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 OpenLAIR/OpenSkill --skill evo-mars-grid-searchgit clone --depth 1 https://github.com/OpenLAIR/OpenSkillWrote 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/openlair/openskill/evo-mars-grid-search)<a href="https://agentmods.dev/skills/openlair/openskill/evo-mars-grid-search"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-mars-grid-search/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/openlair/openskill/evo-mars-grid-search"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-mars-grid-search.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 | $0.00034 | $0.00313 |
| Opus 5 | $0.00017 | $0.00156 |
| Sonnet 5 | $0.00007 | $0.00063 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
evo-mars-grid-search 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 yesterday.
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
evo-mars-grid-search
Parallel grid search over DBSCAN hyperparameters.
Key Functions
load_data(citsci_path, expert_path)- Load CSVs, return grouped dictsevaluate_hyperparameter_combo(ms, eps, sw, images, citsci_dict, expert_dict)- Eval one comborun_grid_search(unique_images, citsci_dict, expert_dict, n_jobs)- Full parallel grid searchfilter_results(results_df, min_f1=0.5)- Filter to F1 > 0.5
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-mars-grid-search/scripts')
from utils import load_data, run_grid_search, filter_results
_, _, images, citsci_dict, expert_dict = load_data('citsci.csv', 'expert.csv')
results = run_grid_search(images, citsci_dict, expert_dict)
filtered = filter_results(results)
Averaging Rules
- Loop over ALL unique images from expert dataset
- Images with no citsci points: F1=0.0, delta=NaN
- F1 average includes all zeros
- Delta average excludes NaN values
- Filter: only keep F1 > 0.5
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.
- yesterday First seen · 36 lines · 34 tokens per session scan A d02cb4088430
evo-mars-grid-search is a skill published in the GitHub repository OpenLAIR/OpenSkill (90 stars, last pushed 2d ago), licensed Apache-2.0. It adds 34 tokens to every session and 313 once invoked, about $0.0002 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 2026-09-11.
Other skills, from other repositories
fba-simulator
Run Flux Balance Analysis (FBA) and related constraint-based simulations using COBRApy. Covers standard FBA, parsimonious FBA (pFBA), Flux Variability Analysis (FVA), loopless FBA, gene/reaction knockouts, and carbon source swapping. Outputs flux distributions and CSV files.
gsmm-validator
Validate a COBRApy genome-scale metabolic model for mass/charge balance, stoichiometric consistency, biomass producibility, dead-end metabolites, thermodynamic loops, and GPR rule formatting. Outputs a structured validation report with errors and warnings.
gsmm-builder
Build or load a genome-scale metabolic model (GSMM) using COBRApy. Covers loading from BIGG, constructing minimal models from scratch, setting medium constraints, and exporting validated .json model files.
stat-result-validator
Validate statistical research outputs for formulation quality, method-to- problem alignment, theory presence, experimental evidence, fair comparison, artifact completeness, and final-claim consistency.
statistical-theory-analysis
Analyze theoretical properties of statistical methods under the formal formulation: identifiability, bias, variance, consistency, asymptotics, coverage, error bounds, robustness, and limitations.
meta-analysis
Statistical methods for combining results across multiple studies. Use when aggregating cross-study or cross-experiment results.