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 Zhang-Henry/CoEvoSkills --skill evo-proteomics-workbookgit clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkillsWrote 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/zhang-henry/coevoskills/evo-proteomics-workbook)<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/evo-proteomics-workbook"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-proteomics-workbook/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/zhang-henry/coevoskills/evo-proteomics-workbook"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-proteomics-workbook.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00078 | $0.00487 |
| Opus 5 | $0.00039 | $0.00244 |
| Sonnet 5 | $0.00016 | $0.00097 |
| Haiku 4.5 | $0.00008 | $0.00049 |
Grade A, and why
evo-proteomics-workbook 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 11d 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.
What it actually says
Proteomics Workbook Skill
This skill automates filling a proteomics analysis workbook with formulas:
- Expression Lookups (C11:L20): INDEX-MATCH formulas to pull values from Data sheet
- Group Statistics (B24:K27): AVERAGE and STDEV for Control and Treated groups
- Fold Change (rows 32-41): Log2 FC = Treated Mean - Control Mean; FC = 2^(Log2FC)
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-proteomics-workbook/scripts')
from utils import run_end_to_end
success = run_end_to_end('/root/protein_expression.xlsx')
if success:
print('Task completed successfully')
else:
print('Validation failed - check errors above')
Key Functions
discover_task_layout(ws_task)- Discovers proteins, samples, groups, and cell rangesdiscover_data_layout(ws_data)- Builds protein-row and sample-column indiceswrite_expression_formulas(ws_task, task_layout, data_layout)- INDEX-MATCH formulaswrite_statistics_formulas(ws_task, task_layout)- AVERAGE/STDEV per protein per groupwrite_fold_change_formulas(ws_task, task_layout)- Log2FC and FC formulasrecalculate_with_libreoffice(filepath)- Headless recalculationvalidate_workbook(filepath)- Checks all output cells for numeric valuesrun_end_to_end(input_path, output_path=None)- Full pipeline
Design Notes
- All layouts discovered at runtime from the workbook
- Formulas reference cells, not hard-coded values
- Statistics reference expression cells in the Task sheet
- Control/Treated group membership read from row 9
- LibreOffice recalculates cached formula values
- Validation checks for formula errors (#REF!, #NAME?, etc.)
What ships with it
1 file 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.
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.
- 11d ago First seen · 47 lines · 78 tokens per session scan A d6002d5ff558
evo-proteomics-workbook is a skill published in the GitHub repository Zhang-Henry/CoEvoSkills (66 stars, last pushed 21d ago), licensed Apache-2.0. It adds 78 tokens to every session and 487 once invoked, about $0.0004 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.
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