est-data-analysis — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited est-data-analysis (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
ES&T reviewers scrutinize the analytical chain: blanks, recoveries, detection limits, replicates, and whether the numbers add up. This skill covers execution and reporting; design decisions live in est-study-design, and deposit/reproducibility in est-reporting-and-reproducibility.
calibration range and R², surrogate/internal-standard recoveries, and how non-detects were handled.
values; propagate uncertainty through derived quantities; state n every time.
(e.g., substitution caveats, MLE/ROS, Kaplan–Meier); check distributional assumptions; use nonparametric or transformed analyses for skewed/heteroscedastic data; correct for multiple comparisons.
report closure (%) and explain gaps.
EC/IC/LC values with confidence bounds; state the model fitted.
to environmentally meaningful thresholds.
est-reporting-and-reproducibility).ES&T referees often work down a mental analytical checklist. Reporting each item pre-empts the most common "rigor not established" objection. The minimum set, with what a reviewer reads when it is absent:
| Element | What to report | If omitted, the reviewer assumes |
|---|---|---|
| Method/field blanks | blank levels vs. sample levels; subtraction approach | contamination is uncontrolled |
| Recoveries | matrix-spike % and CRM agreement | quantitation is biased/unknown |
| LOD/LOQ | derivation (e.g., 3σ/10σ or S/N) and per-analyte values | "detections" may be noise |
| Calibration | range, R², whether samples fall in range | extrapolation beyond standards |
| Surrogate/IS recoveries | per-sample recovery correction | run-to-run drift hidden |
| Non-detects | censoring method (ROS/MLE/KM), not bare substitution | summary statistics distorted |
A river-PFAS dataset (illustrative numbers) shows how the rules combine into a reportable result:
3.1 ng/L; regression-on-order-statistics (ROS) gives 2.4 ng/L (illustrative), because substitution inflated the low tail. Report the ROS mean with its CI and state the method.
single line carries magnitude, uncertainty, n, censoring handling, and recovery — the form a reviewer can sign off without a query.
and cite it from Methods; never leave it implicit.
result is robust to the censoring choice.
volatilized, mineralized), and bound it rather than ignoring the gap.
【Main result】magnitude + uncertainty (n, SD/CI) + units
【QA/QC】blanks / recoveries / CRM / LOD-LOQ / calibration reported? [Y/N]
【Censored data】handled how
【Mass/energy balance】closure % + explanation
【Statistics】appropriate test + assumptions checked? [Y/N]
【Reproducible】master script + seeds + pinned versions? [Y/N]
【Next】est-figures-and-tables../../resources/external_tools.md — analytical QA/QC, statistics, and modeling packages../../resources/official-source-map.md — data-availability and reproducibility expectations~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.