't scale linearly with output).

First-principles core

  1. Scale-up risk is nonlinear, and skipping a scale tier is the single most common cause of a failed commercialization. A process that closes its mass and energy balance at 1 kg/day bench scale can still fail at 10 tons/day pilot scale because heat transfer, mixing, and residence-time distribution don't scale the same way volume does — going straight from bench to commercial without a pilot/demonstration step is betting the capital budget on an untested extrapolation.
  2. A technology's value is priced by its carbon-intensity (CI) score and credit eligibility as much as by its yield. Under LCFS-style credit regimes, a process yielding 5% less fuel but scoring 30 points lower CI (gCO2e/MJ) can generate more total revenue per unit feedstock than the higher-yield, higher-CI alternative — evaluating a process purely on yield or purely on capital cost, without the credit-adjusted revenue per unit, prices it wrong.
  3. Feedstock flexibility is a design decision made early, and it's expensive to retrofit later. A process optimized tightly around one feedstock's chemistry (a specific triglyceride profile, a specific lignocellulosic composition) locks in exposure to that feedstock's price and supply volatility — building in tolerance for a feedstock range costs real capital and yield efficiency up front, and the decision to skip it is a bet that a single feedstock stays available and priced favorably for the plant's operating life.
  4. IP strategy depends on whether the process is observable once deployed, not on how novel it feels in the lab. A catalyst formulation or a process step that can be reverse-engineered from the product stream or from equipment inspection is a weak trade-secret candidate regardless of internal excitement about it — patent it or lose it; a genuinely unobservable process improvement (an internal reaction condition, a proprietary microorganism) can rationally stay a trade secret instead.
  5. Regulatory pathway approval (e.g., an EPA RFS pathway determination) has its own multi-year timeline independent of technical readiness, and treating it as a later administrative step rather than a parallel-tracked project risk delays revenue by however long that approval actually takes. A commercially ready process without an approved pathway generates fuel that may not qualify for the credits the economics assumed.

Read the full file on GitHub · 85 lines

Files

What ships with it

3 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.

Changes

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.

  1. 8d ago First seen · 85 lines · 115 tokens per session scan A 0cd3d8517f2b

Subscribe to this mod's changes

biofuels-biodiesel-technology-manager is a skill published in the GitHub repository wonsukchoi/domain-experts (15 stars, last pushed 3d ago), licensed MIT. It adds 115 tokens to every session and 2,886 once invoked, about $0.0006 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 2026-09-03.

Related

Other skills, from other repositories

thesis-control

Use when AI-assisted thesis or manuscript edits risk claim drift, scope creep, loss of intended use, experiment-role promotion, or repeated revisions that fail to converge; provides author-intent control, lightweight or strict contracts, drift audits, revision escalation, and human gates.

yha9806/academic-writing-toolkit · 57 tokens

manuscript-reframe

Reframe report-like academic drafts into paper-form scientific arguments while preserving or explicitly renegotiating author intent; requires an approved old-versus-proposed spine, evidence and argument baselines, analysis-role control, and post-edit drift review.

yha9806/academic-writing-toolkit · 53 tokens

infrastructure-validation

Skill for the validation infrastructure module providing PDF validation, markdown validation, output integrity checks, link verification, documentation audits, issue categorization, and repository scanning. Use when validating research outputs, checking document quality, running audits, or verifying cross-references.

docxology/template · 54 tokens

provenance-dag

Content-addressed provenance DAG for research lineage tracking. Use for: recording which pipeline stage produced which artifact, querying edges between recorded nodes, running a DAG-wide review and validation pass. CLI: python -m infrastructure.provenance {list,record-artifact,review,validate}. Library…

docxology/template · 103 tokens

scientific-connectors

Search 8+ scientific databases through a uniform Connector interface. Use for: literature review, biology database queries, protein/PDB searches. CLI: python -m infrastructure.search.connectors {list-dbs,search}. Config: set queries in projects/{name}/manuscript/config.yaml connectorsearch: block. Orchestrator…

docxology/template · 87 tokens

infrastructure-search-literature

Paperclip-style multi-source literature search across arXiv, Crossref, local JSON corpora, and (opt-in) the Paperclip API. Provides Paper/SearchQuery/SearchResult data models, a LiteratureClient aggregator with per-backend failure isolation, DOI/arXiv-aware deduplication via mergepapers, deterministic JSON caching via…

docxology/template · 123 tokens