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 xuansenpa1/skillrevise --skill seismic-picker-selectiongit clone --depth 1 https://github.com/xuansenpa1/skillreviseWrote 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/xuansenpa1/skillrevise/seismic-picker-selection)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/seismic-picker-selection"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/seismic-picker-selection/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/xuansenpa1/skillrevise/seismic-picker-selection"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/seismic-picker-selection.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 | $0.00052 | $0.00846 |
| Opus 5 | $0.00026 | $0.00423 |
| Sonnet 5 | $0.00010 | $0.00169 |
| Haiku 4.5 | $0.00005 | $0.00085 |
Grade A, and why
seismic-picker-selection 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 10d 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.
This is a copy
100% identical to seismic-picker-selection — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Seismic Event Detection & Phase Picking Method Selection Guide
Overview: Method Tradeoffs
When choosing an event detection and phase picking method, consider these key tradeoffs:
| Method | Generalizability | Sensitivity | Speed, Ease-of-Use | False Positives |
|---|---|---|---|---|
| STA/LTA | High | Low | Fast, Easy | Many |
| Manual | High | High | Slow, Difficult | Few |
| Deep Learning | High | High | Fast, Easy | Medium |
| Template Matching | Low | High | Slow, Difficult | Few |
- Generalizability: Ability to find arbitrary earthquake signals
- Sensitivity: Ability to find small earthquakes
Key insight: Each method has strengths and weaknesses. Purpose and resources should guide your choice.
STA/LTA (Short-Term Average / Long-Term Average)
Advantages
- Runs very fast: Automatically operates in real-time
- Easy to understand & implement: Can optimize for different window lengths and ratios
- No prior knowledge needed: Does not require information about earthquake sources or waveforms
- Amplitude-based detector: Reliably detects large earthquake signals
Limitations
- High rate of false detections during active sequences
- Automatic picks not as precise
- Requires manual review and refinement of picks for a quality catalog
Template Matching
Advantages
- Optimally sensitive detector (more sensitive than deep-learning): Can find smallest earthquakes buried in noise, if similar enough to template waveform
- Excellent for improving temporal resolution of earthquake sequences
- False detections are not as concerning when using high detection threshold
Limitations
- Requires prior knowledge about earthquake sources: Need template waveforms with good picks from a preexisting catalog
- Does not improve spatial resolution: Unknown earthquake sources that are not similar enough to templates cannot be found
- Setup effort required: Must extract template waveforms and configure processing
- Computationally intensive
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.
- 10d ago First seen · 82 lines · 52 tokens per session scan A 20ff09362d21
seismic-picker-selection is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 5d ago), licensed MIT. It adds 52 tokens to every session and 846 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to seismic-picker-selection, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…